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PHYSICAL THERAPY

IJSPT international JOURNAL OF SPORTS

Board of Directors / Business Advisory Board

Turner A Blackburn, APTA Life Member, AT-Ret, AOSSM-Ret President

Mary Wilkinson Executive Director

Michael Voight Executive Editor and Publisher

Joe Black, PT, DPT, SCS, ATC

Eric Fernandez

Jay Greenstein, DC

Skip Hunter, PT, ATC-Ret

Russ Paine, PT, DPT

Tim Tyler, PT, ATC

Sports Legacy Advisory Board

Turner A. Blackburn, PT, ATC

George Davies, PT, DPT, MEd, SCS, ATC, LAT, CSCS, PES, FAPTA

Terry Malone, PT, PhD

Bob Mangine, PT

Barb Sanders, PT, PhD

Tim Tyler, PT, ATC

Kevin Wilk, PT, DPT, FAPTA

Staff

Executive Editor/Publisher

Michael L. Voight, PT, DHSc, OCS, SCS, ATC, CSCS

Executive Director/Operations and Marketing

Mary Wilkinson

Editor in Chief

Barbara Hoogenboom, PT, EdD, SCS, ATC

Managing Editor

Ashley Campbell, PT, DPT, SCS

Manuscript Coordinator

Casey Lewis, PTA, ATC

NORTH AMERICAN SPORTS MEDICINE INSTITUTE

Publisher

Contact Information

International Journal of Sports Physical Therapy 6011 Hillsboro Pike Nashville, TN 37215, US, http://www.ijspt.org

IJSPT is a monthly publication, with release dates on the first of each month.

ISSN 2159-2896

Underwriting Sponsor Genie Health

Founding Sponsors Enovis Exertools Hyperice Trazer Woodway

Platinum Sponsors ATI Elvation

Gold Sponsors Hawkgrips Kayezen Structure + Function Education Winback Partners

Northeast Seminars Academy of Human Movement American Academy of Sports Physical Therapy

IJSPT is an official journal of the International Federation of Sports Physical Therapy (IFSPT). Countries with access to IJSPT as a member benefit. Reach us at www.ifspt.org.

IJSPT is an official journal of the ICCUS Society for Sports Rehabilitation. www.iccus.org

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IJSPT

Executive Editor/Publisher

INTERNATIONAL

JOURNAL OF SPORTS PHYSICAL THERAPY

Michael L. Voight, PT, DHSc, OCS, SCS, ATC, CSCS

Belmont University

Nashville, Tennessee – USA

Editor in Chief

Barbara Hoogenboom, PT, EdD, SCS, ATC

Grand Valley State University Grand Rapids, Michigan - USA

Managing Editor

Ashley Campbell, PT, DPT, SCS

Nashville Sports Medicine and Orthopaedic Center Nashville, Tennessee – USA

Manuscript Coordinator

Casey Lewis, PTA, ATC

Nashville Sports Medicine and Orthopaedic Center

Nashville, Tennessee – USA

Executive Director/Marketing

Mary Wilkinson

Indianapolis, Indiana – USA

Editors

Robert Manske PT, DPT, Med, SCS, ATC, CSCS

University of Wichita Wichita, KS, USA

Terry Grindstaff, PT, PhD, ATC, SCS, CSCS

Creighton University Omaha, NE, USA

Phil Page PT, PhD, ATC, CSCS

Franciscan University DPT Program Baton Rouge, LA, USA

Kevin Wilk PT, DPT, FAPTA

Clinical Viewpoint Editor Champion Sports Medicine Birmingham, AL, USA

International Editors

Luciana De Michelis Mendonça, PT, PhD UFVJM

Diamantina, Brazil

Colin Paterson PT, MSc PGCert(Ed), MCSP, RISPT, SFHEA

University of Brighton Brighton, England, UK

Chris Napier, PT, PhD

Clinical Assistant Professor

University of British Coumbia, Vancouver, BC, Canada

Nicola Phillips, OBE, PT, PhD, FCSP

Professor School of Healthcare Sciences Cardiff University, Cardiff, Wales, UK

Associate Editors

Eva Ageberg, PT, PhD

Professor, Lund University Lund, Sweden

Lindsay Becker, PT, DPT, SCS, USAW Buckeye Performance Golf Dublin, Ohio, USA

Keelan Enseki, PT, MS, OCS, SCS, ATC University of Pittsburgh Pittsburgh, PA, USA

John Heick, PT, PhD, DPT, OCS, NCS, SCS

Northern Arizona University

Flagstaff, AZ, USA

Julie Sandell Jacobsen, MHSc, PhD

VIA University

Aarhus, Denmark

RobRoy L. Martin, PhD, PT, CSCS

Duquesne University Pittsburgh, PA, USA

Andrea Mosler, PhD, FACP, FASMF

La Trobe Sport and Exercise Medicine Research Centre, School of Allied Health, Human Services and Sport, La Trobe University

Melbourne, Victoria, Australia

Brandon Schmitt, DPT, ATC

PRO Sports Physical Therapy Scarsdale, NY, USA

Barry Shafer, PT, DPT

Elite Motion Physical Therapy Arcadia, CA, USA

Laurie Stickler, PT, DHSc, OCS

Grand Valley State University

Grand Rapids, MI, USA

Editorial Board

James Andrews, MD

Andrews Institute & Sports Medicine Center

Gulf Breeze, AL, USA

Amelia (Amy) Arundale, PT, PhD, DPT, SCS

Red Bull/Ichan School of Medicine

Salzburg, Austria/New York, NY, USA

Gary Austin, PT PhD

Belmont University Nashville, TN, USA

Roald Bahr, MD

Oslo Sports Trauma Research Center Oslo, Norway

Lane Bailey, PT, PhD

Memorial Hermann IRONMAN Sports Medicine Institute

Houston, Texas, USA

Gül Baltaci, PT,Ph.D. Professor, CKTI, FACSM

Private Guven Hospital Ankara, Turkey

Asheesh Bedi, MD

University of Michigan

Ann Arbor, MI, USA

David Behm, PhD Memorial University of Newfoundland St. John's, Newfoundland, Canada

Barton N. Bishop, PT, DPT, SCS, CSCS Kaizo Clinical Research Institute Rockville, Maryland, USA

Mario Bizzini, PhD, PT Schulthess Clinic Human Performance Lab Zürich, Switzerland

Joe Black, PT, DPT, SCS, ATC Total Rehabilitation Maryville, Tennesse, USA

Turner A. "Tab" Blackburn, APTA Life Member, ATC-Ret, AOSSM-Ret NASMI Lanett, AL, USA

Lori Bolgla, PT, PhD, MAcc, ATC Augusta University Augusta, Georgia, USA

Matthew Briggs The Ohio State University Columbus, OH, USA

Tony Brosky, PT, DHSc, SCS Bellarmine University Louisville, KY, USA

Brian Busconi, MD UMass Memorial Hospital Boston, MA, USA

Robert J. Butler, PT, PhD St. Louis Cardinals St. Louis, MO, USA

Duane Button, PhD Memorial University St. Johns, Newfoundland, Canada

J. W. Thomas Byrd, MD Nashville Sports Medicine and Orthopaedic Center Nashville, TN, USA

Lyle Cain, MD Andrews Institute & Sports Medicine Center Birmingham, AL, USA

Gary Calabrese, PT, DPT Cleveland Clinic Cleveland, Ohio, USA

Meredith Chaput, PT, DPT, SCS Ohio University Athens, OH, USA

Rita Chorba, PT, DPT, MAT, SCS, ATC, CSCS United States Army Special Operations Command Fort Campbell, KY, USA

John Christoferreti, MD Texas Health Dallas, TX, USA

Richard Clark, PT, PhD Tennessee State University Nashville, TN, USA

Juan Colado, PT, PhD University of Valencia Valencia, Spain

Brian Cole, MD Midwest Orthopaedics at Rush Chicago, IL, USA

Ann Cools, PT, PhD

Ghent University Ghent, Belgium

Andrew Contreras, DPT, SCS Washington, DC, USA

George Davies, PT, DPT, MEd, SCS, ATC, LAT, CSCS, PES, FAPTA

Georgia Southern University Savannah, Georgia, USA

Pete Draovich, PT

Jacksonville Jaguars Footbal Jacksonvile, FL, USA

Jeffrey Dugas, MD Andrews Institute & Sports Medicine Center Birmingham, AL, USA

Jiri Dvorak, MD Schulthess Clinic Zurich, Switzerland

Todd Ellenbecker Rehab Plus Phoenix, AZ, USA

Carolyn Emery, PT, PhD University of Calgary Calgary, Alberta, Canada

Ernest Esteve Caupena, PT, PhD University of Girona Girona, Spain

Sue Falsone, PT, MS, SCS, ATC, CSCS, COMT Structure and Function Education and A.T. Still University Phoenix, Arizona, USA

J. Craig Garrison, PhD, PT, ATC, SCS Texas Health Sports Medicine Fort Worth, Texas, USA

Maggie Gebhardt, PT, DPT, OCS, FAAOMPT Fit Core Physical Therapy/Myopain Seminars Atlanta, GA and Bethesda, MD, USA

Lance Gill, ATC

LG Performance-TPI Oceanside, CA, USA

Phil Glasgow, PhD, MTh, MRes, MCSP Sports Institute of Northern Ireland Belfast, Northern Ireland, UK

Robert S. Gray, MS, AT Cleveland Clinic Sports Health Cleveland, Ohio, USA

Jay Greenstein, DC Kaizo Health Baltimore, MD, USA

EDITORIAL BOARD

Martin Hagglund, PT PhD

Linkoping University Linkoping, Sweden

Allen Hardin, PT, SCS, ATC, CSCS

University of Texas Austin, TX, USA

Richard Hawkins, MD

Professor of surgery, University of South Carolina

Adjunct Professor, Clemson University

Principal, Steadman Hawkins, Greenville and Denver (CU)

John D.Heick, PT, PhD, DPT, OCS, NCS, SCS

Northern Arizona University Flagstaff, AZ, USA

Tim Hewett, PhD

Hewett Consulting Minneapolis, Minnesota, USA

Per Hølmich, MD

Copenhagen University Hospital Copenhagen, Denmark

Kara Mae Hughes, PT, DPT, CSCS

Wolfe PT Nashville, TN, USA

Lasse Ishøi, PT, MSc

Sports Orthopedic Research Center

Copenhagen University Hospital Hvidovre, Denmark

Jon Karlsson, MD Sahlgrenska University Goteborg, Sweden

Brian Kelly, MD Hospital for Special Surgery New York, NY, USA

Benjamin R. Kivlan, PhD, PT, OCS, SCS Duquesne University Pittsburgh, PA, USA

Dave Kohlrieser, PT, DPT, SCS, OCS, CSCS

Ortho One Columbus, OH, USA

Andre Labbe PT, MOPT

Tulane Institute of Sports Medicine New Orleans, LA USA

Henning Langberg, PT, PhD University of Copenhagen Copenhagen, Denmark

Robert LaPrade, MD Twin Cities Orthopedics Edina, MN, USA

Lace Luedke, PT, DPT University of Wisconsin Oshkosh Oshkosh, WI, USA

Phillip Malloy, PT, PhD

Arcadia University/Rush University Medical Center Glenside, PA and Chicago, IL, USA

Terry Malone, PT, EdD, ATC, FAPTA University of Kentucky Lexington, KY, USA

Robert Mangine, PT University of Cincinnati Cincinnati, OH, USA

Eric McCarty, MD University of Colorado Boulder, CO, USA

Ryan P. McGovern, PhD, LAT, ATC Texas Health Sports Medicine Specialists Dallas/Fort Worth, Texas, USA

Mal McHugh, PhD

NISMAT

New York, NY, USA

Joseph Miller, PT, DSc, OCS, SCS, CSCS

Pikes Peak Community College Colorado Springs, CO, USA

Havard Moksnes, PT PhD

Oslo Sports Trauma Research Center Oslo, Norway

Andrew Murray, MD, PhD

European PGA Tour Edinburgh, Scotland, UK

Andrew Naylor, PT, DPT, SCS

Bellin Health

Green Bay, WI, USA

Stephen Nicholas, MD NISMAT New York New York, NY, USA

John O'Donnel, MD

Royal Melbourne Hospital Melbourne, Australia

Russ Paine, PT McGovern Medical School Houston, TX, USA

Snehal Patel, PT, MSPT, SCD

HSS Sports Rehabilitation Institute New York, NY, USA

Marc Philippon, MD

Steadman-Hawkins Clinic Vail, CO, USA

Kevin Plancher, MD, MPH, FAAOS

Plancher Orthopedics and Sports Medicine

New York, NY USA

Marisa Pontillo, PT, PhD, DPT, SCS

University of Pennsylvania Health System Philadelphia, PA, USA

Matthew Provencher, MD

Steadman Hawkins Clinic Vail, CO, USA

Charles E. Rainey, PT, DSc, DPT, MS, OCS, SCS, CSCS, FAAOMPT

United States Public Health Service Springfield, MO, USA

EDITORIAL BOARD

Alexandre Rambaud, PT PhD Saint-Etienne, France

Carlo Ramponi, PT Physiotherapist, Kinè Rehabilitation and Orthopaedic Center Treviso, Italy

Michael Reiman, PT, PhD Duke University Durham, NC, USA

Mark F. Reinking, PT, PhD, SCS, ATC Regis University Denver, CO, USA

Mark Ryan, ATC Steadman-Hawkins Clinic Vail, CO, USA

David Sachse, PT, DPT, OCS, SCS USAF San Antonio, TX, USA

Marc Safran, MD Stanford University Palo Alto, CA, USA

Alanna Salituro, PT, DPT, SCS, CSCS New York Mets Port Saint Lucie, FL, USA

Mina Samukawa, PT, PhD, AT (JSPO) Hokkaido University Sapporo, Japan

Barbara Sanders, PT, PhD, FAPTA, Board Certified Sports Physical Therapy Emeritus Professor and Chair, Department of Physical Therapy Texas State University Round Rock, TX, USA

Felix “Buddy” Savoie, MD, FAAOS Tulane Institute of Sport Medicine New Orleans, LA, USA

Teresa Schuemann, PT, DPT, ATC, CSCS, Board Certified Specialist in Sports Physical Therapy Evidence in Motion Fort Collins, CO, USA

Timothy Sell, PhD, PT, FACSM Atrium Health Musculoskeletal Institute Charlotte, NC, USA

Andreas Serner, PT PhD

Aspetar Orthopedic and Sports Medicine Hospital Doha, Qatar

Ellen Shanley, PT, PhD ATI Spartanburg, SC, USA

Karin Silbernagel, PT, PhD University of Delaware Newark, DE, USA

Holly Silvers, PT, PhD Velocity Physical Therapy Los Angeles, CA, USA

Lynn Snyder-Mackler, PT, ScD, FAPTA STAR University of Delaware Newark, DE, USA

Alston Stubbs, MD Wake Forest University Winston-Salem, NC, USA

Amir Takla, B.Phys, Mast.Physio (Manip), A/Prof

Australian Sports Physiotherapy The University of Melbourne Melbourne, Australia

Charles Thigpen, PhD, PT, ATC ATI

Spartanburg, SC, USA

Steven Tippett, PT, PhD, ATC, SCS Bradley University Peoria, IL, USA

Tim Tyler, PT, ATC NISMAT New York, NY, USA

Timothy Uhl, PT, PhD, ATC University of Kentucky Lexington, KY, USA

Bakare Ummukulthoum, PT University of the Witswatersrand Johannesburg, Gauteng, South Africa

Yuling Leo Wang, PT, PhD Sun Yat-sen University Guangzhou, China

Mark D. Weber, PT, PhD, SCS, ATC Texas Women’s University Dallas, TX, USA

Richard B. Westrick, PT, DPT, DSc, OCS, SCS US Army Research Institute Boston, MA, USA

Chris Wolfe, PT, DPT Belmont University Nashville, TN, USA

Tobias Wörner, PT, MSc Lund University Stockholm, Sweden

VOLUME 19, NUMBER 11

PAGE TITLE

THE BRAIN AND SPORTS: Neurocognitive Enriched Rehabilitation

In Collaboration with Sportfisio Switzerland.

EDITORIAL

1289 The Power of International Cooperation.

Voight M, Hoogenboom B, Campbell A, Bizzini M.

1290 Monitoring Cortical and Neuromuscular Activity: Six-month Insights into Knee Joint Position Sense Following ACL Reconstruction.

Busch A, Gianotti LRR, Mayer F, et al.

1304 Increased Visual Attentional Demands Alter Lower Extremity Sidestep Cutting Kinematics in Male Basketball Players.

Rikken KTH, Panneman T, Vercauteren F, et al. (listed as Benjaminse)

1314 Proprioceptive Reweighting and Postural Control are Impaired Among Elite Athletes Following Anterior Cruciate Ligament Reconstruction.

Attalin B, Sagnard T, Laboute E, et al.

1324 Advanced Neuromuscular Training Differentially Changes Performance on Visuomotor Reaction Tests and Single-leg Hop Tests in Patients with ACL Reconstruction.

Chmielewski T, Obermeier M, Meierbachtol A, et al. (Listed as Tompkins)

1333 The Impact of Visual Perturbation Neuromuscular Training on Landing Mechanics and Neural Activity: A Pilot Study.

Wohl TR, Criss CR, Haggerty AL, Rush JL, Simon JE, Grooms DR.

1346 Task-Driven Neurophysiological qEEG Baseline Performance Capabilities in Healthy, Uninjured Division-I College Athletes.

Mangine RE, Palmer TG, Tersak JA, et al.

1362 Neurocognitive and Ecological Motor Learning Considerations for the 11+ ACL Injury Prevention Program: A Commentary.

Grooms DR, Bizzini M, Silvers-Granelli H, et al.

INVITED CLINICAL COMMENTARY

1373 Neurocognitive and Neuromuscular Rehabilitation Techniques after ACL Injury, Part 1: Optimizing Recovery in the Acute Post-Operative Phase- A Clinical Commentary.

Wilk KE, Ivey M, Thomas ZM, Lupowitz L.

ORIGINAL RESEARCH

1386 Agreement Between 2D Visual and 3D Motion Capture-Based Assessment of Foot Strike Pattern. Goto H, Kamikubo T, Yamamoto R, et al.

1397 Intra-rater and Inter-rater Reliability of the KangaTech (KT360) Fixed Frame Dynamometry System During Maximal Isometric Strength Measurements of the Knee Flexors.

Woolhead E, Partner R, Parsley M, et al. (Lead author is listed as Jones)

1407 Position- and Sex-Related Differences in Sagittal and Frontal Plane Concentric Isokinetic Hip Muscle Peak Torques and Agonist-Antagonist Ratios.

Hoglund LT, Schiffino MC, Freels JE, et al.

VOLUME 19, NUMBER 11 (Continued)

1417 Hip Stability Isometric Test (HipSIT): Concurrent Validity and Reference Values for CrossFit® Participants.

Santos TRT, Rodrigues ALR, Faria HMP, et. al. (listed as lead author Ocarino)

1426 Hip and Groin Problems in Female Team-Sport Athletes: A Cross-Sectional Study. Stadelmann JD, Reichman F, Franceschini-Brunner R.

1439 Dominant Arm Internal Rotation Strength is Related to Arm Pain in Youth Baseball Players. Paskewitz J, Breidenbach F, Malloy P, et al.

1447 Relationship Between Lumbar Locked Rotation, Trunk Rotation During Pitching, and Pitch Velocity in High School Baseball Players. Okamura S, Gakuin B.

1455 The Quality of the Functional Movements and the Back Squat in Amateur and Professional Bodybuilders.

Iljinait� V, Šiupšinskas L, Berškien� K.

1465 Epidemiology and Influencing Factors in Davis Cup Retirements Over the Past TwentyYears. Casals M, Cortés J, Llenderrozos D, et al.

CLINICAL COMMENTARY

1477 Physical Therapy Utilization Prior to Biceps Tenodesis or Tenotomy for Biceps Tendinopathy. McDevitt AW, Cleland JA, Hiefield P, et al.

MSK ULTRASOUND BITES: Tips and Tricks

The Utilization of Diagnostic Musculoskeletal Ultrasound in the Evaluation for Ischiofemoral Impingement: A Perspective for Rehabilitation Providers. Manske RC, Wolfe C, Page P, Voight M, Bardowski B.

I J S PT

IN COLLABORATION WITH

THE POWER OF INTERNATIONAL COOPERATION.

Mario Bizzini, PhD, PT (SSPA)

Ashley Campbell, PT, DPT, SCS, (IJSPT)

Barb Hoogenboom, PT, EdD, SCS, ATC (IJSPT)

Michael Voight, PT, DHSC, SCS, OCS, ATC, CSCS, FAPTA (IJSPT)

The International Journal of Sports Physical Therapy (IJSPT) is proud to present you with this special issue, in collaboration with the Swiss Sports Physical Therapy Association (SSPA), and in conjunction with the 2024 annual conference November 8, in Bern, Switzerland.

The topic Neurocognitive Enriched Rehabilitation has seen recent advances in neuroscience and motor learning. In the last decade, research groups in the US and in Europe have provided ground-breaking knowledge to better understand the role of the brain in preventing and recovering from ACL injuries. We're pleased and thankful that some of these researchers, such as Anne Benjaminse and Dustin Grooms, who are also among the speakers at the SSPA conference, have actively contributed to this special issue!

The SSPA and the IJSPT have been partners for more than 20 years. We firmly believe that open access is one of the keys to effective dissemination and promotion of clinically relevant evidence, as well as sharing trends and practices in sports physical therapy worldwide. We also believe that only with true open international cooperation we can together advance the rehabilitation and care of our athletes worldwide.

IJSPT readers will be able to relive the 2024 SSPA conference on the SSPA YouTube channel (sportfisioswiss - YouTube), a free educational resource for the sports PT community worldwide. We also remind our readers that they can find our popular Journal Club series on the IJSPT Youtube channel (https://www.youtube.com/@IJSPT/videos).

We hope you'll enjoy reading this IJSPT special issue, and "may the international power be with you!"

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The Power of International Cooperation

Mario Bizzini, PhD, PT, Ashley M Campbell, PT, DPT, SCS, Barb Hoogenboom, PT, EdD, SCS, ATC, Michael Voight, PT, DHSC, SCS, OCS, ATC, CSCS, FAPTA

https://doi.org/10.26603/001c.125160

International Journal of Sports Physical Therapy Vol. 19, Issue 11, 2024

The topic Neurocognitive Enriched Rehabilitation has seen recent advances in neuroscience and motor learning. In the last decade, research groups in the US and in Europe have provided ground-breaking knowledge to better understand the role of the brain in preventing and recovering from ACL injuries. We’re pleased and thankful that some of these researchers, such as Anne Benjaminse and Dustin Grooms, who are also among the speakers at the SSPA conference, have actively contributed to this special issue!

IJSPT readers will be able to relive the 2024 SSPA conference on the SSPA YouTube channel (sportfisioswissYouTube), a free educational resource for the sports PT community worldwide. We also remind our readers that they can find our popular Journal Club series on the IJSPT Youtube channel (https://www youtube.com/@IJSPT/ videos).

We hope you’ll enjoy reading this IJSPT special issue, and “ may the international power be with you!”

Mario Bizzini, PhD, PT (SSPA)

Ashley Campbell, PT, DPT, SCS (IJSPT)

Barb Hoogenboom, PT, EdD, SCS, ATC (IJSPT)

Michael Voight, PT, DHSC, SCS, OCS, ATC, CSCS, FAPTA (IJSPT)

This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CCBY-NC-4.0). View this license’s legal deed at https://creativecommons.org/licenses/by-nc/4.0 and legal code at https://creativecommons.org/licenses/by-nc/4.0/legalcode for more information.

Bizzini M, Campbell AM, Hoogenboom B, Voight M. The Power of International Cooperation. IJSPT. 2024;19(11):1289.

Busch A, Gianotti LRR, Mayer F, Baur H. Monitoring Cortical and Neuromuscular Activity: Six-month Insights into Knee Joint Position Sense Following ACL Reconstruction. IJSPT. 2024;19(11):1290-1303. doi:10.26603/001c.124840

Monitoring Cortical and Neuromuscular Activity: Six-month Insights into Knee Joint Position Sense Following ACL Reconstruction

Aglaja Busch1,2a , Lorena R. R. Gianotti3 , Frank Mayer2 , Heiner Baur1

1 School of Health Professions, Bern University of Applied Sciences, 2 Sports Medicine & Sports Orthopeadics, University of Potsdam, 3 Department of Social Neuroscience and Social Psychology, University of Bern

Keywords: Anterior cruciate ligament, electroencephalography, surface electromyography, brain, proprioception https://doi.org/10.26603/001c.124840

International Journal of Sports Physical Therapy

Vol. 19, Issue 11, 2024

Background

Changes in cortical activation patterns after rupture of the anterior cruciate ligament (ACL) have been described. However, evidence of these consequences in the early stages following the incident and through longitudinal monitoring is scarce. Further insights could prove valuable in informing evidence-based rehabilitation practices.

Purpose

To analyze the angular accuracy, neuromuscular, and cortical activity during a knee joint position sense (JPS) test over the initial six months following ACL reconstruction. Study design: Cohort Study

Methods

Twenty participants with ACL reconstruction performed a JPS test with both limbs. The measurement time points were approximately 1.5, 3-4 and 6 months after surgery, while 20 healthy controls were examined on a single occasion. The active JPS test was performed seated with a target angle of 50° for two blocks of continuous angular reproduction (three minutes per block). The reproduced angles were recorded simultaneously by an electrogoniometer. Neuromuscular activity of the quadriceps muscles during extension to the target angle was measured with surface electromyography Spectral power for theta, alpha-2, beta-1 and beta-2 frequency bands were determined from electroencephalographic recordings. Linear mixed models were performed with group (ACL or controls), the measurement time point, and respective limb as fixed effect and each grouping per subject combination as random effect with random intercept.

Results

Significantly higher beta-2 power over the frontal region of interest was observed at the first measurement time point in the non-involved limb of the ACL group in comparison to the control group (p = 0.03). Despite individual variation, no other statistically significant differences were identified for JPS error, neuromuscular, or other cortical activity

Aglaja Busch

E-mail: agbusch@uni-potsdam.de a

Outpatient Clinic, University of Potsdam Am Neuen Palais 10, Building 12 14469 Potsdam, Germany

Conclusion

Variation in cortical activity between the ACL and control group were present, which is consistent with published results in later stages of rehabilitation. Both indicate the importance of a neuromuscular and neurocognitive focus in the rehabilitation.

Level of Evidence 3

INTRODUCTION

An anterior cruciate ligament (ACL) rupture represents a significant and long-lasting sports injury. Surgical reconstruction is frequently selected as a means of restoring joint stability.1 Nonetheless, neither reconstruction nor rehabilitation can fully restore knee function.2 It has been stated that the ACL contains mechanoreceptors that are responsible for detecting position, movement, and force within the joint.3 These contribute to the proprioceptive information that is provided for the central nervous system (CNS) in order to maintain function.4,5 An evaluation of these proprioceptive senses is the joint position sense (JPS) test, which assesses the ability to reproduce actively or passively a previously presented angle by a body segment.6 Systematic reviews and meta-analyses have demonstrated tendencies of greater knee JPS errors after ACL rupture in the injured limb compared to the non-injured side as well as to healthy controls,7‑10 however, the clinical significance of these errors is still a matter of debate.11 In addition to changes in proprioception, sensory dysfunction can result in deficits in balance, coordination, and joint stability.12,13 Neuromuscular activity, which encompasses both voluntary and involuntary muscle activation for the purpose of performing functional tasks and maintaining or restoring joint stability, can be quantified through the use of surface electromyography (EMG).4 In patients with anterior cruciate ligament (ACL) injuries, there is evidence that neuromuscular activity is impaired.14 Thus, proprioceptive changes might translate to errors in the coordination of movement, potentially leading to an elevated secondary injury risk.11, 15

The loss of mechanoreceptors resulting from an ACL rupture is likely to impact the adaptability of the CNS in regulating joint function.15,16 Consequently, studies have examined brain activation following ACL rupture during a knee JPS test. In their functional magnetic resonance imaging (fMRI) study, Strong et al.17 reported no significant differences in JPS error or brain response in the ACL group, with an average follow-up of 23 months post-surgery, compared to a healthy control group. However, greater JPS errors were significantly associated with higher brain activity in some brain regions (ipsilateral anterior cingulate, supramarginal gyrus and insula) in both groups.17 Baumeister et al.18 examined brain activity via electroencephalography (EEG) during a JPS test in ACL patients with an average follow-up of 12.5 months after reconstruction. The authors observed a higher JPS error in the ACL injured limb in comparison to the healthy controls, accompanied by a significantly higher theta-power recorded by the electrodes over the frontal cortical region of interest and a significantly

higher alpha-2 power in the electrodes over the parietal cortical region of interest.18 Additionally, they identified significant differences in brain activity between the contralateral limb and healthy controls. Moreover, a review article discusses that bilateral alterations in other tasks may be attributable to the functional reorganization of motor networks, which is not confined to somatosensory and mechanical deficiencies subsequent to unilateral injury.15

The aforementioned studies have only investigated participants with an ACL rupture and reconstruction crosssectionally after completion of the standard rehabilitation programme. This leaves uncertainty regarding early adaptations and potential time points for specified interventions during the rehabilitation phase.16,19 Therefore, the purpose of this investigation was to analyze the angular accuracy, neuromuscular, and cortical activity during a knee joint position sense (JPS) test over the initial six months following ACL reconstruction.

The hypothesis was that no significant proprioceptive deficiencies measured by the angular error would be detectable between the groups, measurement time points, and limbs10 Although the performance outcome may remain unchanged, alterations in the underlying neuromuscular and cortical activity were assumed. It was hypothesized that there would be differences in the neuromuscular activity during the extension to the target angle.20 Furthermore, higher theta frequency was expected in the frontal region of interest and lower alpha-2 power in the parietal region of interest. Conversely, no differences in the beta frequency were anticipated in the ACL group compared to the healthy control group, regardless of the region of interest.18

METHODS

PARTICIPANTS

In this prospective observational study, 20 participants with reconstructed ACL were recruited in collaboration with their corresponding orthopaedic surgeon between March 2022 and September 2023. Additionally, 20 healthy controls participated voluntarily The participants were matched according to sex, age, height, weight and leg dominance. The subsequent analyses were conducted on a single leg of the healthy control group. This was identified as the leg corresponding to the involved limb of the ACL participant, representing the matched involved leg. General inclusion criteria were: age between 18 and 50 years, physically active (at least 2x 45 min per week21) currently or before the ACL rupture, and no former knee pathology. The ACL patient group was required to have a clinically

confirmed ACL rupture and have undergone reconstructive surgery with a quadriceps tendon graft within eight weeks of the incidence. No restriction regarding concomitant injuries was set. General exclusion criteria were: cardiac, neurological or peripheral vascular diseases, acute infection, alcohol abuse, current pain medication, other injuries of the lower extremity or trunk, back pain, thrombosis, pregnancy, dementia, or other musculoskeletal disorders limiting successful execution of the test protocol. An a priori sample size calculation was not feasible, due to missing data in a previous publication. Nonetheless, based on findings of previous studies examining EEG after ACL rupture, it was estimated that a sample size of 20 participants per group would be required.18,22 The study complied with the criteria of the declaration of Helsinki and was ethically approved by the local legal authority Kantonale Ethikkommision für die Forschung (KEK Bern, CH, No. 2020-02200). All participants gave their informed consent before participation. The study was pre-registered at the German Clinical Trials Register (DRKS-ID: 00023002).

PROCEDURE

The ACL group was invited to participate in a series of measurements at the Bern Movement Lab (Bern University of Applied Sciences, Bern, Switzerland) at three defined time points: 1.5 months, 3-4 months and 6 months following the reconstructive surgery The healthy control group was invited to participate in a single measurement session. Following clarification of the inclusion criteria, anthropometric data, leg dominance, the side of the ACL rupture and reconstruction and any concomitant injuries of the ACL group were recorded. Additionally, the Tegner activity score (TAS)23 (before the injury in the ACL group) and the current Knee Osteoarthritis Outcome Score (KOOS)24 were obtained at the first measurement. The ACL group reported if they received preoperative rehabilitation and provided details of their current main rehabilitation program content and the amount of rehabilitation they received at each measurement time point.

Next, the participants were prepared for the JPS test in the knee with recordings of the cortical activity using electroencephalography (EEG; see EEG recording and processing section), neuromuscular activity using electromyography (EMG; see EMG recording and processing section) as well as the angular error using an electrogoniometer (see electrogoniometer recording and processing). The procedure of the active-active JPS test as well as the recording and processing of the neuromuscular activity and angular deviation has been described in detail elsewhere.25 In short, following preparation, the participants’ actual general well-being and pain levels were assessed using a visual analogue scale with 100 mm in length.26 Then, the participants completed five minutes of level walking on a treadmill (Quasar® med, h/p/cosomos sports & medical GmbH, Nussdorf-Traunstein, Germany) at a speed of 3 km*h-1 as a standardized warm-up with additional recording of the neuromuscular activity during the final minute for later submaximal normalization of the EMG signals.27 Subsequently, the resting EEG activity during the period of seated

rest with the eyes open was recorded for three minutes and later used for the normalization of the EEG signals.28 Following this, the active-active JPS test was performed. Participants were seated with a hip angle of 100° flexion and a gap of approx. 5 cm between the posterior aspect of the knee and the chair surface, in an open kinetic chain (Figure 1).

During familiarization with the task, the participants actively flexed their knee into the starting position of 90° knee flexion (0° = full extension) and extended it to the target angle of 50° knee flexion (movement range of 40°) as indicated by the instruction of the examiner and visual feedback of the knee angle on a screen.25 While the vision of the participants towards their leg was obstructed by a hanging curtain throughout the five familiarization trials, they were allowed to use the feedback displayed on a screen. During the actual testing, the visual feedback was no longer available. The testing phase comprised two blocks of 3-minutelong active continuous angular reproduction per leg at a self-selected pace. Between the blocks, a 3-minute rest was taken and the starting leg was randomised for each measurement time point. The participants were instructed to reproduce the target angle as accurately as possible, hold it for three seconds and then return to the starting position (90° flexion).25 During the execution of the JPS test, the angular changes and neuromuscular and cortical electrical activity were recorded.

ELECTROGONIOMETER RECORDING AND PROCESSING

The electrogoniometer (Potentiometer RP20, Megatron Elektronik GmbH & Co.KG, Munich, Germany) was attached with the center of rotation placed at the knee joint

Figure 1. Study setup of the active knee joint position sense test.

space, in the midline between the lateral femoral and tibial epicondyle of the participant’s leg. The goniometer arms were affixed with Velcro strips in a superior/inferior orientation, aligned proximally with the greater trochanter and distally with the lateral malleolus. The electrogoniometer data were captured at a rate of 4000 Hz and then underwent analogue-to-digital conversion (NI PCI 6255 device from National Instruments®, Austin, USA; 1.25 MS/s, 16 bits). Subsequently, the signals were recorded ustilizing LabVIEW®-based software Imago Record (Pfitec®, Endingen, Germany). The electrogoniometer data were processed using Imago Process Master (Pfitec®, Endingen, Germany). The angle reproduced for each trial was determined as the midpoint of the 3-second holding phase, in accordance with the specified procedure. These angles were then exported to a Microsoft® Excel spreadsheet (Windows 10, Microsoft Corporation, Redmond, WA, USA). The angular error, defined as the difference between the targeted and reproduced angles, was calculated for each trial. Moreover, the constant angular error (CE) and absolute angular error (AE) were computed.29 The CE quantifies the directional bias of the error, with positive or negative arithmetical differences considered in the calculation. Negative arithmetic differences indicate an underestimation of the reproduced angle in comparison to the targeted angle, which is characterised by lesser knee extension. Conversely, positive values signify an overestimation, indicating greater knee extension. Additionally, the variable error (VE) was calculated in order to assess the consistency of the constant error.30

NEUROMUSCULAR RECORDING AND PROCESSING

For the surface EMG measurements, the electrodes were positioned meticulously on the vastus medialis (VM), vastus lateralis (VL), and rectus femoris (RF) of both limbs, adhering to the guidelines provided by SENIAM.31 Prior to electrode placement, the skin was prepared by shaving, sandpaper abrasion, and alcohol cleaning in order to optimize muscle signal detection. Bipolar electrodes (Type P-00-S, Blue Sensor®, Ambu, Ballerup, Denmark, interelectrode distance: 20 mm) were utilized to ensure that interelectrode impedance remained below 2 kΩ (Impedance meter: D175, Digitimer®, Hertfordshire, UK). The data acquisition methodology was consistent with that described previously The neuromuscular activity during the JPS test was analyzed in the extension movement phases based on angular recordings obtained from the electrogoniometer. The extension phase spanned from the commencement of the extension until reaching the anticipated target angle. EMG data underwent processing using the Imago Process Master (Pfitec®, Endingen, Germany). The raw signals were subjected to full-wave rectification and band-pass filtering within the range of 10–500 Hz (Butterworth, 2nd order). The root mean squares (RMS) of the amplitudes were computed for each muscle and movement phase and exported to a Microsoft® Excel spreadsheet (Windows 10, Microsoft Corporation, Redmond, WA, USA). The submaximal normalization of neuromuscular activity involved utilising the mean gait cycle activity of each muscle during level walking.27

ELECTROENCEPHALOGRAPHY RECORDING AND PROCESSING

Cortical electrical activity was recorded continuously throughout each block of JPS testing using a dry electroencephalography-system (DSI-24, Wearable Sensing, San Diego, CA, USA) and the corresponding software (DSISTREAMER–V.1.08.44), operating at a sampling rate of 300 Hz. The dry-EEG headset comprised 19 electrodes arranged in accordance with the international 10:20 system across the scalp and with two electrodes positioned at the ear lobules. The electrodes were mounted and secured following the instructions provided in the device manual to ensure optimal scalp contact.32 The impedances of each electrode were carefully monitored to maintain levels below 5kΩ. The recorded cortical activity signals were processed in MATLAB (Version R2020a, Mathworks Inc., Natick, MA, USA) utilising the EEGLAB toolbox (eeglab2022.1),33 following a standardized pipeline. Initially, the two blocks of JPS test per leg were combined. To mitigate line noise, the CleanLine software plugin34 was employed. Subsequently, the cortical activity signals were band-pass filtered within the range of 1 to 30 Hz. An “Artifact Subspace Reconstruction bad burst correction”35 was implemented to rectify any erroneous data periods. Following manual identification and rejection of undesirable episodes or channels, an adaptive mixture independent component analysis (AMICA)36 was conducted to discern and eliminate non-brain signals originating from muscle activity, eye movements, or electrocardiogram interference. The EEG data were then rereferenced to a common average, with the reference channel Pz reinstated in the dataset. Power spectra for the following frequency bands – theta (4-7.5 Hz), alpha-1 (8-10 Hz), alpha-2 (10.5-12.5 Hz), beta-1 (13-18 Hz), and beta-2 (18.5-25 Hz) – were computed using Fast-Fourier-Transformation and extracted for each trial and participant. Regions of interest (ROI) were formed for the frontal (F3, Fz, F4), central (C3, Cz, C4), and parietal (P3, Pz, P4) brain areas, as per current literature.18,28 The spectral power values per ROI were normalised to the resting cortical activity baseline for further statistical analysis.

STATISTICAL ANALYSIS

Statistical data analysis was carried out using R (R Core Team, Version 4.3.2, 2023).37 Participants’ characteristics were tested for significant group differences using a MannWhitney U test and a one-way repeated measures ANOVA to identify any significant differences in the general wellbeing and pain levels before and after each measurement time point performed. Post-hoc analysis was utilized for multiple comparisons. The electrogoniometer, neuromuscular, and cortical activity data were examined to ensure their plausibility Individual values exceeding two standard deviations from the overall mean were identified and traced back to the original dataset. A comprehensive examination of the data processing procedures pertaining to these outliers was conducted, and adjustments were made if deviations from standard procedures were identified. Otherwise, they were excluded from the dataset in accordance with the

relevant criteria.27 The results section presents descriptive statistics as mean, standard deviation (SD) and 95% confidence intervals (95% CI). Inferential statistics were conducted on the independent variable “Group”, which consisted of the three factors: group (ACL patients or healthy controls), measurement time point, and whether the task was executed with the involved or non-involved leg. A linear mixed model was fitted to each dependent variable (namely the absolute error of the electrogoniometric data, normalized neuromuscular activity during extension to the target angle and normalised cortical activity for the defined frequency bands per ROI frontal theta, parietal alpha-2 and beta-1 and beta-2 within the frontal, central, and parietal ROI) with Group as the fixed effect and using different random effect structures, that is random intercept and slope per Group-subject combination, random intercept per Group-subject combination and random intercept for both Group and subject. Model comparison using the Akaike information criterion (AIC) indicated that the optimal model was the one with “Group:subject” as a random intercept, thereby allowing each Group-subject combination to have a random intercept. From the fitted model, contrasts of interest were computed, that is, the effects relative to the reference category (matched-involved leg of the healthy control group), with standard errors and 95% CI’s including p-value adjustment for multiple comparisons using the Tukey’s Honest Significance Difference method. A residual analysis was performed to ascertain the validity of the model assumptions. The R lme4 package38 was used for model fitting and emmeans package39 was used for computing contrasts.

RESULTS

PARTICIPANTS

A total of 40 participants were enrolled in this study (20 participants after ACL rupture and reconstruction and 20 healthy matched controls). The initial measurement time point (M1) was 1.5 ± 0.2 months post-surgery, the second (M2) was 3.5 ± 0.3 months post-surgery and the third measurement time point (M3) was 6.1 ± 0.3 months postsurgery. There were no dropouts. Table 1 provides an overview of the participants’ characteristics. Half of the ACL participants had a rupture in their dominant leg. Only one participant reported no associated injuries. Four participants received preoperative rehabilitation, and all participants in the ACL group underwent standard rehabilitation procedures following surgery over the course of the six month measurement period. Details on associated injuries and the rehabilitation content and frequency can be found in the supplement. One ACL participant was unable to perform the JPS test at the first measurement time point due to discomfort in the targeted range of motion in the involved limb. Data of one non-involved limb of an ACL participant at the first measurement time point and the second block of the non-involved limb at the third measurement time point were excluded from the analysis due to technical issues. The pre- and post-measurement self-reported well-

being scores were comparable between the two groups (p = 0.39; Table 1). Significant differences were observed in pain levels between the measurement time points (p = 0.004). A post-hoc analysis revealed that the ACL group exhibited significantly elevated pain levels following the first measurement time point when compared to both pre- and postmeasurements in the control group (p = 0.017 and p = 0.006, respectively). The remaining mean pain levels were higher among the ACL group than the control group, though they did not reach a statistically significant difference (0.22 < p < 1).

ANGULAR ERROR

The mean number of repetitions performed by the participants was 48 repetitions (overall range of repetitions: 8-99; Con-matched-involved limb: 25-84; ACL-M1-involved limb range: 39-99; ACL-M1-non-involved limb range: 40-77; ACL-M2-involved limb range: 35-75; ACL-M2-non-involved limb range: 22-75; ACL-M3-involved limb range: 27-90; ACL-M3-non-involved limb range: 8-88). The highest mean absolute errors were observed in the control group with (9.1 ± 5.9°), while the lowest was noted in the non-involved leg of the ACL group at M3 (6.3 ± 4.2°). Conversely, the mean constant error was found to be lowest in the control group (4.9 ± 9.7°) and highest in the involved limb of the ACL group at M3 (7.5 ± 6.1°). The mean variable error did not exceed 1°. A comprehensive presentation of the descriptive statistics for the constant, variable and absolute error are presented in Table 2

The linear mixed model revealed no statistically significant difference in the absolute error in the fixed effects estimates (0.06 < p < 0.77, AIC = 33943.0; R2 = 0.56) (Table 3). The residual analysis provided no evidence against model assumptions.

NEUROMUSCULAR ACTIVITY

Descriptive statistics of the normalised neuromuscular activity during the extension to the target angle are displayed in Table 4 Residual analysis revealed no evidence to contradict the model assumptions. Vastus medialis presented no statistical difference in the fixed effect estimates (0.80 < p < 0.98; AIC = 52333.5; R2 = 0.84). No statistically significant difference in the fixed effect estimates was found for the vastus lateralis (0.64 < p < 1; AIC = 48910.8; R2 = 0.85). The rectus femoris demonstrated no statistically significant difference in the fixed effect estimates (0.31 < p < 0.99, AIC = 49927.3; R2 = 0.78) (Table 4).

CORTICAL ELECTRICAL ACTIVITY

Descriptive statistics of the normalized cortical activity over the entire JPS test per frontal, central and parietal region of interest, as well as frequency bands, are displayed in Table 5 Residual analysis demonstrated no evidence against model assumptions. No significant differences were observed in the fixed effects estimates for frontal theta (0.16 < p < 0.99; AIC = 3613.4; R2 = 0.34) and frontal beta-1 (0.06 < p < 0.47; AIC = 3550.5; R2 = 0.35) (Table 5). A signif-

Table 1. Participant characteristics displayed in mean ± standard deviation.

VAS well-being (mm)

VAS pain (mm)

anterior cruciate ligament group; n number; KOOS Knee injury and Osteoarthritis Outcome Score; max maximum; VAS visual analogue scale

Table 2. Constant, variable and absolute error of the JPS test per measurement time point and leg.

M mean; SD standard deviation; Con control group; ACL anterior cruciate ligament group; M1-M3 measurement time point 1-3

Table 3. Linear mixed model output for the absolute error with Group as fixed effect and Group:subject as random effect with random intercept.

Absolute Error Model output

= standard error; CI = confidence interval; Con = control group; ACL = anterior cruciate ligament group; M1-M3 = measurement time point 1-3

Table 4. Normalized neuromuscular activity during extension to the target angle. Descpritive statistic and linear mixed model output with Group as fixed effect and Group:subject as random effect with random intercept.

Vastus lateralis

Rectus femoris

icantly different fixed effect estimate was found for frontal beta-2 when comparing the ACL-M1-non-involved leg to the control group (p = 0.03). The remaining comparison of frontal beta-2 did not yield a statistically significant difference (0.32 < p < 0.75, AIC = 3468.2; R2 = 0.27) (Table 5).

No statistically significant differences were detected in the fixed effects estimates for central beta-1 (0.06 < p < 0.47; AIC = 3550.5; R2 = 0.35) and central beta-2 (0.81 < p < 1, AIC = 3595.9; R2 = 0.46) (Table 5).

Furthermore, no statistically significant differences were evident in the fixed effects estimates for parietal alpha-2 (0.15 < p < 0.99; AIC = 3623.3; R2 = 0.49), parietal beta-1 (0.50 < p < 0.95, AIC = 3391.1; R2 = 0.50) and parietal beta-2 (0.62 < p < 0.99, AIC = 3365.3; R2 = 0.54) (Table 5).

DISCUSSION

This is the first study to examine the angular accuracy, neuromuscular, and cortical activity during a JPS test longitudinally over the first six months following ACL reconstruction. No significant differences were observed between the measurement time points or limb in comparisons to the

healthy control group, with the exception of the beta-2 frequency band in the frontal region of interest for the noninvolved leg of the ACL group, which demonstrated a difference at the first measurement time point in comparison to the control group.

ANGULAR ERROR

The mean constant error was observed to be the smallest in the control group, although this was accompanied by a high standard deviation and no statistically significant differences when compared to the ACL group. It could be suggested that the mean precision presented by the constant error is marginally better in the control group when compared to the ACL group. Nevertheless, the mean absolute errors were found to be higher in the healthy control group than in the ACL group for each measurement time point and limb, with no significant difference observed. The non-significant difference confirms the authors’ hypotheses. Furthermore, a systematic review focusing on the active JPS test among ACL reconstructed participants in the early phase following surgery demonstrated nonhomoge-

Table 5. Normalized cortical activity during joint position sense test. Descpritive statistic and linear mixed model output with Group as fixed effect and Group:subject as random effect with random intercept.

Parietal Alpha-2

Frontal Beta-1

Frontal Beta-2

Central Beta-1

Central

Parietal Beta-1

Parietal Beta-2

neous results.10 Contrary, in the literature, JPS errors have most often been reported to be higher among the ACL patient groups compared to the contralateral side or a healthy control group,7‑9 however, no clear consensus exists.40

The psychometric properties of the present study setup were investigated within a healthy control group, and a minimal detectable change of 6.8° was identified.25 Therefore, presented differences found within the current study are likely to be the result of systematic error and demonstrate no clear influence of the measurement time point or limb in the ACL group. Moreover, it has been proposed that differences should exceed 5° to be considered clinically meaningful.8,9,11 The absolute errors presented exceed the minimal clinically important difference, yet no significant differences were observed between the ACL group and the healthy control group.

NEUROMUSCULAR ACITVITY

No significant differences were found between the healthy control group and the ACL group at each time point and for each limb. In the literature, only a few studies investigating the neuromuscular activity in the early postoperative period following ACL reconstruction exist. A general reduction in voluntary quadriceps activation has been reported in the literature,14,20,41 as well as alterations in the neural pathways responsible for this activation.42 Studies have discussed whether the quadriceps deficits can be attributed to arthrogenic muscle inhibition.14,43 In the present study, it can be hypothesized that the open-chain and non-weight-bearing JPS task may not have elicited differences in the neuromuscular activity due to the absence of sensory feedback and task functionality

CORTICAL ELECTRICAL ACTIVITY

A higher mean frontal theta power was observed in both limbs of the ACL group in the first two measurement time points, although this did not reach statistical significance when compared to a healthy control group. Baumeister et al.18 reported significantly higher theta power over the frontal cortical areas in both limbs of participants on average one year after ACL reconstruction compared to healthy controls.18 Elevated frontal theta power might represent a higher need for attention during the JPS test execution.44, 45

No significantly different alpha-2 power was detected in recordings from the electrodes over the parietal region at both limbs of the ACL group in comparison to the healthy control group. The mean alpha-2 power over the parietal region demonstrated a slight increase over the measurement time points in the ACL group. Higher alpha-2 power over parietal cortical brain regions indicates less task-specific demands.46 It can be hypothesized that the slight increase in alpha-2 power may be influenced by a learning effect with the repeated measures, reflecting a reduction in the need for cortical activation during the task.46 However, this hypothesis was not supported by the findings of the present study The study by Baumeister et al.18 presented a significantly lower alpha-2 power from the parietal electrodes during JPS testing with the involved limb of the ACL group in comparison to healthy controls.18 Reduced activity within the alpha-2 frequency band in sensorimotor areas has been found to be associated with an increase in movement-related information and sensory processes.47

The literature suggests that frontal theta and parietal alpha-2 activities play an important role in the executive functions of working memory 46,48 The findings of the present study did not reveal any alterations in these executive functions within the ACL group while maintaining performance in the JPS test. It is worth considering, whether the study protocol, which included an open-chain JPS test, creates a sufficiently challenging environment for typically physically active, young participants. Moreover, the primary focus of attention during the execution of a JPS test is internally. It is possible that the ACL group has undergone a process of training whereby they have focused predominantly on their knees and limbs over the past six months of rehabilitation. which could result in a different basis in comparison to a healthy control group. It would be of interest to examine whether similar results would be found if the JPS test was conducted with external visual cues or under dual-task conditions. Herewith, it may be beneficial to investigate attention control in addition to working memory.49 Furthermore, recent clinical commentaries have recommended adapting ACL rehabilitation to allow for motor re-learning and support neuroplasticity, during which an external focus during the execution of movements is emphasized.50,51

Beta oscillations are thought to be involved in top-down processing and sensorimotor integration and are linking different brain regions, including the pre-motor and somatosensory cortex, the supplementary motor areas and the cerebellum.44,52 The literature indicates that fluctuations in beta oscillations can be divided into movementbased reductions, with a decrease in beta power slightly prior to and during movement, and post-movement beta rebound, which is characterized by an elevation of beta power following movement.52 It should be noted that the referenced study did not distinguish between beta-1 and beta-2. Apart from frontal beta-2 in one comparison, no other significant results were found in the present study 51 A detailed analysis regarding the movement phase would provide valuable insights into the differences in movement planning, execution and the integration of sensory information. Moreover, examining cortical activity in repetitions with higher angular error could prove beneficial. One fMRI study reported a significantly positive correlation between angular error and brain activity 17 Further investigation could clarify how proprioceptive error detection and integration contribute to the execution of precise movements and the association with cortical activities. This could be used to evaluate the high re-injury rates among patients with ACL reconstruction.

It is possible that the statistically significant differences, which were not observed during the initial six month period following ACL reconstruction, may become apparent at a later stage.14 This is supported by a systematic review, reporting neurocognitive changes and alterations to the central nervous system that persist after athletes return to sport.53 It is further recommended that a neurocognitive test battery be implemented in the return to sport testing process to enhance the detection of neurocognitive reliance in patients returning to sport following ACL reconstruc-

tion.54 Nevertheless, it remains ambiguous whether differences in cortical activities and functional connectivity precede ACL injury as a cause or emerge as a consequence thereof.55,56

METHODOLOGICAL CONSIDERATIONS AND LIMITATIONS

The characteristics of the participants were not significantly different between the groups, with the exception of the (preinjury) Tegner score and the current KOOS total score. Both groups exhibited a mean Tegner score of greater than 4, indicating that they were a physically active cohort in total. Nevertheless, the preinjury Tegner score of the ACL group was slightly higher than that of the healthy control group. The influence of physical activity on proprioceptive capacity is a topic that has been discussed in the literature.57,58 It is possible that a less active ACL patient group would yield more distinct results.17 Moreover, the presence of joint effusion and potential pain, particularly at the first measurement time point for the ACL group, may have exerted additional influence on the outcomes. This is, however, unavoidable in measurements taken during the early phase following injury and reconstruction. Nonetheless, it is possible that the observed effects within the ACL group may have been influenced by the rehabilitation process, which was not controlled. A sub-analysis of patients with a higher frequency of rehabilitative appointments in comparison to a lower frequency might provide further insights into the potential effect on the neuromuscular or cortical activity Nevertheless, the number of patients included in the present study was insufficient for the performance of meaningful sub-analyses. The influence of limb dominance on JPS quality has been the subject of previous research.25, 57,58 A recent fMRI study has proposed the existence of a right hemisphere lateralization of proprioceptive processing test in healthy persons during a JPS.59 Although the present study included only one participant per group defined as left-footed and ACL patients with equally paired ACL injuries in their non-dominant limb, future research should evaluate the potential influence of limb dominance. The self-selected pace during testing resulted in different repetitions per execution of the JPS test. The use of a metronome would have ensured greater standardisation of the procedure, although it is possible that this would have resulted in alterations to individual movement preferences. Nonetheless, the range of repetitions was comparable between the two groups and measurement time points, particularly in order to minimize the impact of potential pain or discomfort during the first measurement time points in the involved limb of the ACL group. Moreover, the rather long duration of angular reproduction may have resulted in a decline in motivation or focus. Yet, the variable error was minimal and the numerous repetitions ensured an accurate assessment of angular reproduction performance.60 As previously stated, the clinical relevance of the JPS test is a topic of ongoing debate.6,11 The limitation of the test to a single joint does not accurately reflect the planning and execution of movement in functional tasks, which often involve multiple joints and movement directions.60 Accordingly, a test simulating weight-bearing movement or ob-

stacle clearance test has been proposed.61,62 However, the feasibility of these tests within a study population in the early stages after surgery, with the measurement of brain activity using EEG, remains unknown and would be subject to further investigation. Moreover, the JPS test enables the explicit measurement of the participant’s ability to perceive the position of the knee joint. A comprehensive understanding of the changes observed during the execution of this test may provide valuable insights into the various affected parts of the sensorimotor system. This could offer a differentiated view of the observed alterations during functional tasks and assist in determining the original causes of the changes.

It should be noted that this study is not without limitations. The rehabilitation process of the ACL group was not subject to control, but was documented. While the primary rehabilitation content was largely consistent across the participants, there were also notable differences in terms of frequencies. Furthermore, the degree of independent training varied considerably between participants, depending on their motivation. This may have had an impact on the results and a more structured and balanced rehabilitation scheme may facilitate more effective clinical implications. Nevertheless, the recruited patients represent patients in their regular therapy setting, which lends to a high external validity to the study and corresponds well with procedures in everyday practice. The target angle consisted of solely 50° knee flexion. Despite this angle representing the range of typical daily activities and having been used in previous studies,63,64 a variation of movement directions and angles would provide more comprehensive insight.25

CONCLUSION

No statistically significant differences in acuity, neuromuscular, or cortical activity were observed during the first six months after ACL reconstruction, except for the beta-2 frequency band in the frontal region of interest for the noninvolved leg in comparison to the control group at the first measurement time point. Differences might become evident in later phases following ACL reconstruction and neurocognitive testing should be incorporated into the return to sport evaluation process. In an active study population, the JPS test may not align with the requirements of functionality or difficulty, particularly in terms of eliciting observable changes in neuromuscular activity. An extension with visual cues or under dual-task conditions may yield a distinct evaluation.

CONFLICT OF INTEREST

The authors report no conflicts of interest.

ACKNOWLEDGEMENTS

We express our gratitude to all participants for their time and dedication to this study

We would like to thank Philipp Henle for his support in informing and recruiting the ACL volunteers.

Submitted: July 18, 2024 CDT, Accepted: September 23, 2024 CDT

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14. Tayfur B, Charuphongsa C, Morrissey D, Miller SC. Neuromuscular Function of the Knee Joint Following Knee Injuries: Does It Ever Get Back to Normal? A Systematic Review with Meta-Analyses. Sports Medicine. 2021;51(2):321-338. doi:10.1007/ s40279-020-01386-6

15. Needle AR, Lepley AS, Grooms DR. Central nervous system adaptation after ligamentous injury: a summary of theories, evidence, and clinical interpretation. Sports Med 2017;47(7):1271-1288. doi:10.1007/s40279-016-0666-y

16. Neto T, Sayer T, Theisen D, Mierau A. Functional brain plasticity associated with ACL injury: A scoping review of current evidence. Neural Plast. 2019;2019:2019. doi:10.1155/2019/3480512

17 Strong A, Grip H, Boraxbekk CJ, Selling J, Häger CK. Brain response to a knee proprioception task among persons with anterior cruciate ligament reconstruction and controls. Front Hum Neurosci 2022:16. doi:10.3389/fnhum.2022.841874

18. Baumeister J, Reinecke K, Weiss M. Changed cortical activity after anterior cruciate ligament reconstruction in a joint position paradigm: An EEG study. Scand J Med Sci Sports. 2008;18(4):473-484. doi:10.1111/j.1600-0838.2007.00702.x

19. Criss CR, Melton MS, Ulloa SA, Simon JE, Clark BC, France CR, et al. Rupture, reconstruction, and rehabilitation: A multi-disciplinary review of mechanisms for central nervous system adaptations following anterior cruciate ligament injury. Knee. 2021;30:78-89. doi:10.1016/j.knee.2021.03.009

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54. Grooms DR, Chaput M, Simon JE, Criss CR, Myer GD, Diekfuss JA. Combining neurocognitive and functional tests to improve return-to-sport decisions following ACL reconstruction. J Orthop Sports Phys Ther. 2023;53(8):415-419. doi:10.2519/ jospt.2023.11489

55. Diekfuss JA, Grooms DR, Yuan W, Dudley J, Barber KD, Thomas S, et al. Does brain functional connectivity contribute to musculoskeletal injury? A preliminary prosperctive analysis of a neural biomarker of ACL injury risk. J Sci Med Sport 2019;22(2):169-174. doi:10.1016/j.jsams.2018.07.004

56. Diekfuss JA, Grooms DR, Nissen KS, Schneider DK, Foss KDB, Thomas S, et al. Alterations in knee sensorimotor brain functional connectivity contributes to ACL injury in male high-school football players: a prospective neuroimaging analysis. Braz J Phys Ther 2020;24(5):415-423. doi:10.1016/ j.bjpt.2019.07.004

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59. Strong A, Grip H, Arumugam A, Boraxbekk CJ, Selling J, Häger CK. Right hemisphere brain lateralization for knee proprioception among rightlimb dominant individuals. Front Hum Neurosci. 2023:17 doi:10.3389/fnhum.2023.969101

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Rikken KTH, Panneman T, Vercauteren F, Gokeler A, Benjaminse A. Increased Visual Attentional Demands Alter Lower Extremity Sidestep Cutting Kinematics in Male Basketball Players. IJSPT. 2024;19(11):1304-1313. doi:10.26603/001c.124804

Increased Visual Attentional Demands Alter Lower Extremity Sidestep

Koen

Cutting Kinematics in Male Basketball Players

T.H. Rikken1 , Tom Panneman1 , Fabian Vercauteren1 , Alli Gokeler2 , Anne Benjaminse3 a

1 a. Department of Human Movement Sciences, University Medical Center Groningen, University of Groningen, 2 Exercise and Neuroscience unit, Department Exercise & Health, Faculty of Science, Paderborn University, 3 Department of Human Movement Sciences, University Medical Center Groningen, University of Groningen

Keywords: Anterior cruciate ligament, basketball, cognitive load, sidestep cutting, visual attention https://doi.org/10.26603/001c.124804

International Journal of Sports Physical Therapy

Vol. 19, Issue 11, 2024

Background

In basketball, changing direction is one of the primary mechanisms of anterior cruciate ligament (ACL) injury, often occurring within complex game situations with high cognitive demands. It is unknown how visual attention affects sidestep cutting kinematics during the entire energy absorption phase of the cut in an ecologically valid environment.

Purpose

The purpose of this research was to study the effect of added cognitive load, in the form of increased visual attentional demands, on sidestep cutting kinematics during the energy absorption phase of the cut in an ecologically valid environment.

Study Design

Crossover Study

Methods

Fifteen male basketball players (aged 22.1 ± 2.3) performed ten sidestep cutting movements without (BASE) and with (VIS) a visual attention dual task. 3D kinematics of the hip, knee and ankle were recorded utilizing Xsens IMU motion capture. Temporal kinematics were analyzed using Statistical Parametric Mapping. Discrete time point kinematics were additionally analyzed at initial contact (IC) and at peak knee flexion utilizing paired t-tests. Effect sizes were calculated.

Results

Hip flexion was significantly reduced in the VIS condition compared to the BASE condition (p<0.01), including at IC (VIS 35.0° ± 7.2°, BASE 40.7° ± 4.9°, p=0.02, d=0.92) and peak (VIS 37.8° ± 9.7°, BASE 45.5° ± 6.9°, p=0.001, d=0.90). Knee flexion was significantly reduced in the VIS condition, in comparison to the BASE condition (p<0.01), at peak (VIS 59.9° ± 7.5°, BASE 64.1° ± 7.4°, p=0.001, d=0.55).

Conclusion

The addition of visual attention during sidestep cutting altered lower limb kinematics, which may increase ACL injury risk. It is suggested that ACL injury risk screening and

Corresponding author:

Dr A. Benjaminse

W: http://www.rug.nl/staff/a.benjaminse/cv +31(0)50-3616015 a

Department of Human Movement Sciences, University Medical Center Groningen, University of Groningen. Antonius Deusinglaan 1 (Room 3215-325), 9713 AV Groningen, The Netherlands

E: a.benjaminse@umcg.nl

prevention should include sidestep cutting with visual attentional demands, in order to mimic the cognitive demands of the sports environment.

Level of Evidence

INTRODUCTION

Injuries of the anterior cruciate ligament (ACL) have increased in incidence over the last decennia, with an increase of 14% in basketball specifically 1,2 Sustaining an ACL injury is associated with numerous adverse health effects3‑7 and impaired athletic performance.8‑10 These facts indicate the need for better primary prevention of ACL injuries and justify the current study.

Of all ACL injuries in basketball 58-67% are non-contact in nature,11,12 of which sidestep cutting is one of the primary injury mechanisms.13 One of the primary playing situations in basketball in which ACL injuries happen is the first step after picking up the ball when attacking.14 During the energy absorption phase (i.e. initial contact (IC) to peak knee flexion) of sidestep cutting several factors may contribute to high knee joint loading, such as low knee flexion angles,15 high initial knee abduction angle,13,16 low hip flexion angle,17 high hip abduction angle,15 and low initial hip internal rotation.18 These unfavorable kinematics are especially prevalent during unplanned sidestep cutting maneuvers.19,20

The aforementioned sidestep cuts are made during games in a dynamically changing environment in which athletes are exposed to numerous stimuli.14,21 Visual attention, defined as the goal-directed allocation of cognitive resources to external stimuli,22 aids the uptake of relevant information in this dynamically changing environment.23 While visual attention is a lower order cognitive function, it facilitates higher order cognitive functions such as working memory, inhibitory control and cognitive flexibility 24 Increased cognitive task demands, which challenge the aforementioned cognitive functions, are consistently linked to an increase in at-risk biomechanics for lower extremity injury 25

A deficit or delay in attentional processing can contribute to a decreased ability to coordinate movement, which could result in the aforementioned unfavorable knee joint loading.26 This has been demonstrated in studies where primarily female basketball players performed sidestep cuts with a passing or dribbling task which divided their attention, which elicited reduced knee flexion,27 increased knee abduction angles,27 increased knee abduction moments,28,29 and increased hip abduction angles compared to when they did not perform the task.29

These findings show the influence of cognitive function, in the form of decision making and divided visual attention, on lower limb biomechanics and the need to include these factors in ACL injury screening and prevention practices.30, 31 The effect of decision-making and visual attention has been studied more directly in various sports, eliciting unfavorable biomechanics.32‑34 However, the effects of increased visual attentional demands during the entire en-

Table 1. Subject characteristics (mean ± standard deviation).

(kg)

Leg dominance left/right 14/1

Hours of basketball played per week 6.4 ± 2.9

Playing level

National (N=5)

Regional (N=2)

Local (N=8)

ergy absorption phase of the sidestep cut in male basketball players remain unknown. Previous research has been limited to studying biomechanics at initial contact and peak values in a lab setting, as opposed to in the natural sporting environment.35 Furthermore, previous research has shown that discrete time point analysis failed to identify statistically significant biomechanical differences which were uncovered with full waveform analysis.36 Gaining insight into the kinematics of the entire energy absorption phase of the sidestep cut could thus provide valuable information on how the movement execution is affected by including a temporal element in the analysis, as opposed to an analysis limited to two discrete timepoints.

This study will investigate kinematic changes during a sport-specific task and will be conducted on an indoor basketball court, increasing its ecological validity.35 The purpose of this research was to study the effect of added cognitive load, in the form of increased visual attentional demands, on sidestep cutting kinematics during the energy absorption phase of the cut in an ecologically valid environment in male basketball players. The hypothesis was that increased visual attentional demands alter sidestep cutting kinematics unfavorably in the context of ACL injury risk.

METHODS

SUBJECTS

Fifteen male subjects were recruited from different basketball clubs from the north of the Netherlands (Table 1). Inclusion criteria were male, player in an official basketball team, 18-30 years, >3 hours of team training and game time per week. Exclusion criteria were recent lower-limb injury (<6 months), ACL injury in history, alcohol or caffeine 24h before measurements and color blindness. All subjects had normal or corrected-to-normal vision. Leg dominance was defined as the leg with which a participant pushes off during a lay-up.38,39

PROCEDURES

The Central Ethical Review Board of the University of Groningen approved this study under ID number #11257 All subjects provided informed consent prior to participating. First, anthropometric measures were taken in order to scale the Xsens Motion Tracking System (XSens Techonolgies, Enschede, Netherlands) proprietary biomechanical model and calibrate the motion capture in Xsens MVN Analyze (v.2021.2.0).40 Joint angles were defined using the Euler sequence ZXY. Xsens MVN has fair to excellent agreement on sagittal plane movements in relation to gold-standard optoelectronic motion capture and allows for sport specific on-field movements to be captured.40,41 Subjects were required to wear their own basketball shoes.

SIDESTEP CUTTING KINEMATICS

The kinematics of each basketball player were recorded on an indoor basketball court. Before starting the actual trials, subjects were granted familiarization trials until they indicated that they were ready to start. The sidestep cutting kinematics were recorded during a 90° near full speed sidestep cut. The subjects were asked to perform the route at near full speed (80-90% of maximum effort) since this mimics the demands of a basketball game more realistically and because kinematics of near full speed cutting elicit biomechanical risk factors for ACL injury more clearly than cutting at 60% speed.42 Furthermore, 90° sidestep cutting results in the highest knee internal rotation and knee abduction moments and angles compared to 45° or 180° cuts; indicating this might be the cutting angle with the greatest inherent risk.43

Each trial started with a participant initiated 8.35m forward sprint followed by a sidestep cut with the non-dominant leg in the direction of the dominant leg. This was followed by a 3.5m forward sprint resulting in a 90° sidestep cut with the dominant leg, which was recorded for analysis. Each trial ended with a 3.5m forward sprint immediately after this last sidestep cut to finish the route. (Figure 1)

First, each subject performed ten trials of baseline sidestep cutting, without cognitive load (BASE). The Fitlights (FITLIGHT Corp, Canada, 2022, v2.17) placed upon the boxes on this predefined route would light up before and during the whole duration of the trial.

Second, each subject performed around fifteen trials of sidestep cutting in the cognitively loaded condition (VIS). The difference with the BASE and the VIS condition is that the subject did not know the route before the trial. The subject had to pay attention to, and then respond to, the Fitlights which dictated the direction. In the VIS condition the subject was tasked to perform distractor trials and actual capturing trials, intertwined with each other The ratio between actual capturing and distractor trials was 2:1 respectively In the distractor trials any of the directions was possible. In the actual capturing routes of the VIS condition the directions were exactly the same as the BASE condition, with the only difference being the added cognitive load through the increased visual attentional demands. Ultimately ten valid trials were performed in which the subject

Figure 1. Left, in red: schematic route of sidestep cut for participants with left sided leg dominance. Right: experimental set-up on the basketball court with FitLights.

thus had to visually scan the environment on approach to (at Fitlight #2) and during (at Fitlight #3) the sidestep cut which was recorded.

DATA PROCESSING AND STATISTICAL ANALYSIS

An initial a priori sample size estimate was performed using Gpower 3.1,44 with a paired t-test where α was set at 0.05, β at 0.20. With an effect size of 0.7 this analysis indicated that 15 subjects were sufficient to achieve adequate power. While sample size calculation using this method is valid for traditional 0D outcome data, the estimated sample size is in line with recommendations for 1D power analysis in biomechanical variables using a paired t-test with medium to large effect sizes.45,46 The region of interest in this study is 0% to 50% of the sidestep cut, since the ACL is most at risk during this energy absorption phase.15,17 The energy absorption phase in this study is defined as from the instance of IC to peak knee flexion angle, in line with previous research.18,47,48 While the analysis focuses on the energy absorption phase, the kinematics of the entire sidestep cut are shown for clarity.

Trials were cropped from initial contact (IC) to toe off (TO). IC was defined as the instant where the vertical acceleration of the foot Inertial Measurement Unit (IMU) reached its minimum value.49 TO was defined as the instant where peak knee extension was achieved.50 All trials were time normalized at IC on a scale of 1-100% of the stance phase to allow for statistical analysis.

A customized Python script (Python 3.9, Python Software Foundation, Delaware, USA) was used in order to perform Statistical Parametric Mapping (SPM) (Spm1D 0.435, http://www.spm1d.org). A two tailed paired t-test was performed to compare hip, knee and ankle kinematics between the BASE and VIS conditions.

The kinematic outcome measures were flexion/extension angles of the hip and knee, dorsi- and plantarflexion of the ankle, abduction/adduction angles of hip and knee, and internal/external rotation angles of the hip, during the entire stance phase of the sidestep cut.

Alpha was set at 0.05 for all analyses. Effect sizes for statistically significant differences between conditions at IC

and at peak values were indicated with Cohen’s d, small (d=0.2), medium (d=0,5), large (d=0,8).51 As the timing of peak values can differ inter-individually this may not be visible in the SPM figures, which average every participant on a set window of 0-100%. The differences between conditions at peak values (i.e. discrete time point) are thus additionally analyzed and reported separately, to allow comparison with other research.

RESULTS

KINEMATICS BASE VS VIS

Hip flexion was significantly reduced over the entire sidestep cut during the VIS condition in comparison to the BASE condition (p<0.01). At IC the hip flexion angle in the VIS condition (35.0° ± 7.2°) was significantly reduced compared to the BASE condition (40.7° ± 4.9°) (t(14)=3.717, p=0.02, d=0.92). The peak hip flexion angle in the VIS condition (37.8° ± 9.7°) was also significantly reduced compared to the BASE condition (45.5° ± 6.9°) (t(14)=4.344, p=0.001, d=0.90). Hip external rotation was significantly increased during the entire sidestep cut during the VIS condition in comparison to the BASE condition (p<0.01). Peak hip external rotation was significantly increased in the VIS condition (13.2° ± 8.8°) compared to the BASE condition (8.2° ± 9.3°) (t(14)=2.798, p=0.014, d=0.56). Results for the hip joint can be found in Figure 2 and Table 2

In the VIS condition, knee flexion was significantly reduced from 10.7% of the sidestep cut and onwards compared to the BASE condition (p<0.01). Peak knee flexion was reduced in the VIS condition (59.9° ± 7.5°) compared to the BASE condition (64.1° ± 7.4°) (t(14)=4.028, p=0.001, d=0.55). Knee abduction was significantly reduced from 17.9% of the cut and onwards in the VIS condition, in comparison to the BASE condition (p<0.01). Results for the knee joint can be found in Figure 2 and Table 2

At the ankle no significant differences were observed between the BASE and VIS conditions. Results for the ankle joint can be seen in Figure 2 and Table 2

Time spent during the sidestep cut between IC and TO in the VIS condition (251.12ms ± 58.23ms) did not differ significantly from the BASE condition (259.20ms ± 40.95ms) (t(149)=1.596, p=0.113).

DISCUSSION

The addition of visual attentional demands to sidestep cutting resulted in reduced hip flexion and increased hip external rotation angles, and reduced knee flexion and knee abduction angles in the energy absorption phase of the cut. The difference in sidestep cutting kinematics between conditions primarily occurred in the sagittal plane for the hip and knee joint.

The current findings are in line with previous research, which indicates that divided visual attention can lead to reduced hip and knee flexion angles.27 At baseline, participants in the current study performed the sidestep cut with 40.7° of hip flexion at IC whereas the participants in the

Figure 2. Means (solid line) and standard deviations (cloud) joint kinematics during the stance phase (IC=0%, TO=100%) of the sidestep cut (1,2,3,4,5,6). Significance graph of Statistical Parametric Mapping where grey indicates a statistically significant difference between conditions (1a, 2a, 3a, 4a, 5a, 6a).

study of Almonroeder et al.27 performed the sidestep cut with 53.3° of hip flexion at IC. The magnitude of change differs however In the study of Almonroeder et al.27 hip flexion at IC only decreased by 2.5° under the influence of divided visual attention, compared to 5.7° in the current study This indicates that the participants in the current study started with lower hip flexion angle, from which they reduced the hip flexion angle even further in the VIS condition. This finding, in combination with a reduced knee flexion angle in the VIS condition in the current study, could increase ACL injury risk since it could limit the ability to actively absorb energy during the sidestep cut through range of motion and ultimately transfer more load to the ACL.16,18,52‑54 A possible explanation for the differences between the studies is that in the current study subjects were required to perform the visual attention task during the sidestep cut, whereas in the study of Almonroeder et al.27 the subjects had to perform the divided visual attention task directly after the sidestep cut. This could allow the participant to still focus on executing the sidestep cut,27 something which was not the case in the current study Additionally it should be noted that the study by Almonroeder et al.,27 was performed with female basketball players, whereas the current study was performed with male basketball players.

Almonroeder et al.27 reported no effect of visual attention on knee abduction angle at IC (6.4° at baseline vs 7.0° with divided visual attention). Other researchers have shown an increase in knee abduction angle from 7.4° to 8.5°

Table 2. Joint angles during the sidestep cut

and an increase in hip internal rotation angle from 4.6° to 6.4°, but this was measured during sidestep cuts of 45°.28 Comparing kinematics of 45° cuts with 90° cuts, as per the current study, is futile since baseline kinematics differ based on the angle of the cut.43,55 In addition to the effect of the cutting angle, it has also been shown that the type of visual stimulus matters in altering kinematics during sidestep cutting.56,57 The differences in findings between the studies, in all three planes, highlight the specificity of task constraints.

Since the subjects were asked to perform the route at near full speed (80-90% of maximum effort), the altered kinematics during the VIS condition, can be linked to the performance-injury risk trade-off hypothesis during sidestep cutting.58 This hypothesis states that an increase in performance often results in suboptimal kinematics when related to ACL injury risk.58 It is possible that in the current study these dual-task costs came into effect. In order to maintain performance (i.e. perform the route at 80%-90% of their speed) with the increased dual-task constraints in the VIS condition, the sidestep cutting kinematics changed as a function of the increased visual attentional demands.

Altered higher-risk kinematics are undesirable when related to ACL injury risk, but it has been shown that specifically training sidestep cutting for six weeks can improve both sidestep cutting performance and kinematics in male football players.53 In semi-elite basketball players it has also been shown that including cognitive-motor dual-task training using LED-displays during dribbling tasks can improve dribbling performance in five weeks of training, to a greater extent than motor training without the cognitive dual task.59 Furthermore, the cognitive-motor dual-task training also improved cognitive performance by allowing a faster connection between sensory encoding and response execution.59 These findings indicate that an improvement in cognitive or sidestep cutting performance when trained properly does not have to occur at the expense of sport performance. These promising results may be important for the secondary prevention of ACL injuries, since due to neu-

roplasticity an ACL reconstructed athlete may shift towards visual-motor control of movement instead of sensory-motor control of movement.60 This is shown during sidestep cutting when ACL reconstructed basketball players exhibited different hip and knee coordination when a simulated visual attention dual task was added, compared to healthy matched basketball players who did not show altered coordination.61 These combined findings highlight the importance of including integrated sidestep cutting execution and visual attention in training, in order to improve primary and secondary prevention of ACL injuries.

A strength of the current study is the investigation of the combined effects of unplanned change of direction and a visual attention task on sidestep cutting kinematics in basketball players in a gym environment. Prior research indicates that sidestep cutting kinematics in a laboratory setting differ from actual on field kinematics.62 Since the current study took place on an indoor basketball court the athlete-environment relationship was preserved resulting in increased ecological validity 35

Another strength of the current study was the statistical analysis. The area most of interest in ACL injury risk research is the energy absorption phase during the sidestep cut, which roughly corresponds with the first 50% of the cut.15,17,18,47,48 Focusing only on kinematic values at IC and peak generally discards a plethora of information in between these timepoints.36,63 Since this study utilized Statistical Parametric Mapping we were able to statistically analyze the entire stance phase of the sidestep cut instead of being limited to fixed time points only. Analyzing the entire absorption phase allows for a more thorough interpretation of the kinematics, since temporal differences are included.37

A limitation of the current study is that some caution is warranted when interpreting the kinematic results. IMU based 3D motion capture systems allow for sport specific on field measurement, but are less accurate than gold standard infrared optoelectronic 3D measurement systems.38, 39,64 IMU based systems are quite accurate at capturing

movement in the sagittal plane, however, the accuracy of IMU based systems is acceptable in movements in the frontal plane, and questionable in the transverse plane.38, 64 During change of direction, IMU based knee abduction/ adduction angles could be up to 11° off and hip rotation angles could be more than 8° off compared to optoelectronic measurement systems.38,39 During the current study these movements had ranges of motion of 5.0 degrees and 7.5 degrees respectively. Since the ranges of motion of these movements are relatively small and measurement errors can be relatively large, caution is warranted when interpreting the outcomes of the current study with regards to these movements. IMU-based motion capture was chosen to accommodate the on-court movements needed for an ecologically valid task, but may have only maintained accuracy in the study of sagittal plane movements.

Another limitation of the current study lies within the practical design of the measurements. In the VIS condition subjects did not know the route which they had to follow, the FitLights dictated this such that they had to scan their environment. Some routes would be eligible for capturing the sidestep cutting kinematics and other distractor routes would not be eligible. To guarantee that the subject would not know the route beforehand, these distractor routes were added. The ratio between actual recording routes and distractor routes was 2:1 respectively We limited the current study to a ratio of 2:1 so that fatigue would not be a factor within the design. However, there was still a possibility that subjects would be able to guess the route beforehand, although the authors saw no signs of this.

Additionally, while the current study did analyze the duration of the sidestep cut in the BASE and VIS conditions, timing gates were not utilized to analyze the approach speed of the participants.

Caution is warranted with generalizing the results of the current study to other populations as the participants were all male and did not differ greatly in skill level. Finally, it could be that the sample size was too limited (small) to uncover more nuanced effects on sidestep cutting execution. The sample size in the current study was similar to comparable research27 and was calculated on the basis of the power analysis with medium to large effects, as found in the hip and knee. While adequate for medium to large effects, the current sample size could be too small to uncover more nuanced kinematic changes.46 Finally, caution is warranted with generalizing the results of the current study to other populations as the participants were all male and did not differ greatly in skill level.

Consistent with the findings of this study, as a practical implication, it can be advised that sidestep cutting execution with cognitive load should be incorporated in injury prevention practices. There are several ways to incorporate visual attention in sport specific prevention training. For

example, cognitive load can be added by performing unanticipated cutting on the sports field by tasking the athlete with mirroring or chasing a leading teammate. A teammate can also approach the athlete and when together, the teammate decides to cut to the left or right, and the athlete must cut the opposite direction. Third, the teammate approaches the athlete dribbling with a ball and when together, the teammate decides to cut to the left or right with the ball, and the athlete cuts and tries to intercept the ball. And lastly, the teammate passes a ball (direction and speed selfchosen) and the athlete has to change direction to chase for the ball. In these examples, temporal variability (timing of stimuli), spatial variability (location of stimuli) and complexity of stimuli can be decreased or increased, thus less or more mirroring the demands of the actual sports environment.65,66

Future research could study the effect of specifically training sidestep cutting with increased visual attentional demands on performance and kinematics, in order to generate methods to improve ACL injury prevention. Furthermore, future research could study the effect of variability (e.g. timing, location, type, complexity) of the visual stimuli on sidestep cutting performance and kinematics. In line with this, future research could investigate whether questionnaires more suited to monitoring the attentional demand could provide more information. Finally, future research could study the possible mediating impact of skill level, alongside the possible effects of age and gender, on the effect of increased visual attentional demands and study the effect of dribbling during sidestep cutting as this is a common ACL injury mechanism in basketball.14

CONCLUSION

The results of the current study demonstrate that the addition of a visual attention dual-task alters sidestep cutting kinematics in male basketball players. Increased visual attentional demands primarily result in less hip and knee flexion during the absorption phase and the increased cognitive demand could lead to an increased ACL injury risk. Professionals in sports and healthcare are encouraged to consider implementing visual attention in their injury prevention paradigms in order to improve ecological validity and facilitate transfer to the actual sports environment.

CONFLICTS OF INTEREST

The authors declare that they have no conflicts of interest.

Submitted: July 31, 2024 CDT, Accepted: October 08, 2024 CDT

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Attalin B, Sagnard T, Laboute E, Forestier N, Rémy-Néris O,

B. Proprioceptive Reweighting and Postural Control are Impaired Among Elite Athletes Following Anterior Cruciate Ligament Reconstruction. IJSPT. 2024;19(11):1314-1323.

doi:10.26603/001c.124802

Proprioceptive Reweighting and Postural Control are Impaired Among Elite Athletes Following Anterior Cruciate Ligament

Reconstruction

Benoit Attalin1a , Telma Sagnard2 , Eric Laboute1,3 , Nicolas Forestier2 , Olivier Rémy-Néris4 , Brice Picot2,5

1 C.E.R.S, Ramsay-santé, Capbreton, France, 2 Interuniversity Laboratory of Human Movement Biology, Savoie Mont-Blanc University, Chambéry, France, 3 Société Française de Traumatologie du Sport (SFTS), France, 4 Université Brest, CHU Brest, INSERM, UMR 1101, F29200 Brest, France, 5 French Society of Sports Physical Therapist (SFMKS Lab), Pierrefitte-sur-Seine, France

Keywords: ACL rehabilitation, central nervous system, postural control, proprioception, proprioceptive flexibility, vibration, ACL injury-induced neuroplasticity.

https://doi.org/10.26603/001c.124802

International Journal of Sports Physical Therapy

Vol. 19, Issue 11, 2024

Background

After anterior cruciate ligament reconstruction (ACLR), the risk of recurrence can reach 20%, partially due to poor postural control and impaired sensory processing. Lack of flexibility in proprioceptive postural strategy has recently been shown to be a potential risk factor for ACL injury.

Hypothesis/Purpose

This study aimed to compare proprioceptive reweighting and postural control between ACLR and controls elite athletes. It has been hypothesized that athletes with ACLR exhibit impaired proprioceptive reweighting and poor postural control.

Study design

Cross-sectional study

Methods

Fifty-two ACLR and 23 control elite athletes (50 males and 25 females, mean age 24.7 years) were included. Proprioceptive reweighting was determined using the evolution of proprioceptive weighting (eRPW), calculated from the center of pressure (CoP) displacements generated by tendon vibration during bilateral standing tasks on firm and foam surfaces. An eRPW <95% classified individuals as flexible (i.e., able to reweight proprioceptive signals from the ankle to the lumbar region), whereas an eRPW >105% classified individuals as rigid (i.e., maintaining an ankle dominant strategy). CoP velocity (vCoP) and CoP ellipse area (EA) were used to characterize postural control. Independent sample t-test and a Chi-squared test were used to compare eRPW, vCoP, EA, and the proportion of flexible and rigid athletes between groups.

Results

The eRPW was higher in the ACLR group (100.9±58.8 vs. 68.6±26.6%; p=0.031; Rank biserial correlation=0.314; medium), with a greater proportion of rigid athletes than in the control group (38.5 vs. 4.4%; p=0.010), reflecting lower proprioceptive reweighting. The ACLR group had greater EA on foam surface (8.0±4.6 vs. 6.3±4.4cm²; p=0.019), revealing poorer postural control.

Corresponding author:

Benoît Attalin

Centre Européen de Rééducation du Sportif (CERS)

Groupe Ramsay Santé, Capbreton France

Email: benoit.attalin@gmail.com

Picot

Conclusion

Elite athletes with ACLR showed impaired proprioceptive reweighting and poor postural control on an unstable surface. This reflects an inability to adapt proprioceptive weighting when balance conditions are changing and suboptimal postural strategies.

Level of Evidence

INTRODUCTION

Anterior cruciate ligament (ACL) injuries are common in sports and the most common treatment for athletes is surgery and rehabilitation.1,2 In this specific population, the rate of reinjury can reach up to 20% and only 65% of athletes returned to their preinjury level.3,4 One possible explanation for these poor outcomes is the persistence of some defiencies that are not targeted during the rehabilitation such as proprioception, proprioceptive adjustment, or neuromotor deficits.

It has been shown that postural control impairments related to a central origin persist in the short and long term after ACL reconstruction (ACLR) and are considered as potential risk factors for reinjury 5‑9 Recent evidence has identified neuroplastic adaptation of the central nervous system (CNS) following ACL injuries in particular in afferent pathways.10‑12 Ligament injuries significantly disrupt proprioceptive signals and induce nociceptor hyperactivity due to associated inflammatory processes. These factors alter sensory information and its processing by the CNS, leading to cortical reorganization in injured athletes.13‑15

A recent studies has revealed that six weeks post-surgical reconstruction, patients show increased cortical connectivity during an unipedal balance tasks without vision compared to healthy subjects.5 This heightened functional connectivity in somatosensory and visual areas may indicate a compensatory mechanism to control postural stability of the injured leg. Long-term (up to 20 years post-injury) injured individuals exhibit reduced adaptability in postural control and greater effort to maintain balance compared to healthy individuals.16 This decreases motor control flexibility in unexpected situations.17,18 These postural control deficits are primarily attributed to alterations in sensory reweighting.

A fundamental contributor to optimal postural control is sensory reweighting.19 It reflects the ability of the CNS to identify and select the most appropriate signal according to balance conditions. For instance, in eyes-closed postural conditions, the CNS mainly relies on proprioception to maintain optimal postural control while in eyes-open balance situations, a reweighting towards vision is observed. The systematic review by Wikstrom et al. confirms an overreliance on visual information during postural tasks in ACL injured athletes.20 This increased dependence on visual signals is considered as a central mechanism of sensory reorganization, compensating for degraded proprioceptive signals due to ligamentous damage to maintain effective postural control and joint stability 21,22

In addition to this intermodal reweighting (proprioception vs vision), an intramodal modality has also been iden-

tified (i.e. proprioceptive reweighting). Proprioceptive reweighting is defined as the ability of the CNS to integrate sensory signals from different anatomical locations and select the most appropriate cue according to balance conditions. For example, when standing on a firm surface individuals mainly rely on ankle signals. Conversely, on a foam surface a shift toward a lumbar proprioceptive strategy is observed.19,23,24 However, it appears that in certain pathological conditions such as chronic low back pain or diabetic neuropathy, this ability to reweight proprioceptive signals when postural conditions are changing is impaired.25‑28 In addition, recent investigations revealed that a large heterogeneity exists among healthy athletes regarding this proprioceptive strategies.29,30 Most athletes are indeed able to switch from ankle to lumbar proprioceptive signals when moving from a firm to a foam surface (i.e. flexible athletes). However, some individuals seem to adopt an ankle-steered strategy, even on unstable surface (i.e. rigid athletes). It could be considered as a suboptimal strategy since it has been shown that rigid athletes exhibited at-risk determinants for ACL injuries during side-cutting maneuvers.29

Therefore, the primary aim of this study was to compare proprioceptive reweighting between ACLR and control elite athletes. The authors hypothesized that following ACLR, athletes would exhibit a lower ability to switch from ankle to lumbar signals than healthy athletes. The secondary aim of this study was to compare postural control between control and ACLR elite athletes. It was hypothesized that ACLR athletes would exhibit poor balance control.

MATERIALS AND METHODS

POPULATION

This cross-sectional study was conducted in the European Sports Rehabilitation Center of Capbreton, France, from June to September 2023. Based on the primary aim of this study, a priori calculation of the number of subjects required to obtain a statistical power of 0.90 and type 1 error of 0.05 with an effect size of 0.8, showed that at least 68 subjects were needed.29

The inclusion criteria for the ACLR group were as follows. Patients were high-level athletes (top national and international division) who had undergone ACL reconstruction (for first or reinjury) and had to be able to stand on two legs with their eyes closed without pain or instability For these reasons, the minimum postoperative inclusion period was set at 30 days. Individuals in the control group were high-level athletes free from any recent (six months) lower limb injuries but involved in a rehabilitation process primarily for shoulder, elbow, or wrist injury/surgery The ex-

clusion criteria for both groups were known neurological or vestibular impairments and spine or lower limb injuries in the prior six months, and pain during the procedure or significant destabilization leading the examiner to prevent the athlete from falling. This study was performed in accordance with the principles of the Declaration of Helsinki. All subjects provided written informed consent, and this study received Institutional Ethics Approval (IRBA02114-49).

PROTOCOL

The procedure was the same as previously detailed by Picot et al.29,30 Participants stood barefoot in a bipedal stance with their arms relaxed by their sides and their head in neutral. Feet position was standardized and vision was prevented using opaque goggles. Two conditions were evaluated: “firm” (standing on the force plates) and “foam” (Physiopad®; 50x41x5cm; 52 kg/m3) surfaces. Four muscle vibrators (VB115, Techno Concept, France) were placed bilaterally on the triceps surae (TS) and the lumbar paravertebral muscles (LPM) by the same experienced experimenter.25 Vibration frequency was set at 80 Hz with an amplitude of 0.5 mm to stimulate the muscle spindles. Computer software automatically and randomly triggered the site of vibration. This also ensured that neither the participant nor the experimenter could anticipate the next vibration site. Each trial lasted for 60s. Recordings began at 20s prior to vibration, then vibration was applied for 20s and the recording continued for another 20s during the restabilization period. Force and moment data were collected using portable, uniaxial, dual force plates (Force Decks, FDLite, V.2, VALD, Brisbane, Australia, 200 Hz) to determine center of pressure (CoP) displacement. Raw data were extracted by Force Decks software. Signals were filtered using a Butterwoth low-pass, fourth order filter with a cut-off frequency of 10 Hz. Anterior/Posterior CoP displacement (dCoP) was calculated using custom software developed in Matlab (The MathWorks, Inc., Version: 9.13.0 (R2022b).

PROPRIOCEPTIVE STRATEGY

Relative Proprioceptive Weighting (RPW) is the ratio between the effects of vibration of the TS and the LPM (absolute TS / (absolute TS + absolute LPM)) on CoP displacement. It provides a reliable indication of individual proprioceptive strategies: an RPW of 1 indicates 100% reliance on ankle afferent input while an RPW of 0 indicates a 100% reliance on lumbar afferent input.

RPW has been shown to be the most reliable indicator of the response to muscle vibration and to establish proprioceptive strategy.25,27,31 The evolution of the relative proprioceptive weighting (eRPW) between the firm and foam surfaces (expressed as a percentage of the RPW on the firm support) was then calculated.29,30

Participants were then dichotomized according to their proprioceptive profile using the eRPW by a second blind assessor. A change < 95% corresponded to a reallocation of signals from ankle to lumbar when standing on foam surface and indicated a flexible proprioceptive profile. Conversely, a change ≥ 105% indicated a rigid profile with an

inability to reweight proprioceptive reliance reflecting ankle-dominated strategy.26,29,30 Participants with an eRPW value between 95% and 105% were not characterized to avoid incorrect characterization due to variability in the index.25,29

POSTURAL CONTROL

Postural stability was determined by analyzing the CoP ellipse and CoP velocity area during the 20s of the pre-vibration period on the two different surfaces (firm and foam).32 The data were averaged for trials performed on the same surface and under the same conditions. Higher values indicated poorer postural stability 33

STATISTICAL ANALYSIS

Normality and equality of variances were assessed using the Shapiro-Wilk and Levene’s tests. For the primary aim of the study, eRPW was compared between the groups using a nonparametric independent t-test. The proportions of flexible and rigid subjects in each group were tested using the chi-square (Chi²) test. RPW values were compared using a two-way (Group x Surface) repeated measure ANOVA and post-hoc analysis (Scheffé’s correction) were performed if needed. As postural control data (vCoP and EA) were not normally distributed, they were compared using independent (between-group) and paired (between-surface) nonparametric t-tests. The level of significance was set at 0.05. Effect sizes (Rank biserial correlation, Cramer V or partial η2) were calculated for all comparisons and compared using the Hopkins scale. The statistical analysis was performed using JASP (Amsterdam 0.12.2.0) and G*Power (Version 3.1, University of Dusseldorf, Germany).

RESULTS

POPULATION

Fifty-two ACLR (17 females and 35 males, 23.2±4.9 years) and 23 control elite athletes (8 females and 15 males, 28.2±5.3 years) were included (Table 1). Among ACLR athletes, five underwent reinjury surgery (9.6%). The mean post-operative delay was 162.1 days (SD: 65.1) (Table 1).

PROPRIOCEPTIVE STRATEGY

The ACLR group exhibited a higher eRPW value than the control group (100.9 ± 58.8% vs. 68.6 ± 26.6%; p=0.031; Rank biserial correlation=0.314; medium) (Figure 1). In addition, the ACLR group had a significantly lower proportion of flexible athletes and a higher proportion of rigid athletes than the control group (p=0.01, Cramer’s V=0.351, large) (Table 2).

There was a significant interaction (Group x Surface) for RPW values (p=0.05; partial η2=0.014; small). Post-hoc analysis revealed differences only in the control group where RPW values were significantly lower on the foam compared to the firm surface (0.51 ± 0.26% vs. 0.71 ± 0.20%; p=0.002, Cohen’s d=0.845; big) (Figure 2).

Table 1. Mean (±SD) baseline characteristics.

Figure 1. Individual change in eRPW from the firm to the foam condition: RPW increased for the rigid strategy (≥105%) and decreased for the flexible strategy (≤95%).

RPW: Relative Proprioceptive Weighting; ACLR: Anterior Cruciate Ligament Reconstruction; *: p<0.05

Table 2. Distribution of athletes (%) according to their proprioceptive postural strategy and groups.

Group

Control (N=23) ACLR (N=52)

Flexible (N, % of group) 19 (82.6%) 27 (51.9%)

Rigid (N, % of group) 1 (4.4%) 20 (38.5%)

Not characterized (N, % of group) 3 (13.0%) 5 (9.6%)

p=0.01

POSTURAL CONTROL

On the foam surface, the ACLR group showed increased mean CoP ellipse area compared to the control group (7.95 ± 4.57 cm² vs. 6.25 ± 4.40 cm²; p=0.019; Rank biserial correlation=0.343; medium) indicating poorer postural control. No other differences were observed between the two groups (Table 3). CoP velocity was significantly higher on the foam than on the firm surface for both ACLR (p<0.001) and con-

Figure 2. Mean ± SD and individual RPW values for the firm and foam support surfaces of the ACLR and control groups.

RPW: Relative Proprioceptive Weighting; ACLR: Anterior Cruciate Ligament Reconstruction; *: p=0.001

trol groups (p<0.001), as well as the CoP ellipse area for both ACLR (p<0.001) and control groups (p<0.001) confirming the higher difficulty to maintain postural control on foam surface (Table 3).

DISCUSSION

The primary aim of this study was to compare proprioceptive reweighting between elite athletes following ACL reconstruction and a control group. Results revealed higher eRPW values in the ACLR group indicating an inability to reweight proprioceptive signals according to balance conditions.29,30 More specifically, it appears that only the control group was able to significantly shift from an ankle strategy on the firm surface to a lumbar strategy when standing on foam surface (i.e. decrease RPW value, Figure 2). On the contrary, the ACLR group maintained an ankle-dominated strategy regardless of the surface stability The mean eRPW of ACLR elite athletes was 100.9%, reflecting a strategy close to a rigid profile for the entire group. On the contrary, mean eRPW value of the control group (69%) was similar to values from a previous study obtained from a group of flexible athletes (72%).29 The higher eRPW values found in ACLR athletes can be explained by lower RPW on firm surfaces, which do not decrease on foam surface (Figure 2). It

Table 3. Mean ± SD postural parameters in the control and ACLR groups

P-values refer to the independent t-test between the

reveals an inability to shift from ankle reliance when the reliability of the signals from this joint is altered by the instability of the support.23‑25,34 Conversely, more than 80% of controls were able to operate a proprioceptive reweighting to lumbar signal on foam surface. This reveals a suboptimal proprioceptive postural strategy in ACLR group.30, 35 When examining RPW values on firm and foam surfaces, both groups exhibit higher values than those previously reported among healthy populations.26,27,31,36,37 This might be explained by the characteristics of our population, since high level athletes tend to increase reliance on ankle proprioceptive information.33,38

When comparing the proprioceptive strategies between the two groups, a significantly higher proportion of rigid athletes was observed in the ACLR group (38.5% vs. 4.4%). Additionally, the control group exhibited a remarkably high proportion of flexible athletes (83%). Only one study among young healthy athletes reported the proportion of flexible/rigid individuals with 43% of rigid and 57% of flexible 30

Contrary to Picot et al. who used an eRPW cut-off value of 100% to distinguish between rigid and flexible individuals, in the present study, the dichotomization was made using an eRPW > 105% for rigid and eRPW < 95% for flexible athletes in order to avoid incorrect characterization of participants due to the variability of this index.25,29,30 In addition, the population studied by Picot et al. was composed of young subelite healthy handball players.30 Both type of sport and level of practice may play a role in proprioceptive reweighting strategy.24,33,38,39 It might be possible that most healthy elite athletes exhibit flexible strategy compared to non-expert individuals. Further studies with larger sample sizes are needed to better understand the specific proportion of flexible/rigid and the role of sports expertise in proprioceptive postural strategies according to the type of population.

The secondary aim of this study was to compare postural performance between ACLR athletes and a control group. Data confirm previous results revealing bilateral deficits in both static and dynamic postural control, in single-leg and double-leg stances following ACLR. Single-leg assessments showed impairment for both the affected and unaffected limb. These bi and unilateral deficits are found in the short and long term.7,40‑43 It is worth mentioning that only significant differences between the two groups were observed on foam surfaces. The moderate effect size as well as the absence of difference on firm surface between the

two groups could be explained by the fact that individuals were elite athletes and bipedal tasks might not be challenging enough.44 It seems assessment of postural control deficits in challenging tasks, such as unstable surfaces, single-leg tasks may improve the characterization of postural control deficits.44,45

Overall, the results indicate possible functional modifications of the CNS in elite athletes following ACLR, especially in areas involved in postural control. Over-reliance on visual signals after ACL injury have been identified as a probable consequence of altered proprioceptive signal.20 Indeed, an hyperactivation of lingual gyrus has been shown after ACLR which could be considered as an adaptation mechanism of the CNS to maintain postural control by reweighting altered proprioceptive signals to visual signals.46‑48 Although the CNS attempts to compensate for this proprioceptive impairment, central alterations persist, which may explain the ongoing postural control deficit after an ACL injury Indeed, Grooms et al. found greater activation of the contralateral cerebellum and the pre-motor area, and the ipsilateral secondary somatosensory cortex in individuals who underwent an ACLR, all of which are highly implicated in postural control.47 The recent scoping review from Vitharana et al. confirmed impaired central processing within the somatosensory and visual systems and underlined the impact of these neuroplastic changes on balance control.22 These results suggest that cortical and subcortical deficiencies after ACLR may be involved in the persistence of a postural control deficit after ACLR.6,46,47 Further imaging studies are needed to better understand which brain regions are involved in the proprioceptive reweighting process and whether functional connectivity between brain regions responsible for posture and sensory integration is impaired among rigid individuals.

It has been shown that several regions of the CNS involved in proprioceptive reweighting such as the somatosensory, pre-motor and motor cortex exhibit altered activity after an ACL rupture.46,47,49 This could explain the lack of proprioceptive reweighting found in ACLR subjects in this study. In addition, impaired functional connections between the left primary sensory cortex and the right posterior lobe of the cerebellum were observed in athletes who go on to suffer an ACL injury. These connections are considered essential for motor control, thus functional impairments of the CNS especially between brain regions implicated in sensory integration during postural control might

increase the risk of ACL injury 50,51 It has been suggested that these central adaptations could be responsible for reinjury after ACLR, since it limits the ability of athletes to adapt to complex and unplanned game situations.52

Recently, Picot et al. showed that lack of proprioceptive reweighting in postural strategy is associated with at-risk biomechanics and neuromuscular control for ACL injuries during sidecutting maneuvers.29,53,54 Poorer postural control was also observed among rigid athletes during bipedal stance tasks which is also a major risk factor for primary and secondary ACL injuries.8,9,30,40

These results suggest that following ACLR elite athletes exhibiting suboptimal (i.e. rigid) proprioceptive strategies could be more likely to suffer from a reinjury Further studies are needed to determine whether a lack of proprioceptive reweighting is a risk factor of ACL (re)injury

STRENGTHS AND LIMITATIONS

This is the first study to evaluate proprioceptive reweighting abilities in athletes undergoing ACLR. It is also the first to use vibration as a method to probe the CNS in this population without imaging or electroencephalography, which is more functional and closely approximates postural control. This could be considered as a CNS assessment tool that can be easily used in clinical practice to personalize rehabilitation and be part of return-to-sport criterion.

This study had several limitations. First, due to the design of this study, it is not possible to determine whether the lack of proprioceptive reweighting observed in ACLR athletes was present before the injury. Future studies should examine preinjury data to confirm the link between proprioceptive reweighting and ACL rupture.

Furthermore, the exact effects of rehabilitation on proprioceptive reweighting remains to be established. The mean post-operative delay for the ACLR group was five months. It remains unclear whether proprioceptive reweighting impairments persist in the long term. Thus, further research is needed to determine the progression or potential recovery of these proprioceptive deficits over time. Future longitudinal studies should evaluate the evolution of proprioceptive reweighting during rehabilitation, and whether exercising can transform rigid to flexible patients. Since athletes who suffer an ACL lesion are 30 to 40 times more prone to recurrences than those who did not, lack of proprioceptive reweighting and impaired postural control should be evaluated and targeted during the rehabilitation.3,55

On another note, as bipedal testing on a unilateral injury may have limitations and could fail to reveal important asymmetries in weight-bearing strategies for each individ-

ual limb, it would be valuable to conduct a bilateral singleleg assessment to identify potential differences in proprioceptive reweighting capabilities between the injured and healthy limbs.55

Additionally, the authors did not conduct a subgroup analysis based on the type of graft (hamstring or quadriceps), associated injuries (antero-lateral ligament suture or lateral tenodesis, meniscal resection or suture), or first or reinjury surgery because of the low number of athletes. Future studies should include larger cohorts to evaluate the effect of these differences on proprioceptive reweighting.56

Moreover, the small sample size likely contributed to the high variability observed. This variability is especially in the ACL group and is possibly due to variable postoperative times. Such variability in proprioceptive reweighting is common with this methodology

The average age of the ACLR group was lower than that of the control group (23.2 vs 28.2 years). Even if it has been shown that age could influence proprioceptive reweighting capabilities in elderly, a difference of five years seems insufficient to induce variations in proprioceptive reweighting capabilities.24,39 Furthermore, given that the proprioceptive system is fully matured at this age it seems unlikely that this could have influenced the results.57

CONCLUSION

Elite athletes who underwent ACL reconstruction exhibit a lack of proprioceptive reweighting, and a higher proportion of rigid individuals compared to a control group. More specifically, they show a lack of ability to reweight proprioceptive signals when moving from a firm to a foam surface. In addition, poorer postural control was observed on foam surface among ACLR athletes. These results highlighted central alterations associated with suboptimal strategy that could increase the risk of reinjury. Further studies are needed to assess whether these alterations exist prior to injury and if these can be considered potential risk factors for reinjury

CONFLICTS OF INTEREST

The authors report no conflicts of interest.

Submitted: September 01, 2024 CDT, Accepted: October 12, 2024 CDT

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50. Diekfuss JA, Grooms DR, Yuan W, et al. Does brain functional connectivity contribute to musculoskeletal injury? A preliminary prospective analysis of a neural biomarker of ACL injury risk. J Sci Med Sport 2019;22(2):169-174. doi:10.1016/ j.jsams.2018.07.004

51. Manto M, Bower JM, Conforto AB, et al. Consensus paper: roles of the cerebellum in motor control--the diversity of ideas on cerebellar involvement in movement. Cerebellum 2012;11(2):457-487 doi:10.1007/s12311-011-0331-9

52. Grooms DR, Onate JA. Neuroscience application to noncontact anterior cruciate ligament injury prevention. Sports Health 2016;8(2):149-152. doi:10.1177/1941738115619164

53. Donelon TA, Dos’Santos T, Pitchers G, Brown M, Jones PA. Biomechanical determinants of knee joint loads associated with increased anterior cruciate ligament loading during cutting: A systematic review and technical framework. Sports Med - Open 2020;6(1):53. doi:10.1186/s40798-020-00276-5

54. Zebis MK, Aagaard P, Andersen LL, et al. Firsttime anterior cruciate ligament injury in adolescent female elite athletes: a prospective cohort study to identify modifiable risk factors. Knee Surg Sports Traumatol Arthrosc 2022;30(4):1341-1351. doi:10.1007/s00167-021-06595-8

55. Spiliopoulou SI, Amiridis IG, Hatzitaki V, Patikas D, Kellis E. Tendon vibration during submaximal isometric strength and postural tasks. Eur J Appl Physiol 2012;112(11):3807-3817 doi:10.1007/ s00421-012-2319-7

56. Laboute E, James-Belin E, Puig PL, Trouve P, Verhaeghe E. Graft failure is more frequent after hamstring than patellar tendon autograft. Knee Surg Sports Traumatol Arthrosc. 2018;26(12):3537-3546. doi:10.1007/s00167-018-4982-7

57 Sá CDSCD, Boffino CC, Ramos RT, Tanaka C. Development of postural control and maturation of sensory systems in children of different ages a crosssectional study. Braz J Phys Ther. 2018;22(1):70-76. doi:10.1016/j.bjpt.2017.10.006

Chmielewski T, Obermeier M, Meierbachtol A, et al. Advanced Neuromuscular Training Differentially Changes Performance on Visuomotor Reaction Tests and Single-leg Hop Tests in Patients with ACL Reconstruction tional Test Results in Patients with ACL Reconstruction. IJSPT. 2024;19(11):1324-1332. doi:10.26603/001c.124807

Advanced Neuromuscular Training Differentially Changes

Performance on Visuomotor Reaction Tests and Single-leg Hop Tests in Patients with ACL Reconstruction tional Test Results in Patients with ACL Reconstruction

Terese Chmielewski1 , Michael Obermeier2 , Adam Meierbachtol1 , Asher Jenkins3 , Michael Stuart4 , Robby Sikka5 , Marc Tompkins6a

1 Tria Orthopedic Center, 2 Orthopedic Surgery, University of Minnesota, 3 University of Minnesota, 4 Orthopedics and Sports Medicine, Mayo Clinic, 5 COVID Sports and Society Workgroup/SMART, Mayo Clinic, 6 TRIA Orthopaedic Center

Keywords: ACL, Rehabilitation, Sports, functional test, Reaction time https://doi.org/10.26603/001c.124807

International Journal of Sports Physical Therapy

Vol. 19, Issue 11, 2024

Background

Advanced neuromuscular training prepares patients with anterior cruciate ligament reconstruction (ACLR) for sport participation. Return-to-sport testing often includes single-leg hop tests, yet combining motor and cognitive tasks (i.e., dual-task) might reveal neurocognitive reliance.

Purpose/Hypothesis

Study Design

Quasi experimental, Pretest-Posttest

Methods

Twenty-five patients with ACLR (11 males) completed 10 sessions of advanced neuromuscular training and pre-and post-training testing. Reaction tests outcomes were from a platform and visual display. The double-leg reaction test involved touching target dots with either leg for 20 seconds; correct touches and errors were recorded. The single-leg reaction test involved hopping on the test leg to 10 target dots; hop time and errors were recorded. Single-leg hop tests included forward, triple, crossover triple, and timed hop; limb symmetry index was recorded. Effect sizes were calculated for corrected touches on the double-leg reaction test, surgical side hop time on the single-leg reaction test, and surgical side hop distance or time on single-leg hop tests.

Corresponding Author: Marc A. Tompkins, MD

marc.tompkins@tria.com a

Department of Orthopedic Surgery

University of Minnesota

2450 Riverside Avenue South Suite R200

Minneapolis, MN 55455

Ph: 612-273-1177

Fax: 612-273-7959

Results

Correct touches on the double-leg reaction test significantly increased from pre- to post-training (20.4 +/- 4.3 vs. 23.9 +/- 2.8, p<0.001). Hop time on the single-leg reaction test significantly decreased from pre- to post-training (Surgical leg 13.2 vs. 12.3 seconds, non-surgical leg 13.0 vs. 12.1 seconds, p=0.003). Mean errors did not significantly change on either reaction test (p> 0.05). Cohens d effect sizes in descending order was single-leg hop tests (d=0.9 to 1.3), double-leg reaction test (d=0.9), and single-leg reaction test (d=0.5).

Conclusion

Motor performance improved after advanced neuromuscular training, but the effect size was less on visuomotor reaction tests than single-leg hop tests. The results suggest persistence of neurocognitive reliance after ACLR and a need for more dual-task challenges in training.

Level

of Evidence 3

INTRODUCTION

Anterior cruciate ligament (ACL) injuries are prevalent in the United States, with 1 in 3000 persons sustaining an ACL rupture, and the incidence appears to be increasing.1 The current standard of care for athletes and active individuals with an ACL injury is arthroscopic ACL reconstruction (ACLR), and roughly 100,000 ACLR surgeries are performed annually 2 Patients with ACLR participate in months of rehabilitation to address impairments in knee range of motion, lower extremity strength, and lower extremity neuromuscular control before attempting to return to activity and/or sport participation.3 Despite extensive rehabilitation after ACLR, the risk for a secondary ACL injury is high.4‑6

A patient’s readiness to return to sport participation after ACLR is often determined from clinical tests, including single-leg hop tests.7 Research suggests that patients might demonstrate good performance on motor tasks like singleleg hop tests but require greater attention and neural effort to perform the motor task.8 This neural compensation, called neurocognitive reliance,9 could put patients at risk for secondary injury during sport participation because visual, auditory, and tactile information in the sporting environment must also be processed. Neurocognitive reliance can be exposed by pairing a motor task with a cognitive task (i.e., dual task training), such as reaction tests.9 Few studies have administered reaction tests to patients with ACLR, and these have focused on reaction time during simulated driving10 and tapping lights while standing.11

Advanced neuromuscular training is recommended to prepare patients for the physical demands of sport participation.12‑14 Typical interventions including plyometrics, dynamic stability exercises, and agility drills to provide physical challenges that exceed traditional rehabilitation and address residual neuromuscular deficits that could increase risk for re-injury.12‑14 Post-training improvements include better hop test performance, agility, and self-reported knee function.14‑16 Dual-task challenges, such as ball catches, may be implemented during training to challenge motor control and improve dynamic knee joint sta-

bility while simulating sport conditions, but these are not the primary focus. It is unknown if advanced neuromuscular training improves performance on reaction tests, including physical and cognitive measures.

This study examined changes in performance on visuomotor reactions tests and single-leg hop tests following advanced neuromuscular training in patients with ACLR. The hypothesis was that performance would improve less on reaction tests than on single-leg hop tests. Study findings can provide insight into dual-task performance after ACLR and the impact of advanced neuromuscular training.

METHODS

STUDY OVERVIEW

This study used a quasi-experimental pretest-posttest design. Study participants completed testing immediately before and after participating in an advanced neuromuscular training program.

PARTICIPANTS

Patients with ACLR who enrolled in an advanced neuromuscular training program between January 2014 and June 2015 were eligible for this study Inclusion criteria were: (1) age 14–30 years at the time of surgery; (2) primary ACLR; (3) participated in organized sports that require cutting, jumping, or pivoting before injury; (4) intention to return to pre-injury activity level at the time of study participation. In addition, patients had to meet eligibility criteria for participating in advanced neuromuscular training: (1) at least five months postoperative; (2) symmetrical knee extension and knee flexion within five degrees of the contralateral knee; (3) able to hop vertically on the surgical leg without knee instability or pain; (4) trace effusion or less; and (5) surgeon approval. Exclusion criteria included previous lower extremity surgery or concomitant surgical procedures that alter postoperative rehabilitation (i.e., concomitant meniscal or ligamentous repair or cartilage stimulating procedure). Study criteria were meant to identify patients

with good potential to return to sport after ACLR. The study protocol was approved by the Institutional Review Board at the authors’ facility

DEMOGRAPHIC VARIABLES

Demographic variables collected from the electronic medical records included age, gender, body mass index (BMI), graft source, surgical side, concomitant surgeries, pre-injury sport, and time from surgery to pre-training and posttraining testing.

ADVANCED NEUROMUSCULAR TRAINING PROGRAM

The advanced neuromuscular training program has been described previously 16 Briefly, the training program is cash-based (USD 300 at the time of the study) and offered to patients after they finish standard rehabilitation and received surgeon clearance to initiate a return to sport participation. Patients in the study were enrolled in the training program and were not compensated for the cost of the training. Training sessions were held in group format at a frequency of two times per week over five weeks and duration of two hours per session for a total of 20 hours of training. Groups consisted of up to six patients supervised by a physical therapist and athletic trainer who provided feedback on movement patterns.16,17 Each session began with a dynamic warm-up that lasted approximately 20 minutes, then patients performed the neuromuscular exercises prescribed for that session for approximately one hour, and the session ended with cool down exercises of stretching or foam rolling. Neuromuscular exercises were categorized as dynamic stability, plyometric, agility, and strengthening, and exercises were progressed in physical demand over the course of training (Table 1). If necessary, exercises were modified for patient safety Some exercises incorporated a partner ball toss (e.g. ball catch while kneeling on or jumping on/off the BOSU ball) or were performed with reaction to a verbal command (e.g. cone drills) or ball-bounce (e.g., partner race to reaction ball), but this was intended to improve dynamic knee stability,18 not to resolve neural compensation. The volume of dual-task challenges in the advanced training program was low and did not exceed more than two exercises per session.

TESTING

Reaction tests were administered on a commercially available system consisting of a platform with five yellow dots on the surface connected to an electronic visual display (The QuickBoard, QuickBoard LLC, Memphis, TN) (Figure 1). The arrangement of the dots is two on the right side of the platform, two on the left side of the platform, and one in the center as on the number five side of a dice. Force sensors are located underneath the dots, and the arrangement of the dots is replicated on the visual display For the double-leg reaction test, patients stood with their feet positioned on either side of the center dot. Target dots were randomly presented on the visual display. The patient used the right leg to touch targets on the right side, the left leg

Table 1. Exercises in the Advanced Neuromuscular Training Program.

• Hop & hold

• Superman and swimmers on BOSU® ball

• Jump on/off BOSU® ball

• Hop & hold on Airex pad

• Kneeling on stability ball

• Hamstring curl on stability ball

• Tuck jumps (with or without hurdle)

• Box jump

• Scissor jump

• Lateral line hop (single- & double-leg)

• Lunge jump

• Various drills that incorporate running and shuffling with or without cones

• Dead lift

• Barbell squat

• Lunge

• Side plank

• Abdominal crunch

• Sidelying Copenhagen

• Rolling T (core strength progressions)

• Bridge (single- & double-leg)

1. Patient Position for Double-Leg (A) and Single-Leg (B) Reaction Tests.

to touch targets on the left side, and either of the legs to touch the center target. After the patient touched a target correctly, the next target was shown on the visual display. The test was performed for 20 seconds, and the number of correct touches and incorrect touches (i.e., errors) were recorded. The single-leg reaction test was first completed with the non-surgical leg. Patients stood on the nonsurgical leg positioned on the ipsilateral side of the center dot (e.g., right side of the center dot when the right leg was tested). Target dots were randomly shown on the visual display, and the patient hopped to the corresponding dot on the platform. When the target dot was touched, the next target was shown on the visual display. The test was complete when the patient had correctly hopped to 10 targets. Hop time was recorded in seconds, and the number of errors (i.e., incorrect touches) was recorded. The test was then repeated with the surgical leg.

Figure

The single leg hop tests were forward hop for distance, triple hop for distance, crossover triple hop for distance, and a six-meter timed hop.19 The non-surgical leg was tested first. For each hop test, patients received one or more practice trials and then performed three maximal effort test trials. The best performance was recorded in centimeters. A limb symmetry index was calculated as [(surgical limb performance/non-surgical limb performance) x 100] for distance measures and [(non-surgical limb performance/surgical limb performance) x 100] for the timed hop test. Testing was then repeated on the surgical leg.

STATISTICAL ANALYSIS

No power analysis was conducted for this study. Data were analyzed with SPSS version 28 (IBM Statistics,). Descriptive statistics were computed for all variables, including means and standard deviations for continuous variables and frequency distributions for categorical variables. The ShapiroWilk test assessed normality of the measures.20 The double-leg reaction test measures were found to have non-normal distribution due to outliers with a high number of errors; however, the data points were confirmed and the variables are continuous, so parametric statistics were used for all analyses. Alpha was set at 0.05 to determine statistical significance.

Pre- to post-training changes in the number of correct touches and errors on the double-leg reaction test were examined with paired t-tests. Separate repeated measures general linear models (limb x time) examined changes in hop time and the number of errors on the single-leg reaction test. Although not the primary purpose of this study, pre-to-post training differences in the limb symmetry indexes on each single leg hop test were examined with paired t-tests. This analysis was intended to confirm expected improvements in physical performance following advanced neuromuscular training.15 Effect size (Cohen’s d) was computed for the pre- to post-training difference in number of correct touches on the double-leg reaction test, surgical side hop time on the single-leg reaction test, and surgical side hop distance or hop time on the single-leg hop tests. An effect size of 0.2 is considered a small effect size, 0.5 is considered moderate, and > 0.8 is considered large.21

RESULTS

PARTICIPANT DEMOGRAPHICS

A total of 43 patients were enrolled in the study and completed pre-training testing, but four patients were excluded from analysis for missing data at pre-training and an additional 14 patients were excluded for missing data at posttraining (Figure 2). The missing data resulted from a combination of technological issues and a change in the testing protocol. Thus, only the data from the 25 patients who completed the entire study were included in the analysis.

Demographic information is found in Table 2 No significant differences were found in gender or age between patients analyzed and those excluded from the analysis

2. Participant flow diagram.

(p>0.05). The patients in the analysis included 54% females and 73% had ACLR with bone-patellar tendon-bone autograft.

PRE- TO POST-TRAINING CHANGE IN PERFORMANCE ON REACTION TESTS

Scores on the reaction tests are found in Table 3. For the double-leg reaction test, the number of correct touches significantly increased from pre- to post-training (p<0.001), but there was no significant change in the number of errors (p=0.637). The highest number of errors at pre-training and post-training was 12. For the single-leg reaction test, the main effect of time was significant for hop time (p=0.003), indicating that hop time improved in both the surgical and non-surgical legs. No significant main effect was found for number of errors on the single-leg reaction test (p>0.05). At pre-training, the highest number of errors on the surgical side was 9 and on the non-surgical side was 12. At posttraining, the highest number of errors on the surgical side was n=6 and on the non-surgical side was n=9.

EFFECT SIZES FOR CHANGE IN PERFORMANCE ON REACTION TESTS AND SINGLE-LEG HOP TESTS

Scores on the single-leg hop tests are shown in Table 4 Limb symmetry indexes on each single-leg hop test significantly improved from pre- to post-training (p<0.05). Effect sizes for the pre-to post-training change in test performance varied according to the difficulty of the test; specifically, effect sizes decreased in magnitude from single-leg hop tests to double-leg reaction test to single-leg reaction test (Table 5). All effect sizes were moderate to large.

Figure

Table 2. Demographic Information

Patellar Tendon

Graft source, n

Surgical side, n

Concomitant surgeries, n

Values for continuous variables are mean (SD).

Mass Index

Table 3. Pre- and Post-Training Performance on the Double-Leg and Single-Leg Reaction Tests.

*p<0.05

**Main effect for time, p<0.05

EXPLORATORY POST-HOC ANALYSIS

In the dataset, 13 patients had post-training limb symmetry indexes ≥90% for all single-leg hop tests and 12 patients failed to achieve the criteria for at least one single-leg hop test (one hop test: n=3; two hop tests: n=2; three hop tests: n=3; four hop tests: n=4). Independent samples ttests compared post-training results on the double-leg reaction test and single-leg reaction test (surgical side only) between groups. No significant group differences were found in correct touches (p=0.737) or errors (p=0.771) on the double leg reaction test or in surgical side hop time (p=0.073) or errors (p=0.237) on the single-leg reaction test (Table 6).

DISCUSSION

This study examined changes in performance on reaction tests (dual-task) and single-leg hop tests (single-task) following advanced neuromuscular training in patients with ACLR. The study hypothesis was supported. Performance

improved from pre-training to post-training on both reaction tests and single-leg hop tests, but the effect sizes were generally lower for reaction tests than for single-leg hop tests. Additionally, the mean number of errors on the reaction tests did not significantly change. The findings indicate that advanced neuromuscular training improves motor task performance in patients with ACLR but does not prepare them as well for performing motor tasks that include a cognitive challenge (i.e, visuomotor reaction test).

Results of this study support the concept of neural compensation, specifically neurocognitive reliance, after ACLR.8 Neural cognitive reliance is demonstrated in the current study by improvement in motor performance on the reaction tests without a significant improvement in the number of errors. The highest number of errors in any patient on the single-leg reaction test was lower following training, and this indicates that individual results might differ from overall group results. Future work is needed to understand if neurocognitive reliance occurs in all, or only some, patients with ACLR and how advanced neuromuscu-

Table 4. Pre- and Post-Training Performance on Single Leg Hop Tests. Reported as mean (SD)

Forward Hop

Triple Hop

Crossover Triple Hop

Timed Hop

Table 5. Effect Sizes for the Pre- to Post-training Change in Performance on Reaction Tests and Single-Leg Hop Tests.

Table 6. Post-Training Performance on Reaction Tests in Patients Categorized by Criteria for Single-Leg Hop Tests (≥90% Limb Symmetry Index on All Hop Tests). Reported as mean (SD).

lar training should be augmented to reduce neurocognitive reliance.

The dual-task test used in this study was a lower extremity visuomotor reaction test. Study results add to a small body of literature on reaction tests in patients with ACLR and could be used as comparative data in future studies. The exploratory analysis found no significant difference in post-training reaction test performance based on clinical criteria for return-to-sport (i.e., ≥90% limb symmetry index

on single-leg hop tests). The finding adds to knowledge that single-task motor performance and dual-task motor performance are not mirrored.22,23 It is yet unknown which dual-task testing methods provides meaningful insight into readiness for sport participation after ACLR. Visuomotor tests have been recommended, and a variety of reaction tests demonstrate good reliability8,24; however, interpretation of reaction test performance requires a benchmark. Alternatively, a motor task (e.g., single-leg hop tests) can

be administered with and without a cognitive challenge so that a “dual-task cost” metric can be computed.9 For this method, the cognitive challenge requires thoughtful selection, and equipment may be needed to acquire an objective measure. As visuomotor tests are developed, it will be important to understand the association with return-to-sport outcomes to determine their contribution within a comprehensive testing battery

It has previously been posited that neuromuscular training with a focus on biomechanical factors (i.e., movement control) might be inadequate to address neural compensation after ACLR.8 This is supported in the current study by the smaller effect size change in reaction test performance compared to single-leg hop test performance. The advanced neuromuscular training program incorporated some dualtasks conditions, such as catching a ball while balancing on an unstable surface, to challenge postural stability and dynamic joint stability, but a greater volume of dual-task challenges appears to be needed. It is yet unclear what training methods might be most effective. Positive changes in dual-task performance been reported in uninjured athletes after visuomotor25 and cognitive training on a computer,26 suggesting different methodologies for providing neurocognitive tasks in rehabilitation may be effective in minimizing neurocognitive reliance.

STRENGTHS AND LIMITATIONS

The strengths of this study are the application of novel reaction tests in patients with ACLR before and after participation in an advanced neuromuscular training program. The results of this study provide insight into dual-task visuomotor performance after ACLR as well as the impact of advanced neuromuscular training. The single-leg hop tests in the testing protocol are commonly used in return-tosport testing7 and provided a comparator to the reaction tests. The primary limitation of this study is the small sample size, which is partly due to the relatively large attrition from the initially included population. The attrition could

contribute to bias in the study if patient characteristics were different between those who did or did not complete the study Study bias may also be present because the advanced training program was cash-based, which means patients needed to be motivated and have financial means to participate. Another limitation is potential confounding from the dual-task challenges in the advanced neuromuscular training program that may have contributed to improved performance on the reaction tests. More of these dual-task challenges, or different challenges, may be needed for improving errors on the reaction tests. An additional limitation is the lack of a control group that would aid the understanding of performance changes that could be attributed to recovery over time. A final limitation is the lack of isokinetic quadriceps strength data. At the time of this study, the clinic did not own an isokinetic dynamometer Knowledge of quadriceps strength would aid the interpretation of neural compensation as patients with lower quadriceps strength (i.e., better motor reserve) are expected to demonstrate greater neural compensation.9

CONCLUSION

Motor performance in patients with ACLR improved after advanced neuromuscular training but the effects on visuomotor reaction tests were less than those effects seen on single-leg hop tests. The results suggest the persistence of neurocognitive reliance after ACL and for more dual-task challenges in advanced neuromuscular training to minimize neurocognitive reliance that might increase the risk for re-injury when returning to sport.

CONFLICT OF INTEREST

The authors declare that they have no conflict of interest.

Submitted: February 15, 2022 CDT, Accepted: October 03, 2024 CDT

The Author(s)

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Wohl TR,

CR,

AL,

DR. The Impact of Visual Perturbation Neuromuscular Training on Landing Mechanics and Neural Activity: A Pilot Study. IJSPT. 2024;19(11):1333-1347. doi:10.26603/001c.123958

The Impact of Visual Perturbation Neuromuscular Training on Landing Mechanics

and Neural Activity: A Pilot Study

Timothy R Wohl1,2 , Cody R Criss3,4,5 , Adam L Haggerty5,6 , Justin L Rush5,7 , Janet E Simon5,6 , Dustin R Grooms5,6,7a

1 Department of Physical Therapy, The Ohio State University, 2 Honors Tutorial College, Ohio University, 3 Translational Biomedical Sciences Program, Ohio University, 4 Heritage College of Osteopathic Medicine, Ohio University, 5 Ohio Musculoskeletal & Neurological Institute, Ohio University, 6 Department of Athletic Training, Ohio University, 7 Department of Physical Therapy, Ohio University

Keywords: anterior cruciate ligament, neuroimaging, fMRI, injury prevention https://doi.org/10.26603/001c.123958

International Journal of Sports Physical Therapy Vol. 19, Issue 11, 2024

Background

Athletes at risk for anterior cruciate ligament (ACL) injury have concurrent deficits in visuocognitive function and sensorimotor brain functional connectivity

Purpose

This study aimed to determine whether visual perturbation neuromuscular training (VPNT, using stroboscopic glasses and external visual focus feedback) increases physical and cognitive training demand, improves landing mechanics, and reduces neural activity for knee motor control.

Design

Controlled laboratory study

Methods: Eight right leg dominant healthy female athletes (20.4±1.1yrs; 1.6±0.1m; 64.4±7.0kg) participated in four VPNT sessions. Before and after VPNT, real-time landing mechanics were assessed with the Landing Error Scoring System (LESS) and neural activity was assessed with functional magnetic resonance imaging during a unilateral right knee flexion/extension task. Physical and cognitive demand after each VPNT session was assessed with Borg’s Rating of Perceived Exertion (RPE) for both physical and cognitive perceived exertion and the NASA Task Load Index. Descriptives and effect sizes were calculated.

Results

Following VPNT, LESS scores decreased by 1.5 ± 1.69 errors with a large effect size (0.78), indicating improved mechanics, and reductions in BOLD signal were observed in two clusters: 1) left supramarginal gyrus, inferior parietal lobule, secondary somatosensory cortex (p=.012, z=4.5); 2) right superior frontal gyrus, supplementary motor cortex (p<.01, z=5.3). There was a moderate magnitude increase of cognitive RPE between the first and last VPNT sessions.

Conclusion

VPNT provides a clinically feasible means to perturbate visual processing during training that improves athletes’ real-time landing mechanics and promotes neural efficiency for lower extremity movement, providing the exploratory groundwork for future randomized controlled trials.

Corresponding Author: Dustin Grooms

Grover Center W283, 1 Ohio University, Athens OH 45701-2979 groomsd@ohio.edu

Criss

Haggerty

Rush JL, Simon JE, Grooms

Level 3

INTRODUCTION

The anterior cruciate ligament (ACL) is a static knee stabilizer that is commonly injured in sports.1,2 The incidence of ACL injury has continued to rise over the years, with young female athletes being at an increased risk for noncontact ACL injuries compared to males.3‑6 Injury prevention programs (IPP) are a common tool used to reduce the incidence of ACL tears, but these programs have limited efficacy, as they require ~100 participants to prevent a single ACL injury and may not target all aspects of injury risk.7,8 Typical IPPs target biomechanical risk factors associated with ACL injuries, such as knee valgus and stiff-legged landing patterns.9,10 However, the efficacy of IPPs may be limited by treatment approaches targeting biomechanical outputs without accounting for critical nervous system processes that contribute to injury risk.11‑13

Dynamic knee valgus, or collapse of the knee toward midline during landing, is a specific and sensitive biomechanical risk factor for ACL injury,9 which has been associated with neurocognitive deficits14 (e.g., visual attention, reaction time) and increased sensorimotor and visuospatial neural activity12,13 for knee movement during functional magnetic resonance imaging (fMRI). Taken together, these studies suggest athletes at increased risk of ACL injury employ sensorimotor control strategies highly influenced by the visuocognitive system. Further support comes from three prospective studies: one that identified baseline visuospatial deficits in uninjured athletes who later sustained an ACL injury15; and two studies that used resting state MRI to identify decreased sensorimotor brain functional connectivity in uninjured athletes who later sustained an ACL injury 11,16 Taken together, these neurophysiological and neurocognitive data support the influence of sensory and visuospatial cognition on injuryrisk. Therefore, incorporating visuocognitive training into IPPs may improve their efficacy by preparing athletes for the visually and cognitively demanding dynamic sport environment.

A simple and relatively cost-effective way that IPPs could add visuocognitive training is by incorporating stroboscopic glasses (SG).17 SG allow for portable visual perturbation by alternating between clear and opaque lens states at controllable frequencies. This high degree of control enables clinicians/athletic trainers/coaches to incrementally perturb the amount of visual information available to their athletes during neuromuscular training. SG has previously been used in a research setting to assess training effects on behavioral performance, neurocognitive function, and sport-specific abilities,18‑28 but there is a paucity of research quantifying neural activity changes following visuocognitive training with SG. Therefore, we developed visual perturbation neuromuscular training (VPNT, injury prevention exercises29,30 overlayed with visual perturbation via SG and external focus feedback to direct attention to the environment) to fill this gap. The purpose

of this study was to determine changes in landing mechanics, neural activity (quantified using blood-oxygen-leveldependent [BOLD] signal) for knee motor control, and physical and cognitive training demands in young female athletes following VPNT

METHODS

SCREENING

This study was approved by Ohio University’s Institutional Review Board, and all experiments were performed in accordance with the approved protocol. Pre-/post-intervention procedures and VPNT were carried out by one researcher (TW). Female recreational athletes (at least 3 hours of moderate-to-vigorous exercise per week, including one hour of running, cutting, pivoting, or decelerating every week) aged 18-30 were included. Eight female participants (8 F; age = 20.4 ± 1.1 years, height = 1.6 ± 0.1 m, mass = 64.4 ± 7.0 kg) from Ohio University (Athens, OH) were enrolled to participate in this study, and informed written consent was obtained prior to participation. All participants were right leg dominant and met the exercise requirement criteria, as determined by the Marx Activity Rating Scale,31 which assesses one’s general level of activity on four metrics indicating involvement in activities requiring running and rapid change of direction (run=2.6±0.7, cut=1.9±1.6, decelerate=1.9±1.6, pivot=2.1±1.5). No formal power analysis was completed as these data are exploratory and meant to be hypothesis-generating.

Participants were excluded who were contraindicated for fMRI (e.g., pregnancy, implanted metal devices, claustrophobia, and any other criteria as determined by the MRI operator), had visual impairments, had a history of seizures or epilepsy, or had a history of surgery on the back, hip, leg, knee, etc. Other screening criteria included: primary sport, leg dominance, and exclusion for previous leg injury or medical history of anxiety disorder, ADHD, depression, diabetic neuropathy, concussion or traumatic brain injury, cerebral palsy, balance disorder, vertigo, Parkinson’s disease, multiple sclerosis, substance abuse or dependence, heart disease/defect.

PRE-/POST-INTERVENTION LANDING ERROR SCORING SYSTEM (LESS) ASSESSMENT

The LESS is a clinical tool used to assess lower extremity injury risk by identifying injury risk landing mechanics during a jump-landing task.32,33 To ensure participants were enrolled that would benefit from the training, potential subjects were screened and only enrolled participants with high injury risk landing mechanics (LESS score of 6+). This cutoff was selected as prior work validated the 6+ error threshold with 3D motion capture to discriminate between high and low risk biomechanics.34 A total of 20 athletes were screened and eight met the enrollment criteria.

A designated experimenter (TW) was trained to evaluate jump-landing mechanics in real-time using the LESS. For training, TW rated the landing biomechanics of athletes using the LESS while watching 50+ videos from frontal and sagittal views. TW’s ratings were compared with an expert’s ratings (with 10+ years of clinical experience) until TW’s ratings were reliable and valid (over 90% agreement).35‑37 The LESS methods have previously demonstrated good to excellent intra- (ICC: .82-.99) and interrater (ICC: .83-.92) reliability as well as good intersession reliability (ICC: .81).36,38

Participants performed the jump-landing task for the LESS four times: twice with a face-forward frontal view and twice with a right (dominant) sagittal view Participants performed the jump-landing task on a 30 cm tall box, landed at a distance equal to half their height, and were given unlimited practice trials until they could perform the task correctly and explicitly follow test instructions.32 Participants received the following instructions and no additional feedback: 1) stand at the edge of the box in a neutral position, 2) jump forward so both your legs leave the box simultaneously, 3) land just past the target line, and 4) jump for maximal height immediately after landing Trials were considered successful if the participant jumped from the box using both feet, cleared the minimum distance and performed the task in a fluid motion. All unsuccessful trials (e.g., the participant jumped vertically from the box) were excluded and repeated until four successful jumps were completed.32 After the final VPNT training session, participants completed the same jump-landing task to determine intervention efficacy of reducing high injury risk landing biomechanics. Total LESS score was used for statistical analyses pre- and post-intervention.

PRE-/POST-INTERVENTION NEUROIMAGING ASSESSMENT

All participants completed a pre- and post-intervention fMRI neuroimaging session (~45 minutes including set-up, instruction, and scan time). During imaging, all participants wore standardized shorts and socks without shoes to reduce the possibility of altered skin tactile feedback. Participants also wore a splint to lock their right (dominant leg) ankle at neutral (~0 degrees) to minimize ankle movement throughout the scan. Headphones and hearing protection were provided for safety and communication. While lying supine in the scanner, participants were strapped down to the table with four straps: one across the thighs at the mid-point between the greater trochanter and knee joint line, one across the hips at the anterior superior iliac spines, and two in an X pattern across the chest from each shoulder to the pelvis. Participants were also fitted with customized padding to reduce head motion. This padding was high-density MRI-safe foam that was inserted around the sides and top of the head to remove space between the skull and head coil. This was customized based on skull size. The straps and customized padding were employed to reduce head motion during imaging. A priori head motion threshold for exclusion was set at >0.35 mm of relative motion to ensure high quality data.

The methods used for the fMRI knee motor control task are based on previous literature that mapped whole brain activity and lateralization of the brain activity during isolated lower extremity movements.39,40 Similar knee specific motor tasks have demonstrated good to excellent reliability across days to weeks.41‑43 Standardized auditory cues informed the participants when to move and rest, and the frequency of the movement (1.2 Hz). The participants’ dominant (right) leg rested upon a foam roller and alternated from ~40 degrees flexion to full extension, while the nondominant (left) leg rested at full extension (0 degrees). This motion was completed continuously for 30 seconds with 30 seconds of rest (right leg relaxed at ~40 degrees flexion) for four total cycles. The participants were given an opportunity to ask questions and practice the task with feedback from the experimenter

Prior to data collection at the MRI, participants completed a mock MRI session where they familiarized themselves with the MRI environment, restraints to reduce head motion, and the lower extremity motor task. The participants were permitted to ask questions and practice the tasks with feedback from the experimenter. The practice session included three practice blocks (30 seconds each) of the motor task with examiner cueing to ensure the participant understood the task, followed by a complete run of the task with the same feedback and timing as during the actual MRI data collection session. This standardized training and mock scanning session played a vital role in reducing head motion during the task, performing the task correctly, and ensuring participants were not claustrophobic.

fMRI scans were collected at Holzer Health (Athens, OH) using a 16-channel head coil. Prior to the functional data collection, a 3-diminsional high-resolution T1-weighted image (repetition time: 2000 ms, echo time: 4.58 ms, field of view: 256×256 mm; matrix: 256×256; slice thickness 1 mm, 176 slices, 8° flip-angle) was collected for image registration (~8 minutes). fMRI collection parameters included 10 whole-brain gradient-echo-echo planar scans per block (4 movement blocks, 5 rest blocks) acquired with a 3 second TR with anterior-posterior phase encoding and a 3.75×3.75 in plane resolution, 5 mm slice thickness for 38 axial slices with a 35 ms TE, 90° flip angle, field of view 240 mm and 64×64 matrix. The functional knee extension/flexion run lasted 4 minutes and 30 seconds. fMRI measured regional brain activity during rest and motor control conditions, which were contrasted to isolate the regional brain activity to the knee flexion/extension task.

VISUAL PERTURBATION NEUROMUSCULAR TRAINING

All participants completed four separate one hour-long training sessions within two to three weeks. These sessions combined agility, balance, and plyometric exercises with visual perturbation training. VPNT exercises were developed based on a previous clinical commentary and methodology paper,44 detailing how chosen exercises were selected to offset the risk of initial ACL rupture and further modified to incorporate a movement goal that required the participants to interact with an external visual object or target.30,

45,46 Each training session spanned one hour with rest interspersed throughout the session to avoid fatigue.

I. AGILITY EXERCISES

• Exercise 1: The T-test involved running 6 m to tap a cone, cutting to the right or left for 3 m to tap another cone, cutting the opposite direction for 6 m to tap a third cone, returning to the center by cutting 3 m to tap the first cone, then running 6 m back to the start position – thereby running in a “T” shape. The experimenter verbally instructed the participant which direction to cut after the participant left the start position, but prior to reaching the first cone reducing ability to plan direction and anticipatory time.

• Exercise 2: Agility ladder drills required the participant to quickly match specified foot placement patterns within the agility ladder The experimenter used five visual aids to instruct each participant on how to perform the foot placement pattern to minimize direct explicit feedback (cones, lines etc.) and increase the salience of the SG visual perturbation.

II. BALANCE EXERCISES

• Exercise 1: Single-leg Romanian deadlifts required the participant to pick up and gently set down a cup at one of three locations marked on the ground (-30, 0, +30 degrees from center) at a distance equal to his or her max volitional reaching distance. The experimenter verbally instructed the participant of which location to place the cup at random. The participant alternated legs for each trial.

• Exercise 2: Single-leg stance required the participant to stand on a foam surface while holding a lightweight bar horizontally for 30 seconds. The experimenter instructed the participant to maintain the bar’s horizontal orientation and to quickly reset her single-leg stance if the participant placed a second limb on the ground. The participant alternated legs for each trial.

III PLYOMETRIC EXERCISES

• Exercise 1: The vertical jump task required participants to reach 80% of their max vertical jump height as measured by a Vertec, a vertical jump tester that serves as the external target during the task. Additionally, the vertical jump task incorporated an unanticipated unilateral landing, where the experimenter called out the desired landing leg as soon as the participant began the flight phase of the jump.

• Exercise 2: The jump squat task incorporated a cognitive challenge: participants had to perform a jump squat and land facing a target in one of four locations (0, 90, 180, 270 degrees from the participant in the center); the specified location was quickly called out at random by the experimenter

Table 1. Error scoring system used to assess behavioral performance.

Exercise Error Count T-test

1. Miss a cone

2. Cut to the wrong direction

Agility Ladder Drills

Single-leg Deadlifts

Single-leg Stance (on foam)

Vertical Jumps Squat Jumps

STROBOSCOPIC GLASSES

1. Hit the ladder

2. Incorrect foot placement

1. Opposite foot touches ground

2. Either hand touches ground

3. Object placed in wrong location

1. Opposite foot touches ground

2. Either hand touches ground

1. Miss the target

2. Land on wrong foot

1. Land facing wrong direction

All participants initially performed all exercises without SG to familiarize themselves with the task at every training session. SG were then worn throughout all other trials for each exercise. For the first training session, SG remained at level 1 throughout the whole training session (highest frequency of fluctuation between clear and opaque states and the lowest level of visual perturbation). For the second, third, and fourth training sessions, SG remained at levels 2, 3 and 4, respectively, for the duration of each training session. SG’s opaque state duration progressively lengthened with each subsequent training session (25 ms for level 1, 43 ms for level 2, 67 ms for level 3, and 100 ms for level 4) while the clear state duration remained constant across SG levels (100 ms), thereby creating greater interruptions in the availability of visual information for the participants. This approach standardizes SG difficulty exposure for each participant.

ERROR SCORING SYSTEM

An error scoring system (Table 1) assessed behavioral performance during training sessions. Scores are reported as counts, which reflect the number of errors incurred during each exercise. All errors are counted equally (one count per error).

QUESTIONNAIRES

The Rating of Perceived Exertion (RPE) scale47 and NASA Task Load Index (NASA TLX)48‑51 were presented to the athletes after each training session to assess perceived levels of difficulty performing exercises with SG. RPE assesses perceived exertion level on a scale from 0 (Nothing at All) to 10 (Very, Very Hard). Both physical and cognitive RPE were assessed. Physical exertion refers to the physical work

of the athlete to perform the exercise. Cognitive exertion refers to the mental work required of the athlete to complete the exercise goal. NASA TLX assesses mental workload on six separate scales (mental demand, physical demand, temporal demand, performance, effort, frustration), each with 21-point scale gradations.

DATA & STATISTICAL ANALYSIS

The fMRI technique used in this study quantified the BOLD signal via the hemodynamic response (blood flow) by contrasting the lower extremity motor control condition with interspersed rest conditions.52 The BOLD response quantified via fMRI collection and analysis has been validated against actual neural recordings, demonstrating a very high correlation between blood flow and neural activity 53,54 The reliability of fMRI quantification of the BOLD signal is generally high and specific to knee movement and has high inter-session reliability.43,55

The fMRI image analyses and statistical analyses were performed using the Oxford Centre for Functional MRI of the Brain Software Library.56 Image analysis began with standard pre-statistic processing applied to individual data in the standardized FSL recommended order,57 which included nonbrain removal, slice timing correction, standard motion correction and realignment parameters (3 rotations and 3 translations) as covariates to limit confounding effects of head movement and spatial smoothing at 6 mm before statistical analysis.58 High-pass temporal filtering at 100 Hz and time-series statistical analyses were carried out using a linear model with local autocorrelation correction. Functional images were coregistered with the respective high-resolution T1 image and the standard Montreal Neurological Institute template 152 using linear image registration. This registration process allowed data from each participant to be spatially aligned on a standardized brain template for comparison.

The subject-level analysis of knee sensorimotor control relative to rest was completed using a cluster corrected zscore greater than 3.1 and significance threshold of p<.05 (corrected). The cluster correction for multiple comparisons uses a variant of the Gaussian random field theory to decrease type I error in statistical parametric mapping of imaging data by evaluating the activation not only at each voxel, but also at the surrounding voxel cluster (as it is unlikely that the voxel tested and surrounding voxels are active above the threshold due to chance).59‑61 The paired contrast between the pre- and post-intervention brain activity was cluster corrected with z scores greater than 3.1 and a significance level of p<.05 (corrected). This pair-wise analysis compares each individual’s pre-/post-intervention brain activity and averages those differences at the group level.

Descriptive statistics including means, standard deviations, 95% confidence intervals (CIs), and Hedge’s g effect sizes were calculated for the LESS, error scores during each training session, RPE, and NASA TLX. With this being a proof-of-concept study with a small sample size, inferential statistics were not calculated. To evaluate the impact of VPNT on these variables, Hedge’s g effect sizes were used

because of the small sample size and interpreted as 0.0-0.3 as small, 0.4-0.5 as medium, and 0.6-0.8 as large.62

RESULTS

Descriptive statistics including 95% CIs and effect sizes for the LESS, error scores, RPE, and NASA TLX are provided in Table 2 All re-assessments were completed within 23 ± 4.3 days from initial assessments. LESS scores decreased by 1.5 ± 1.69 errors with a large effect size after VPNT Regarding individual participant’s changes in LESS scores, 5 participants’ scores decreased, 3 did not change, and 0 increased after VPNT (Figure 1). Agility errors from day 1 to day 4 of VPNT had a medium effect size with decreased errors of -2.6±5.2. Lastly, RPE-C had a large effect size between day 1 and day 4 of VPNT with an increase of 1.5±2.2 points.

Regional brain activity are reported that were identified in FSLeyes based on peak-voxel with the Harvard-Oxford Cortical & Subcortical Structural Atlas,63 Juelich Histological Atlas,64,65 and the Cerebellar Atlas in MNI152 space after normalization with FNIRT66 and with FSL tool atlasquery.57 The atlasquery function from FSL utilizes the averaged probability across all voxels in the cluster to identify probabilistic anatomy across the cluster ensuring reporting of peak voxel location and overall cluster spatial representation.

The results are presented as a z-score (activation level relative to the contrast of pre- vs post-intervention) and percent signal change for each group from baseline to sensorimotor control in Table 3 By comparing pre- and postintervention regional brain activity, reduced BOLD signals were demonstrated in two clusters following VPNT (Figure 2, Table 3): 1) left supramarginal gyrus, inferior parietal lobule, secondary somatosensory cortex (158 voxels; 4.51 zstat; p=0.0122 cluster corrected; MNI -50,-26,34); 2) right superior frontal gyrus, supplementary motor cortex (314 voxels; 5.33 z-stat; p=0.000159 cluster corrected; MNI 16,-4,72). The clusters are the group average of the paired contrasts of each participant at pre/post timepoints (n=7). One participant was excluded from the fMRI analysis due to excessive head motion (>0.35 mm relative head motion and task correlated). Average relative head motion across the remaining seven participants was 0.11±0.05 mm and absolute head motion was 0.35±.19 mm.

DISCUSSION

LANDING SCORES FOLLOWING VPNT

Each participant’s landing mechanics were evaluated with the LESS at pre-/post-intervention timepoints to assess VPNT effects on biomechanical ACL injury risk. There was a decrease in LESS score after VPNT, indicating that VPNT can improve landing mechanics and potentially reduce injury risk. The mean difference in LESS score after VPNT (1.5±1.69) is similar to other reports of improved LESS scores after injury prevention programs, despite the relatively shorter intervention of only two weeks.67‑71 For example, an aquatic injury prevention program that only in-

Table 2. Descriptive statistics of the LESS (yellow), error scoring system (blue), RPE (green), and NASA-TLX (orange). Values for each training session (days 1, 2, 3, 4) were averaged across all participants (n=8) and reported as mean ± standard deviation (95% CI). The difference between the first and last session (Day 4 – Day 1) is reported as mean ± standard deviation (effect size). *For the LESS, “Day 1” and “Day 4” correspond to testing days before and after Days 1 and 4 of training, respectively Abbreviations: SLD (single-leg deadlift); SLS (single-leg stance); RPE (Rating of Perceived Exertion); RPE–C (RPE, Cognitive); RPE–P (RPE, Physical); NASA (NASA Task Load Index); NASA–M (NASA, Mental); NASA–Ph (NASA, Physical); NASA–T (NASA, Temporal); NASA–PE (NASA, Performance); NASA–E (NASA, Effort); NASA–F (NASA, Frustration).

(0.08) SLS 8.0 ± 5.9 (3.9, 12.1) 5.0 ± 4.2 (2.1, 7.9) 4.0 ± 4.6 (0.8, 7.2) 5.4 ± 6.37 (1.0, 9.8) -2.6±9.9 (-0.37)

Jump Squat 4.6 ± 3.5 (2.2, 7.0) 4.4 ± 2.4 (2.7, 6.1) 4.9 ± 1.5 (3.9, 5.9) 4.1 ± 2.5 (2.4, 5.8) -0.5±2.7 (-0.15)

Vertical Jump 5.1 ± 3.0 (3.0, 7.2) 3.9 ± 2.4 (2.2, 5.6) 4.5 ± 3.7 (1.9, 7.1) 3.9 ± 3.2 (1.7, 6.1)

(-0.34) RPE–C 3.0 ± 1.1 (2.2, 3.8) 2.9 ± 1.1 (2.1, 3.7) 3.8 ± 2.6 (2.0, 5.6) 4.5 ± 2.5 (2.8, 6.2) 1.5±2.2 (0.69) RPE–P 3.6 ± 1.5 (2.6, 4.6) 3.9 ± 1.8 (2.7, 5.2) 3.6 ± 1.7 (2.4, 4.8) 4.1 ± 2.0 (2.7, 5.5) 0.5±2.5 (0.25) NASA–M 9.0 ± 4.3 (6.0, 12.0) 8.5 ± 4.3 (5.5, 11.5) 10.0 ± 6.1 (5.8, 14.2) 10.8 ± 6.3 (6.4, 15.2) 1.8±5.0 (0.30)

NASA–Ph 9.6 ± 4.1 (6.8, 12.4) 9.9 ± 4.2 (6.7, 12.8) 9.3 ± 3.9 (6.6, 12.0)

cluded female participants and lasted for six weeks improved LESS scores by 1.68±1.68 (p=0.004).67 Another study that included mixed-gender youth soccer teams implemented a prevention training program led by athletic trainers for eight weeks and yielded similar results (1.29±0.34, p=0.01).68 The ability of VPNT to achieve similar behavioral outcomes as traditional IPPs in a shorter timeframe could improve athlete/coach compliance for teams with limited resources and time.

It is important to note that while most participants (n=5) in the present study experienced improved landing mechanics after the intervention, some participants (n=3) did not change scores and no participants experienced worsened (higher) LESS scores. Therefore, while VPNT may preferentially improve some athletes’ landing mechanics more than others, no athlete experienced worsened per-

formance after training. In comparison to previous studies67,71 that used LESS to measure an injury prevention program’s efficacy and reported an increase in LESS score post-intervention for some select participants, the current study may lack such findings due to the individualized nature of the training sessions, the addition of SG and external focus feedback, or small sample size. Further, Gholami et al.26 showed that training with visual information disruption improved landing mechanics in a larger study with athletes who already completed post-op ACL reconstruction rehabilitation.

Motor performance errors were tracked during each training session that consisted of objective, clinicalfriendly measures of motor performance (e.g., the number of times an athlete placed their opposite foot down during a single-leg balance task). As SG difficulty increased with

Figure 1. Left: Individual participant LESS scores at pre- and post-VPNT timepoints; two subjects with identical scores (pre/post LESS of 6) overlap and share the same circle/line. Right: Within-subject differences, with the mean of difference represented by the solid horizontal line.

Figure 2. Cross-sections of composite brains that reflect the two clusters with statistically significant decreased neural activity following VPNT. Cluster 1: left supramarginal gyrus, inferior parietal lobule, secondary somatosensory cortex. Cluster 2: right superior frontal gyrus, supplementary motor cortex.

each training session, the error scores did not substantially change between Day 1 and Day 4 of training for all exercises except for the agility ladder drills, which had a medium effect size of decreased errors (Table 2). Taken together, the training effects on error scores indicate that progressing SG difficulty between levels 1 through 4 does not impair motor performance as assessed by our clinician error scoring system (Table 1). Therefore, decreasing the amount of vi-

sual information available to athletes with SG did not hinder participant’s ability to complete their desired movement goals/objectives during training.

BOLD SIGNAL AND NEURAL ACTIVATION PATTERNS FOLLOWING VPNT

Another aim of this study was to quantify the brain activation changes after VPNT during a knee flexion/extension task. Cluster 1 of decreased activation included the left supramarginal gyrus, inferior parietal lobule and secondary somatosensory cortex, indicating increased neural efficiency (i.e., reduced neural activity demands) in visuospatial/visuomotor processing,72‑76 somatosensory integration, and attention.77‑79 Cluster 2 of decreased activation included the right superior frontal gyrus and supplementary motor cortex, indicating increased neural efficiency in motor planning.80,81 Overall, neural efficiency in both clusters may reflect training effects from VPNT, which aimed to improve neuromuscular control and the neural activity associated with baseline high injury risk landing mechanics (e.g., increased visuospatial and sensorimotor neural activity).82 Decreased activity in both clusters aligns with motor skill learning83‑85 and improved expertise86,87 specific to lower extremity motor control. Recently, Grooms et al.,88 similarly examined brain activation changes during a knee flexion/extension task in healthy female athletes who underwent neuromuscular training with implicit augmented biofeedback and identified an association between sensory neural activity changes and improved landing mechanics.

The current results are also similar to prior work by Seidel et al.87 that measured brain activity with functional near-infrared spectroscopy during balance training, finding decreased neural activity pre to post-training in the primary motor cortex and inferior parietal lobe to maintain postural stability. The similar regions of decreased activity secondary to improvements in lower extremity motor control (the current study) and postural control (Seidel et al.87), despite the differences in intervention (multimodal balance training87 vs. VNPT) and testing (fNIRS vs. fMRI), may support the key role of proprioceptive processing and motor planning neural efficiency to improve motor performance.

In addition to decreased localized neural activity demands, neural efficiency can be a function of enhanced connectivity between supporting regions. Previous work using resting-state fMRI identified increases in fronto-parietal connectivity following dynamic balance training, where participants had to maintain the horizontal positioning of an unstable stabilometer platform for repeated 30 second intervals.85 After two ~45 minute training sessions spread over two weeks, intrinsic functional connectivity increased between the supplementary motor cortex and parietal cortex. These results following balance training align with the results of the current study, as VPNT (four, 1-hour training sessions spread over two weeks) facilitates functional activity changes in fronto-parietal regions (clusters 1 and 2 of the current study) that could support enhanced connectivity.

Table 3. Regions of brain activity are reported that were identified in FSLeyes with the Harvard-Oxford Cortical & Subcortical Structural atlas, Julich histological atlas and the Cerebellar Atlas in MNI152 space after normalization with FNIRT and with FSL tool atlasquery. *Indicates identified on peak voxel.

PHYSICAL AND COGNITIVE TRAINING DEMANDS

There were no substantial changes in physical or cognitive training demands across the intervention as assessed with the RPE-P and NASA TLX. There was an increase in RPEC, indicating that VPNT preferentially increases cognitive demand over physical demand. Overall physical and cognitive training demands were largely maintained by increasing the visual perturbation dosage each session. One might expect a decrease in training difficulty and demand over time if the SG were not worn, as the athletes experience practice and learning effects for the exercises. Furthermore, of the six metrics measured with the NASA TLX, “frustration” tended to score the lowest. This suggests SG is not aversive to athletes during exercise, which is important for clinicians who want to ensure that their patients have adequate “buy in” and do not become frustrated with the technology.

CLINICAL IMPLICATIONS

This study utilized SG to perturbate vision during agility, balance, and plyometric exercises in female recreational athletes. By comparing pre-/post-intervention brain activity during a knee flexion/extension task, the results show that VPNT has the potential to modulate somatosensory, visual, and motor neural activity. Promoting increased neural efficiency in visuomotor and visuospatial regions of the brain, VPNT may have the ability to improve neuromuscular control and movement efficiency Additionally, subjective reports of frustration with SG were low, and our athletes’ motor performance (error count) was not substantially worsened by progressing SG difficulty Therefore, SG is an attractive, novel modality that warrants further research in future studies that apply visual perturbation training to populations with a maladaptive, increased reliance on vision for motor control (e.g., patients with ACLR).89,90

LIMITATIONS

While the reliability of fMRI quantification of the BOLD signal is generally high and specific to knee movement has high inter-session reliability,43,55 this study is limited by the lack of a control group and small sample size (n=8). Thus, the analyses included 95% CIs and effect sizes instead of inferential statistics to illustrate this proof-of-concept pilot study

The inclusion of a control group, who underwent the same intervention without SG, would allow the authors to delineate whether the results were driven by visual perturbation, neuromuscular training, or their combination. However, published reliability data indicates that no change in the neural activity metrics should be expected across this timeframe if engaged in regularly daily activity, increasing probability that the intervention induced the changes.41 The inclusion of only high injury risk female athletes may prevent the generalization of these findings to non-female athletes and athletes with low injury risk landing biomechanics. And it is reasonable that VPNT may not

be as effective in athletes who already display good landing mechanics. Finally, due to practice trials and performance of four or more recorded trials for the LESS, there was potentially a learning effect of the LESS which could have influenced the scores. However, the practice trials are necessary to ensure the LESS is being performed correctly to complete the assessment, and these methods have demonstrated high reliability 32 Controlling the total number of trials completed (practice and recorded) may be beneficial for a larger clinical trial.

FUTURE DIRECTIONS

Future research may explore VPNT training effects with a longer timeframe (such as six or eight weeks), VPNT training effects in other populations (such as males, the aging, or patients with ACL injuries), or whether the behavioral and neuroimaging effects of VPNT are resilient against time (e.g., 3-month follow-up). Patients with ACL injuries may preferentially benefit from VPNT as they exhibit increased LESS scores relative to uninjured controls91 and an increased reliance on visual information processing to guide motor control.92,93 Future research is needed to examine task-based connectivity following VPNT, as the current study provides support for the use of primary and secondary motor regions and parietal cortex as key regions of interest. Also, the incorporation of 3D motion capture would enable future researchers to increase their sensitivity to movement metrics altered by VPNT Future research is needed to compare an intervention group to a control group to provide further validation for this proof-of-concept study Finally, future clinical trials with larger sample sizes should also consider potential factors that could limit reproducibility and reliability of the collection including the learning curve of examiners training individuals, the length of training sessions, and the cost of MRI.

CONCLUSION

This proof-of-concept pilot study evaluates the potential of VPNT to alter landing mechanics, neural activity, and physical/cognitive training demands in uninjured female recreational athletes. The findings suggest that visual perturbation training improves landing mechanics and visuocognitive abilities simultaneously by promoting neural efficiency in brain regions responsible for sensorimotor integration, visuomotor/visuospatial processing, and motor planning.

CONFLICTS OF INTEREST

The authors declare no competing interests.

FUNDING

This study was supported in part by the US Department of Defense Congressionally Directed Medical Research Program Peer Reviewed Orthopaedic Research Program Re-

search Award (81XWH-18-1-0707) and NIH/National Institute of Arthritis and Musculoskeletal and Skin Diseases NIH/NIAMS; Awards NIAMS; R01AR076153 and R01AR077248. Opinions, interpretations, conclusions, and recommendations are those of the author and are not necessarily endorsed by the Department of Defense and NIH/ National Institute of Arthritis and Musculoskeletal and Skin Diseases.

ACKNOWLEDGMENTS

We thank the Holzer Health system and Holly Henry MRI technologist and Dr. Phillip B. Long radiologist for MRI support.

DATA AVAILABILITY

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Submitted: February 12, 2024 CDT, Accepted: August 28, 2024 CDT

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Mangine RE, Palmer TG, Tersak JA, et al. Task-Driven Neurophysiological qEEG Baseline Performance Capabilities in Healthy, Uninjured Division-I College Athletes. IJSPT 2024;19(11):1348-1361. doi:10.26603/001c.124935

Task-Driven Neurophysiological qEEG Baseline Performance

Capabilities in Healthy, Uninjured Division-I College Athletes.

Robert E. Mangine, PT, ATC, Med1,2 , Thomas G. Palmer, PHD, ATC, CSCS*D, TSAC-F3 , James A. Tersak1,2 , Michael Mark, PsyD, BNC4 , Joseph F Clark, Ph.D, Marsha Eifert-Mangine, PT, ATC, EdD, CERT1,3a , Audrey Hill-Lindsay, PhD4 , Brian M Grawe, MD5,6

1 NovaCare Rehabilitation, A Select Medical Company, Mechanicsburg, PA, USA, 2 University of Cincinnati Athletics, Cincinnati, OH, USA, 3 Mount St. Joseph University, Cincinnati, OH, USA, 4 CLR Neurosthenics, Inc., Manhattan, CA, USA, 5 University of Cincinnati, College of Medicine, Cincinnati, OH, USA, 6 Team Physician, Cincinnati Bearcats & Cincinnati Bengals, Cincinnati, OH USA

Keywords: Neurophysiological assessment, Neuroplasticity, Quantitative electroencephalography/qEEG, Brain Mapping, Mirror Neuron Network, Neural networks

https://doi.org/10.26603/001c.124935

International Journal of Sports Physical Therapy

Vol. 19, Issue 11, 2024

Background

Athletic performance can be measured with a variety of clinical and functional assessment techniques. There is a need to better understand the relationship between the brain’s electrical activity and the body’s physiological performance capabilities in real-time while performing physical tasks related to sport. Orthopedic functional assessments used to monitor the neuroplastic properties of the central nervous system lack objectivity and/or pertinent functionality specific to sport. The ability to assess brain wave activity with physiological metrics during functional exercises associated with sport has proven to be difficult and impractical in real-time sport settings. Quantitative electroencephalography or qEEG brain mapping is a unique, real-time comprehensive assessment of brain electrical activity performed in combination with physiometrics which offers insight to neurophysiological brain-to-body function. Brain neuroplasticity has been associated with differences in musculoskeletal performance among athletes, however comparative real-time normal data to benchmark performance capabilities is limited.

Purpose/Design

This prospective, descriptive case series evaluated performance of task-driven activities using an innovative neurophysiological assessment technique of qEEG monitored neurophysiological responses to establish a comparative benchmark of performance capabilities in healthy, uninjured Division-I athletes.

Methods

Twenty-eight healthy uninjured females (n=11) and males (n=17) NCAA Division-I athletes participated in real-time neurophysiological assessment using a Bluetooth, wireless 21-channel dry EEG headset while performing functional activities.

Email: marshamangine@gmail.com a

Corresponding Author: Marsha Eifert-Mangine PT, ATC, EdD, CERT

Associate Professor Emeritus

Physical Therapy Program

School of Health Sciences

Mount St. Joseph University

5701 Delhi Road | Cincinnati, OH 45233-1672 United States of America

Cell: 859 802-5714

Results

Uninjured athletes experienced standard and regulated fluctuations of brain wave activity in key performance indicators of attention, workload capacity and sensorimotor rhythm (SMR) asymmetries.

Conclusion

qEEG neurophysiological real-time assessment concurrent with functional activities in uninjured, Division-I athletes may provide a performance capability benchmark. Real-time neurophysiological data can be used to monitor athletes’ preparedness to participate in sport, rehabilitation progressions, assist in development of injury prevention programs, and return to play decisions. While this paper focuses on healthy, uninjured participants, results underscore the need to discen pre-injury benchmarks.

Level of Evidence

INTRODUCTION

Injury to the musculoskeletal system perpetuates concurrent and responsive neuroplastic alteration to the central nervous system that impacts quality of function.1,2 Recent objective real-time quantitative electroencephalogram (qEEG) neurophysiological assessment techniques have been identified to monitor neural adaptive structural and functional changes of the brain that impact functional movement patterns in pre- and post-injury status.1,3 Measuring neural activity of the brain during functional tasks offers clinicians objective data to evaluate and monitor regulatory functional properties of the brain-to-body connection offering insight to assist in identification of disturbances in musculoskeletal function leading to less than optimal biomechanical utility.4 Disturbances in the neural excitability and neuroplastic properties of the brain impacts neurophysiological function of the Central Nervous System (CNS) leading to altered motor responses during functional activities.1‑4 Targeting the neuroplastic properties of the brain and CNS have become a primary goal for sports medicine professionals and athletes during both training and injury rehabilitation progressions. The ability to objectively track and monitor neurological structural and functional changes in the brain’s state that affect musculoskeletal function may allow for the optimal management of training and rehabilitation protocols. qEEG has been suggested as a metric for monitoring brain states and brain function as they relate to functional motor performance.1

Similar to functional Magnetic Resonance Imaging (fMRI) of the brain, qEEG reflects changes in the state of the brain related to workload of the different brain regions.5 However, fMRI techniques are not practically applicable for the assessment of dynamic and functional movements.1,3 In addition, the static fMRI images provide limited time windows of brain activity which limits the conclusive alterations associated with musculoskeletal function.5 qEEG offers consistent objective assessments of brain state and the ability to adapt to the changing environment.6

Assessing qEEG brain activity while performing functional movement in healthy uninjured athletes will provide

normal objective performance indicators of neurophysiological function. Such baselines can serve as real-time performance properties that assume the brain state is adequately in sequence with the peripheral neurological properties.5,6 Such performance benchmarks can be used as comparative norms to help establish standards for athlete readiness to participate in sport. Therefore, this prospective investigation evaluated neurophysiological responses to performance of task-driven activities using an innovative neurophysiological assessment technique of qEEG monitored neurophysiological responses to establish a comparative benchmark of performance capabilities in healthy, uninjured Division-I athletes. Such baseline data may be used to measure neurophysiological changes as related to degradation and/or improvement of brain state over time.

METHODS

Twenty-eight uninjured NCAA Division-I athletes qualified and consented to participate in this IRB approved prospective case series designed study. Athletes were excluded from participation if they presented with a current injury, a current history of an attention deficit, anxiety, or history of injury that resulted in disqualification from play in the prior six months. The twenty-eight athletes (10 females and 18 males) participated in a variety of competitive sports including both contact and non-contact.

NEUROPHYSIOLOGICAL ASSESSMENTS

Quantitative electroencephalography (qEEG) is a modern clinical digital assessment used to measure electrical patterns at the surface of scalp which reflect a continuous measure of cortical activity and are referred to as “brainwaves” and assess the central nervous system processing efficiency, power spectra, amplitude, and connectivity. qEEG was used to investigate real-time brain electrical patterns and neurophysiological function as it relates efficiency, power spectra, amplitude, and brain connectivity during functional movement tasks associated with sport. qEEG data were collected during a single testing session of baseline measures where each participant performed a uniform series of cognitive, motor imagery, reaction time and

Figure 1. Depiction of the planned Neurophysiological assessment tasks.

physical functional motor tasks (Figure 1). Baseline data were established by monitoring qEEG brain wave activity during periods where participants sat with eyes closed and eyes open. Once the qEEG baseline was established, participants performed a variety of tasks, including a cognitive test, overt imagery and a corresponding covert activity, functional movement exercises (balance, single limb, and agility tasks) and a reaction time test. Motor imagery was performed before and after five functional movement tasks as previously published.1,7 Functional movement tasks emphasized balance, gait, mobility and lower extremity symmetry.8‑10

1. EO/EC Visual Arrest Baseline – Participants sat in a resting state for one minute with their Eyes Closed (EC) and one minute with their Eyes Open (EO), followed by two minutes with eyes open EO and two minutes with EC. CLR AdvantageTM then compared raw EEG signals collected during EC vs EO periods to provide a neurologic baseline from which to process data collected during subsequent assessment tasks. This baseline provided analytics derived from EEG channels, including frequency band power and ratios, band and ratio topo-plots, and the performance of brain Regions of Interest (ROIs).

2. Stroop Cognitive Test – Participants viewed a 30-second series of congruent and incongruently colored words (“Blue”, “Green”, “Red”, “Yellow”) while using a PC mouse to click on particular words correctly rendered in matching colors. CLR AdvantageTM recorded the number of correct and incorrect responses to assess participants’ speed and ability to discern incongruencies. The Stroop Cognitive Test is a common method to measure psychological performance in athletes, and is used to measure speed of

processing, executive function and selective attention.

3. Positive Imagery Exercise – Participants imagined a pleasing scene or memory for 30 seconds. Positive Imagery is important to either recreate a good past performance or create a current positive new experience which can optimize performance, enhance focus and concentration, and improve self- regulation of heart rate, breath rate, and galvanic skin response.

4. Anticipation Response Exercise – Participants waited 30 seconds for a stressful audiovisual interruption after being told to expect such by investigators. The exercise is used to measure stress, arousal levels, Galvanic Skin Response, diaphragmatic breathing, and how quickly a participant can recover from a perceived stressor.

5. Covert Imagery Task A – Participants focused on a screen-centered white star then responded to a 30-second display of randomly alternating colors (green, red) by imagining tossing a ball into a basket with their right (green) or left (red) hand.

6. Overt Motor Task B – Participants focused on a screen-centered white star then responded to a 30-second display of randomly alternating colors (green, red) by actually tossing a ball into a basket with their right (red) or left (green) hand. Together, Covert Imagery and corresponding Overt Motor Tasks are used to stimulate and measure Mirror Neuron Network activation. Overt is the act of physically directing eyes to a stimulus and covert is mental shift of attention without physical movement. This indicates whether the participant learned from the covert action to better replicate movement during the overt action.

7 Unloaded Squat – Participants repetitiously (3X) squatted into a 90-degree knee flexion position while maintaining an upright torso and holding an unloaded rod overhead with arms fully extended and feet shoulder width apart in a sagittal plane. Part of the Functional Movement Screen, the Unloaded Squat is used to measure a subject’s bilateral, symmetrical functional mobility of hips, knees and ankles.

8. Single Leg Step-Down Right – Participants repetitiously (3X) stepped down from a 10" pedestal with their right leg.

9. Single Leg Step-Down Left – Participants repetitiously (3X) stepped down from a 10" pedestal with their left leg. Part of the Functional Movement Screen, the Single Leg Step Down exercises are used to measure a subject’s dynamic knee function, hip and trunk strength and biomechanical and kinematic deficiencies.

10. Single Leg Balance Right – Participants repetitiously (3X) maintained balance for 30 seconds, while raising their right leg to a perpendicular angle with a rest period of 15 seconds between each repetition.

11. Single Leg Balance Left – Participants repetitiously (3X) maintained balance for 30 seconds while raising their left leg to a perpendicular angle with a rest period of 15 seconds between each repetition. Single Leg Balance tasks were initiated with the nonweightbearing leg flexed to approximately 30 degrees from a hands-on-hips position. Part of the Functional Movement Screen, the Single Leg Balance tasks are used to measure a subject’s balance, joint stability and proprioception.

12. Sidestep Right – Participants repetitiously (3X) led with their right leg to step over a set of three 6" low hurdles before stepping back to the starting position.

13. Sidestep Left – Participants repetitiously (3X) led with their left leg to step over a set of three 6" low hurdles before stepping back to the starting position. Part of the Functional Movement Screen, the Sidestep tasks are used to measure a subject’s gait mechanics, compensation and asymmetry

14. Single Leg Squat Right – Participants repetitiously (3X) maintained balance for 30 seconds while squatting from a hands-on-hip position to a 90-degree knee flexion angle on their right leg with the left leg extended.

15. Single Leg Squat Left – Participants repetitiously (3X) maintained balance for 30 seconds while squatting from a hands-on-hip position to a 90-degree knee flexion angle on their left leg with the right leg extended. Part of the Functional Movement Screen, the Single Leg Squat tasks are used to measure a subject’s balance and control, strength of lower body, postural malalignments and kinematic and biomechanical deficiencies.

16. Reaction Time – Participants focused on a screencentered white star then responded to a 30-second display of randomly alternating colors (green, red) by

clicking a PC keyboard with their right (red) or left (red) index finger. CLR AdvantageTM recorded the speed and accuracy of responses. This Reaction Time Test is a common method to measure responsiveness in athletes

Cognitive tasks, including a Stroop Test, Positive Imagery Exercise, and Anticipation Challenge were designed to stimulate and measure cognitive functions. The Covert Imagery Task and companion Overt Motor Task were designed to stimulate and measure Mirror Neuron Network (MNN) activation. MNN is a critical component of the brain’s social cognitive function in action recognition, imitation, learning, and understanding the intentions and observations behind others’ actions. These neurons are excited during incidences when an individual performs or observes a motor skill which stimulates exclusive motor functions. Nine physical tasks including: an unloaded squat; single leg step down (right and left); single leg balance (right and left); sidestep right, sidestep left; and single leg squat (right and left), as well as a scored Reaction Test, were designed to stimulate Mirror Neuron Network activity while measuring regional connectivity and hemispherical asymmetry These tasks also enabled measurement of attention levels and workload capabilities.11,12

NEUROPHYSIOLOGICAL ASSESSMENT PLATFORM

Investigators utilized a CGX9 (Cognionics Company, San Diego CA) Quick-20r v2, 21-channel dry EEG head set to collect continuous electrical brain activity while simultaneously completing the the functional movements. Chi, et al.7 found this system to be a reliable and valid method to measure evoked response potentials as repeatable signals were seen when a standardized test protocol approach is used as compared to traditional wet, wired EEG systems. The dependent variables of cognitive function, attention, workload capability, and Sensorimotor Rhythm (SMR) asymmetries were monitored.1,12 Each measure accounted for acute real-time neurophysiological compensation and accommodations to physical and cognitive tasks.13,14 Additional physiological measures were conducted as secondary dependent variables to examine participants’ physical performance during each Neurophysiological Assessment Task. These measures included: heart rate to examine stress, anxiety and ability to relax15; heart rate variability to examine the ability regulate emotion, attention and breathing16; respiration rate to examine stress, concentration and ability to minimize distraction17; trapezius muscle tension to examine asymmetry and injury predisposition18; galvanic skin response to examine fatigue, emotional arousal and anticipation19; and peripheral temperature to examine the participant’s ability to regulate stress response.20 Physiometric data was collected with the CGX AIMTM (CGX, a Cognionics Company, San Diego CA) physiological device. The CLR AdvantageTM (CLR Neurosthenics® Manhattan Beach, CA) Neurophysiological Assessment Platform and the CGXAIM were utilized to simultaneously collect, process and analyze neurophysiological data from the brain and physiological monitoring through electrical data from

Figure 2. Data collection and output process steps

1. Selection of tasks from a remote assessment screen during data collection

2. Performance of physical task (in this case, the single leg squat) with visual cues and instructions for participants displayed on a separate screen

3. Output of analytic reports of EEG data representing asymmetry of Mirror Neuron Network Regions of Interests (ROIs)

the body. The CGX devices were then used to stream continuous biometric data via wireless connection to CLR Advantage. This configuration allowed participants to perform various physical tasks without restriction. After confirming the quality and consistency of CGX signal data, CLR Advantage was used to guide participants through the series of preprogrammed neurophysiologic assessment tasks. As investigators selected each task from a remote assessment screen (Figure 2, Step 1), CLR Advantage would display corresponding visual cues and instructions for participants to follow on a separate screen (Figure2, Step 2). Upon completion of each assessment, CLR Advantage would utilize Intheon NeuroscaleTM to generate analytic reports for each participant (Figure2, Step 3). CLR Advantage was also used to collect preassessment profile and medical history data from each participant.1

The EEG and physiologic data screen were designed to capture the most relevant and incisive athletic performance metrics. With 21 channels of continuously streaming EEG, investigators were able to collect data to determine participants’ neural network connectivity, activation, asymmetry and frequency bands levels during each neurophysiological assessment task. The data collected supported sufficient Power Spectral Density (PSD) levels to measure performance across multiple networks and regions of interest including: a) Default Mode Network (medial prefrontal cortex, posterior cingulate cortex, Hippocampus, precuneus, inferior parietal lobe, parietal regions and temporal lobe); b) Salience Network (anterior insula and dorsal anterior cingulate cortex); c) Mirror Neuron Network (inferior frontal cortex and in the inferior parietal cortex, d) Attention (dorsal frontoparietal); e) Sensorimotor Cortex (primary somatosensory cortical area and the primary motor

cortical area); and, f) Occipital Lobe (visual processing center ). PSD levels also provided sufficient data to calculate performance within EEG frequency bands, Including: g) Delta (0.5 to 4Hz); h) Theta (4 to 7Hz); i) Alpha (8 to 12Hz); j) SMR(12 to 15Hz); and k) Beta1-3 (12 to 30Hz

Power spectral analysis (PSA) is a common and wellestablished method for analyzing EEG signals.19 PSA uses a power spectrum to quantify the amplitude of each frequency component in the EEG waveform. PSA estimates the power of a signal at different frequencies.

Spectral analysis comparison between power and frequency bands was measured at the change between Eyes Open (EO) and Eyes Closed (EC). The Welsh20 method was used for spectral density estimation and used for estimating the power spectral density analysis and then used 1/frequency (F) normalization to convert to decibels. The raw EEG compared EO versus EC during resting states and analytics based on measurements per channel, across all channels, right and left hand as well as different brain regions, frequency bands, frequency band ratios and Regions of Interest (ROI). Figure 3 represents a sample Power Spectral Density (PSD) assessment of a male participant.

Upon completion of each participant assessment session, collected data was further processed to calculate individual performance metrics, data aggregation, exponential smoothing (by task) and generation of sub-cohort (uninjured, male/female) analytics. The CLR Advantage Neurophysiological Assessment Platform was utilized to analyze participants’ Individual Performance Reports (IPRs) then compare those results to that of the study sub-cohort (uninjured male and female athletes). IPRs may be used to identify neurophysiological deficiencies and provide clinically valuable information to the rehabilitation specialists,

Figure 3. Power Spectral Density (PSD) Example

This example was captured from a male participant during the Visual Arrest portion of the qEEG Baseline Neurophysiologic Assessment Task. Each trace (separate color line) represents one of the 19 EEG channels of the regions of interest measured as an electrical frequency of brain activity Each trace shows Mean +/- 95% confidence intervals.

Figure 4. Examples of athletes performing physical and cognitive tasks during data collection.

coach, or athlete themselves about how the reacts and accommodates based on the demands of their sport and/or position. Four reports generated include:

1. Pre vs Post Motor Training Task Report provides results from the cognitive metrics as a comparison from motor imagery baseline periods before (pre) and after (post) the motor training tasks. The report includes: SMR Asymmetry (the average S MR (13-15 Hz) Asymmetry for the Mirror Neuron Network Regions of Interest (ROIs) averaged together and computed from

Figure 5. Graphic depiction of data collection methods

The figure on the left depicts EEG electrode sensor placement. The center and right figures depict physiologic data collection points including:

• ECG Paired Electrocardiagraph (ECG) electrodes (Output:Heart Rate BPM, Heart Rate Variability ms/BPM, Respiration BRPM)

• Peripheral Temperature (Temp) sensor (C0 , F0) positioned on the inner bicep as shown to allow free movement by participants’ hands

• Paired Galvanic Skin Response (GSR) electrodes (ms), positioned on the forearm as shown to allow free movement of participants’ hands

• Paired Electromyography (EMG) electrodes positioned as shown to measure Trapezius muscle activity with ground (Grnd) (Output: Left, Right Trapezoid mV, Trapezoidal Imbalance ms).

the motor imagery periods before and after the motor training tasks); Analysis by Channels (analyses and statistics for all channels with power spectral analysis plots for pre motor imagery vs post motor task); Analysis by Sources (analyses and statistics using Regions of Interests (ROIs) as determined by source localization); Cortex Activity (plots showing the difference in pre vs post motor imagery task frequency band powers as T-scores computed for all ROIs, by each hand, and mapped onto a 3D cortex [Figure 6]).

2. Pre vs Post Mirror Neuron Network Connectivity Report provides Connectivity Analyses (MNN Network), including connectogram plots21 (visual representations of neural connections in the brain) showing Pre vs Post (motor imagery) differences in effective connectivity (a multivariate Granger Causaliy22 measure) between selected cortical regions of interest following standardized Low Resolution Electromagnetic Tomography23 sLORETA source localization.

3. Motor Training Task Session Report provides Cognitive Metrics (showing the average Attention and Workload metrics computed across the entire session); SMR Asymmetry Over Time (showing the average SMR [13-15 Hz] Asymmetry for the Mirror Neuron Network ROIs averaged together over time); and Power Bands (with line plots of the frequency band powers (dB) for all channels across the entire session).

4. Individual Session Visual Arrest Report provides: Analysis by Channels (with Power Spectra Channels,

BandPower Channels, BandPower Bands / Ratio Topoplots); and Analysis by Sources (with Power Spectra Sources, BandPower Sources, BandPowerRatio Cortex Plots).

RESULTS

The mean age of participants was 19.37 ± 1 years (females 19.8 years; males 19.1 years); height = 176.75cm ± 8.05 cm (females 167cm; males 186cm); weight = 79.38 ± 14.36 kg females 67kg; males 84kg). (Figure 7)

Analysis of the qEEG data of the male and female athletes in this case series demonstrated asymmetries during motor strategies during the step down left, single leg squat and the unloaded squat. Females performed better in the single leg squat and unloaded squat while males performed better on the step-down landing left task. These findings were also supported by the SMR Cortex plots. These cortex plots illustrate characteristics for both male and female, regions of interest, frequency bands of the EEG and network activation during assessment of motor tasks that emphasize balance, gait, mobility and lower extremity symmetry. (Figure 8)

ATTENTION METRIC

The Attention metric indicates the ability to maintain goaldirected behavior in the face of distractions. The metric composites were measured during the performance of the functional movement tasks, covert and overt imagery, and

Figure 6. Sample cortex plots in the Pre vs Post Motor Training Task Report generated for a male participant.

Visualizations illustrate the difference in Pre and Post Motor Imagery Task frequency band powers as T-scores (masked for significant values only) computed for all ROIs, by each hand, and mapped onto a 3D cortex. Positive (yellow to red) values represent hyperactivity, where negative values (green to violet) represent hypoactivity

The leftmost column shows the entire cortex, while the middle and right images independently represent the two hemispheres of the cortex.

Figure 7. Subject demographic and sport participation data, including a summary of contact versus non-contact athletic participation.

cognitive tasks. The attention metric is calculated utilizing frequency band ratios of frontal theta and beta/alpha. Attention increased consistently for both females and males until the single leg balance task as represented in Figure 9

BRAIN WORKLOAD METRIC

Brain workload is related to the brain region(s) of interest engaged through electrical connections during the performance of tasks being performed. The workload metric in-

Figure 8. Represents SMR Asymmetry data (depicted above in decibels (db)

This figure illustrates the average SMR Asymmetry for the Mirror Neuron Network Regions of Interests (ROI’s). Data compare the motor imagery periods before and after the motor imagery tasks.

Figure 9. The ability to maintain goal-directed behavior in the face of distractions indicating attention during performance tasks.

This composite of brain activity results (measured in db) of all male participants versus all female participants was measured during the performance of the functional movement tasks, covert and overt imagery tasks, and cognitive tasks.

dicates how the brain responds to the activities being engaged. Results from previous studies have shown that there is a significant difference between men and women in terms of brain workload capability.24 Figure 10 indicates the brain

workload metric by task for both females and males. Females’ cognitive workload capability was higher than males beginning at the initial baseline task. Monitoring brain workload in tandem with other key components, such as,

Figure

10. Depiction of Brain Workload (measured in db)

This depicts the cognitive ability to interact with complex environments in a goal-directed manner The metric composite results of all male participants versus all female participants measured during the performance of functional movement tasks, covert and overt imagery and cognitive tasks.

attention and focus provide insight as to the effect certain tasks may tax the brain state.

PRE- AND POST-MOTOR TASK SMR ASYMMETRY

Resting state utilized a spectral analysis comparison between power and frequency bands measuring the delta between EO and EC. The EEG cortex plots illustrate characteristics of various networks for both males and females, and activity in both left and right hemispheres during select functional movement tasks. The EEG cortex plots demonstrate longitudinal EEG for the initial brain map baseline, cognitive tasks, motor tasks and mental imagery Females exhibited more symmetrical pre- and post- motor task. (Figure 11)

DISCUSSION

The primary objective of this case series was to utilize neurophysiologic assessment data, including brain hemisphere asymmetry, attention levels, and brain workload analytics to quantify performance outcomes in healthy, uninjured athletes during functional movements.1,12 The results demonstrate variances in functional tasks between uninjured Division-I athletes (males and female) in key performance indicators of cognitive function, attention, brain workload capability and SMR asymmetry were observed. Musculoskeletal biomechanical asymmetries or disfunction have been previously reported to be associated with variations in muscle and brain symmetry between left and right hemispheres.25 The reported data affords a visual representation of neurophysiological performance observed dur-

ing with qEEG monitoring during performance of task driven assessments. This provides researchers and clinicians alike with a possible mechanism to explore neural behaviors, brain symmetries, and brain state regulation associated with normal movements.

Current applications in rehabilitation have increasingly embraced the concept of neural-oriented rehabilitation methods to facilitate neuroplastic adaptation. The brain has multiple cell types that divide and grow, thus developing new connections throughout a lifespan.26 Plasticity is a hallmark of the adaptability of the brain to remodel, adapt, and repair the central nervous system as a result of purposeful interventions using environmental modifications and brain exercises to stimulate neurofeedback improvements.27,28 In a similar fashion, neurological assessments provide insight into the functioning properties of the neural brain-to-body connection.

Sports medicine professionals are familiar with the concept that skeletal muscle cells do not divide with conditioning, but brain cells can divide and precipitate plasticity 26 It is incumbent upon the rehabilitation specialist to be cognizant of the role of the brain’s adaptability and changes that are seen in the pre- and post-injury periods. Dysregulation and rebuilding of neural networks during functional development and during the rehabilitation process are the hallmarks of neuroplasticity. Mangine et al.1 used high fidelity real-time qEEG and physiometric monitoring software to demonstrate simultaneous linear improvements in neurophysiological and musculoskeletal performance in a case report of an athlete after anterior cruciate ligament reconstruction and rehabilitation during a return to play progression. Although in a single subject, these findings sug-

Figure 11. Depicts Pre/Post-motor task SMR asymmetry between female and male athletes measured in decibels. Females exhibited less left to right asymmetry than males in pre/post Motor Task SMR Asymmetry Analysis than males pre/post Motor Task Asymmetry

gest changes in the brain’s neuroplastic properties impact musculoskeletal function.1 Thus, clinicians should seek to objectively evaluate brain state during functional training and/or rehabilitation progressions.

Division I athletes possess elite levels of human performance capabilities in strength, agility, balance, reaction time and focus.24 Until recently, measuring these capabilities was largely limited to sport statistics, kinematic observation (time trials, jumping distance, etc.)24 and various strength assessments (bench press, leg press, etc.).29 Over time, the proliferation of sports related injuries has warranted investigations into the role the of the brain-to-body connection30 in athletic performance, including both psychological factors31,32 and neurological function.33

There is a need for methods to support assessment of facets of neuroplasticity as part of functional rehabilitation and the development of athletic skills. The current case series provides information gained from neurophysiologic assessment that demonstrates a foundation utilizing analytics from task-driven exercises to evaluate and benchmark athletic performance capabilities and may assist optimize rehabilitation outcomes within the sports medicine field.

Embracing rehabilitation interventions designed to optimize brain and body performance seems ideal for monitoring athlete preparedness in both clinical rehabilitation and sports performance. Recent findings1 have reported dysregulation in qEEG brain mapping occurs following anterior-cruciate injury and/or reconstruction. Mangine et al.1 demonstrated a functional correction in brain state regulation to be related to improved neurophysiological outcomes, such as, reaction time and task completion during a rehabilitative return to play process following an anterior cruciate ligament repair in a single subject. A dysregulated

brain state appears to disrupt neuroprocessing necessary to maintain biomechanical and functional stability associated with sport performance and injury prevention mechanics.7, 33 Future studies could utilize neurophysiological baseline data and progressive assessment information to aid in decision making concerning management and rehabilitation of the injured athlete** **

This case series is a first requisite step in building a body of evidence connecting physical activities and brain functional responses among healthy athletes. Using a combination of qEEG, physiometrics, psychometric, and kinematic applications to monitor change in neurophysiological performance post musculoskeletal injury seems warranted but requires more specialized targeted programs for behaviors associated with brain process for motor control, skill development, and biomechanical sport functions. Future studies should investigate the use of neurophysiological assessments to help determine brain regulatory status and functional readiness to return to athletic participation. Additionally, advanced understanding of brain activity to coordinate neuromuscular function during sports participation may assist sports medicine professionals in examining strategies to mitigate injuries.

LIMITATIONS

The neurophysiologic assessments were performed on healthy non-fatigued, uninjured Division 1 athletes using musculoskeletal movements associated with sport and rehabilitation. Fatigue factors have been shown to have a relationship with functional performance34 and were not accounted for in this case series. qEEG data were not collected during actual sport participation, so maximal strength and

maximal speed likely not reached by each participant. The task driven activities were limited to controlled movements requiring the brain and body functioning together supporting clean analytics by limiting extraneous EEG “noise” during data collection. Notwithstanding, outcome measures from the current study are unique in combining qEEG, physiometric, and physical movements** **

CONCLUSIONS

The data collected in this case series supports the potential use of the combination of qEEG and physiometric data as a novel neurophysiological real-time measurement to serve as a clinical assessment for establishing comparative baseline normative data for athlete performance. In addition to the unique utility of qEEG and neurophysiologic as an as-

sessment for baseline data, qEEG assessment could provide meaningful data to support clinical decision making and clinical intervention choices. Performing qEEG assessments in tandem with functional movements may allow clinicians to gain insight into the athlete’s potential readiness for participation and safe return to play, related to brain health and neurophysiological function. The authors hope that this work will be to empower sports medical professionals to consider quantitative information concerning the brain’s role in motor function as it relates to motor performance and rehabilitation in athletic or functionally active populations.

Submitted: July 23, 2024 CDT, Accepted: September 25, 2024 CDT

The Author(s)

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24. Rentz LE, Brandmeir CL, Rawls BG, Galster SM. Reactive task performance under varying loads in Division I collegiate soccer athletes. Front Sports Act Living 2021;3:707910. doi:10.3389/fspor.2021.707910

25. Olajos AA, Takeda M, Dobay B, Radak Z, Koltai E. Freestyle gymnastic exercise can be used to assess complex coordination in a variety of sports. J Exerc Sci Fit 2020;18(2):47-56. doi:10.1016/ j.jesf.2019.11.00

26. Power JD, Schlaggar BL. Neural plasticity across the lifespan. Wiley Interdiscip Rev Dev Biol 2017;6(1). doi:10.1002/wdev.216

27 Tassani S, Font-Llagunes JM, Gonzalez-Ballester MA, Noailly J. Muscular tension significant affects stability in standing posture. Gait Posture 2019;68:220-226. doi:10.1016/j.gaitpost.2018.11.034

28. Kumar J, Patel T, Sugandh F, et al. Innovative approaches and therapies to enhance neuroplasticity and promote recovery in patients with neurological disorders: a narrative review. Cureus. 2023;15(7):e41914. doi:10.7759/cureus.41914

29. McGuine TA, Post EG, Herzel SJ, Brooks MA, Trigsted S, Bell DR. A prospective study on the effect of sport specialization on lower extremity injury rates in high school athletes. Am J Sports Med 2017;45(12):2706-2712. doi:10.1177/ 0363546517710213

30. Spreng RN, Stevens WD, Chamberlain JP, Gilmore AW, Schacter DL. Default network activity, coupled with the frontoparietal control network, supports goal-directed cognition. Neuroimage 2010;53(1):303317. doi:10.1016/ j.neuroimage.2010.06.016

31. Junge A. The influence of psychological factors on sports injuries. Review of the literature. Am J Sports Med 2000;28(5 Suppl):S10-S15. doi:10.1177/ 28.suppl_5.s-10

32. Webster KE, Feller JA. Psychological readiness to return to sport after anterior cruciate ligament reconstruction in the adolescent athlete. J Athl Train 2022;57(9-10):955-960. doi:10.4085/ 1062-6050-0543.21

33. Grooms DR, Page S, Onate JA. Brain activation for knee movement measured days before second anterior cruciate ligament injury: Neuroimaging in musculoskeletal medicine. J Athl Train 2015;50(10):1005-1010. doi:10.4085/ 1062-6050-50-10-02

34. Verschueren J, Tassignon B, De Pauw K, et al. Does acute fatigue negatively affect intrinsic risk factors of the lower extremity injury risk profile? A systematic and critical review Sports Med 2020;50(4):767-784. doi:10.1007/s40279-019-01235-1

Neurocognitive and Neuromuscular Rehabilitation

Techniques after ACL

Injury, Part 1: Optimizing Recovery in the Acute Post-Operative Phase- A Clinical Commentary

Kevin E. Wilk, PT, DPT, FAPTA1,2a , Morgan Ivey, PT, DPT, SCS3 , Zachary M. Thomas, PT, DPT, OCS, SCS, CSCS4,5 , Lewis Lupowitz, PT, DPT, SCS, CSCS6 1 Champion Sports Medicine, Select Medical, 2 Director of Rehabilitative Research, American Sports Medicine Institute, 3 Sports Physical Therapist, Sports Medicine Fellow, Champion Sports Medicine, 4 Sports Physical Therapist, University of Georgia, 5 Piedmont Orthopedics & Sports Medicine, 6 Sports Physical Therapist, Northwell Health

Keywords: Anterior cruciate ligament reconstruction, neurocognitive training, neuroplasticity, proprioception, motor control https://doi.org/10.26603/001c.124945

International Journal of Sports Physical Therapy

Anterior cruciate ligament (ACL) injury rates are on the rise, despite improved surgical techniques and prevention programs. While traditional rehabilitation emphasizes the restoration of motion, strength, and physical performance, emerging research highlights the importance of addressing neurocognitive deficits that can persist after injury. These deficits, including altered proprioception, impaired motor control and muscle recruitment, as well as heightened reliance on visual feedback, can significantly increase the risk of re-injury and impede return to sport. The purpose of this clinical commentary is to outline a proposed comprehensive approach to rehabilitation that challenges the neurocognitive system to optimize rehabilitation outcomes and reduce reinjury risk. Thus, this clinical commentary discusses the rationale for integrating neurocognitive training into all phases of ACLR rehabilitation, from initial injury to eight weeks post-surgery. It details the neurophysiological changes caused by ACL injury and presents evidence supporting the use of exercises that challenge visual attention, decision-making, and motor planning. A comprehensive rehabilitation framework incorporating both physical and neurocognitive components is proposed, aiming to improve long-term outcomes and reduce re-injury risk.

Level of Evidence: 5

INTRODUCTION

Each year, an estimated 300,000 ACL injuries occur annually in the United States, resulting in about 225,000 to 250,000 surgeries.1 Approximately 70% of ACL injuries occur from a non-contact mechanism, such as running and pivoting, cutting, or landing from a jump.2‑4 Unfortunately, between 10 and 25% of individuals will sustain a second ACL injury.5‑7

Female athletes in sports like soccer, basketball, and volleyball, as well as gymnasts, and male football players, face a heightened risk of injury. These injuries are often triggered by unanticipated or decelerating movements, and the injury that is sustained disrupts the body’s normal sensory input and motor control, leading to neuroplastic changes in the brain.8 Research has shown that these changes can

manifest as decreased reaction times, processing speeds, and proprioception, further contributing to the risk of injury.9‑13

NEUROPLASTICITY AND ACL INJURY

Neuroplasticity, the brain’s ability to form new neural connections, plays a crucial role in recovery from ACL injury. This process can involve modification of cognitive strategies, recruitment of new and different neural networks (neural patterning), or adjusting the strength of existing connections in brain areas in charge of carrying out particular tasks.14 Neuroplasticity can be both beneficial and deleterious. While positive effects can enhance motor control, negative effects can lead to inefficient and compensatory movement patterns.14 This central nervous system

Corresponding Author: Kevin Wilk

200 Montgomery Hwy, Suite 150 Birmingham, AL, 35216 kwilkpt@hotmail.com

re-wiring combined with biomechanical alterations in loading strategies could explain the reason some ACL patients are unable to recruit their quadriceps muscle leading to a quadriceps avoidance gait. As Wexler et al. describe, this maladaptation or negative neuroplastic change involves walking with a slightly flexed knee, marked by overactive hamstring musculature and inhibited quadriceps.15 If not corrected, this could lead to a delay in the return of quadriceps muscle strength, and poorer knee function.

Neuroplastic changes that occur following ACL injury are likely due to altered afferent input which affects the efferent output. The alteration of afferent input is often a result of a loss of somatosensory signal from the ruptured ligament and increased nociceptor activity associated with pain, swelling, and inflammation.11 The altered efferent output leads to a disruption in gamma-motor neuron feedback loops,16 delayed long latency reflexes,17 and altered spinal excitability.18 Therefore, increased cortical excitability is required to generate a muscle contraction after ACLR.19,20 This mechanism results in the shift from what used to be a feedforward or semi-automatic movement, to movements that now require increased volitional control. Grooms et al. demonstrated this paradigm utilizing fMRI with individuals following ACLR, finding that ACLR patients demonstrated increased cortical drive, visual dependency, and decreased neuromuscular control compared to controls during a simple supine knee extension exercise triggered by a visual prompt.10

Often, the regions of the brain most affected following ACL injury are those involved in visual and cognitive function.21 This results in an overreliance on visual processing/ feedback and motor planning to maintain neuromuscular control and dynamic stabilization of the knee. Baumeister et al, utilizing electroencephalography, demonstrated that individuals following ACLR had greater brain activation in attention and sensory areas, however this did not correlate to improvements in proprioceptive performance.22 They concluded that the increased activation may be attributed to decreased efficiency and/or increased excitability required to complete the same task. Each of these studies highlight the complexity of neuroplastic changes that occur after ACL injury, therefore it is important to address these factors in rehabilitation.

NEUROCOGNITIVE REHABILITATION: A COMPREHENSIVE APPROACH

Given the prevalence of non-contact, unanticipated injuries and their impact on the brain, the authors suggest implementing early neurocognitive training into ACL rehabilitation immediately following injury and/or surgery This approach aims to improve neuromuscular control and dynamic stabilization, with the ultimate goal of reducing reinjury risk.

Neurocognitive rehabilitation can be thought of as any task that occupies the patient/athlete’s attention through visual, mental, auditory, verbal and/or kinesthetic stimuli, while simultaneously performing a movement, task, exercise, or skill.12 As the patient demonstrates more automatic

control with decreased response time and proper mechanics, the complexity of the task is increased. The neurocognitive variables could include the following: speed, dual tasking, verbal, visual tracking, perturbations, directions, obstacles, and surfaces.

Traditional ACLR rehabilitation often focuses on physical aspects such as limb symmetry, range of motion, and strength, with less emphasis on neuromuscular and neurocognitive adaptations. Additionally, there is a reliance on an internal focus of control (i.e. “ squeeze your quad”, “don’t let your knee go in” or “bend your knee”) as opposed to an external control (i.e. responding to a visual stimulus, hitting a target or catching a ball). While this may be necessary in the early stages for focusing attention to complete activation of specific muscles, it doesn’t fully prepare athletes for the dynamic and reactive environment of their sport. Internal focus can overload cognitive resources, leading to decreased neuromuscular control during complex tasks. Shifting towards an external focus, where athletes respond to environmental stimuli, promotes more automatic movements and better prepares them for the demands of their sport.

PRINCIPLES OF NEUROCOGNITIVE REHABILITATION

Sports are filled with neurocognitive challenges that expand far beyond just the physical demands placed on an individual. Chaput et al. explain that visual-cognitive processes in sport require components of both divided and selective visual attention.21 Divided attention is described as the ability to simultaneously provide attention to or switch between multiple stimuli (i.e. dual tasking). Divided attention can further be described by the limited or multiple resource theory 23,24 When both stimuli rely on the same sense, such as auditory, they become competitive in nature (limited resource theory) versus when two stimuli affect different senses, such as vision and auditory, it is easier to multi-task (multiple resource theory). Selective attention is being able to ignore irrelevant stimuli to focus on a singular task which can occur by volitional control (topdown) or reactionary due to an un-anticipatory event (bottom-up). It has been mentioned that neurocognitive challenges for athletes do not have to be sport specific if they challenge the same underlying neurocognitive demands of sport (i.e. working memory, rapid decision making, visual processing, or postural perturbations).12,21

With increased task complexity, neuromuscular control deteriorates in those following ACLR as compared to healthy controls, possibly due to an overload of the motor planning resources.11 Sherman et al. found that individuals had greater cortical inhibition and committed more decision accuracy errors to maintain reaction time following ACLR, compared to healthy controls during a Go/No Go task stimulated by a visual target.25 Recently Chaput et al.21 have described implementing the Visual-Cognitive Control Chaos Continuum (VC-CCC) within ACLR rehabilitation which is an expansion from the original Control Chaos Continuum described by Taberner et al.26 In the VC-CCC, the

authors proposed a five-phase progression beginning at high control and stability and ending at a high chaotic environment mimicking the visual cognitive demands of sport. As task complexity increases, if performance is errorless then the challenge may not be difficult enough to elicit learning.27

In the authors’ experience, a comprehensive approach that includes neurocognitive training is necessary to address neuroplasticity changes affecting proprioception and motor control deficits post-ACLR. The senior author has found that incorporating a combination of neuromuscular and neurocognitive training has led to significantly improved outcomes for ACL patients. Therefore, the purpose of this clinical commentary is to outline a proposed comprehensive approach to rehabilitation that challenges the neurocognitive system to optimize rehabilitation outcomes and reduce reinjury risk.

ACL REHABILITATION AND THE INCLUSION OF NEUROCOGNITIVE STRATEGIES

It is imperative to include exercises that address these deficits both immediately after injury and throughout the continuum of care to prevent the deleterious effects of neuroplasticity. Performing a motor task while altering visual input through external factors (e.g., blindfolds/goggles, targets, balls, defenders, visual signals) has been shown to negatively impact neuromuscular control in ACLR patients compared to performing motor tasks alone.20 In addition, vibration can positively impact efferent motor output by enhancing muscle activation and proprioception.28,29 Moreover, many studies indicate no difference at one and two-year follow up with the addition of neuromuscular training alone,28,29 indicating the need for a cognitive component to be included during the exercise. Finally, deficits in both unilateral and contralateral limb proprioception and neuromuscular control30 exist after injury; thus it is important to include education and training for the entire neurocognitive system. The authors’ detailed program including variables and progressions is outlined in Table 1

PRE-OPERATIVE PHASE

The pre-operative phase of ACL reconstruction is crucial for preparing the patient physically and mentally for surgery and subsequent rehabilitation and is ideally incorporated immediately following injury The primary goals during this phase include reducing inflammation and pain to achieve a “quiet knee” prior to surgery, normalizing ROM (especially extension and flexion), quadriceps muscle activation, preventing significant quadriceps atrophy, and normalizing gait. A critical component of this phase is the incorporation of neurocognitive exercises to decrease early motor compensations and quadriceps muscle inhibition. The specific exercises are recommended as soon as possible.

Motor and cognitive dual-tasking exercises are implemented, where patients perform functional and cognitive tasks simultaneously This approach promotes agonist/an-

tagonist muscle coactivation while stimulating brain centers responsible for motor planning and proprioception.20 Patients who initiate gait training early have been shown to have decreased compensations and increased functional outcomes compared to those who initiate gait training later in rehab.31 Gait training drills such as stepping over cones is initiated to develop symmetry between the lower extremities. Symmetrical hip, knee, and ankle flexion over the cone, quadriceps and hip control during weight acceptance, gastroc/soleus symmetry during push-off, and equal stance time between limbs are all vital components in this exercise. This drill is progressed to tax the neurocognitive system by performing at various speeds, in multiple directions (forward, backward, lateral), (Figure 1a, 1b) adding serial counting/memory recall drills, ball tossing/catching, or using strobe goggles.

Additional exercises include squats on a tilt board while throwing/catching a ball or balancing on an unstable surface while catching a randomly colored stick and reacting to the correct color. These exercises target balance, reaction time, and visual processing. Furthermore, active joint repositioning drills can be performed with eyes closed to enhance proprioception. These early intervention drills are designed to minimize and prevent negative neuroplastic adaptations. Consistent implementation of these exercises prior to surgery is crucial to optimize beneficial neuroplastic changes and prevent maladaptive patterns.

IMMEDIATE POST-OPERATIVE PHASE (DAYS 1-7)

The immediate post-operative phase echoes the goals of the pre-operative phase and focuses on achieving a “quiet knee” quickly to facilitate early quadriceps activation, protect the surgical graft, and aid in regaining extension ROM. From day one, quadriceps activation exercises are implemented using neuromuscular electrical stimulation (NMES) and, for those with difficulty in efferent firing, electromyographic (EMG) visual biofeedback devices. These techniques attempt to override quadriceps inhibition by increasing action potentials in motor units (NMES)32 or enhancing real time visual feedback (EMG), allowing patients to adjust their muscle activation patterns during exercise. A limitation of using NMES alone is that, while many patients experience improved quadriceps contraction during individual sessions, it does not directly improve knee extensor strength. Additionally, there is often minimal carryover (voluntary control) to the next session, indicating limited beneficial neuroplasticity Grooms et al. found that increased demands on the central nervous system during complex, high-stakes activities can override normal efferent inhibition mechanisms.11 To accomplish this, the authors advocate for the use of exercises such as quad sets (QS), straight leg raises (SLR), and knee extensions from 90-40 degrees with NMES to assist patients in quadriceps activation. These can be also performed with the patient visualizing EMG data for biofeedback to improve contraction or combined with a reactive cognitivemotor task, such as performing a QS while throwing/catch-

Table

Exercise/Drill Variables/ progressions to enhance neuroplasticity

Quad sets

Straight leg raises (3 way)

Knee extensions (90-40 deg)

Mini squats Standing TKEs

NMES EMG biofeedback

Reactive cognitive motor task (BlazePods)

Surface (i.e. foam, rocker board)

Resistance

Dual task (i.e ball toss or HecoStix)

Reactive cognitive motor task (BlazePods, Neurocognitive Sensory station)

Perturbations

Cognitive task (counting, memory, etc.)

Altered vision Contralateral limb/ UE task

Gait/stepping drills:

Weight shifts

Cone stepping

Lateral lunges

Lateral stepping (slides)

Quick Board stepping drills

CKC neuromuscular exercises:

Anterior/ lateral step

downs

Multidirectional lunges

Speed Direction (ant/ post/lateral)

Dual task (i.e ball toss or HecoStix)

Cognitive task (counting, memory, etc.)

Reactive cognitivemotor task

Resistance Surface

Dual task (i.e ball toss or HecoStix)

Perturbation/ resistance from CLX band

Cognitive task (counting, memory, etc.)

Reactive cognitive motor task (BlazePods)

Resistance Surface

Single leg balance:

SL RDL with UE task

SL balance with band perturbations

Dual task (i.e. ball toss)

Direction (star drill on floor)

Visual targets

Perturbation (KB exchange/ resistance band)

UE task (i.e cable row, med ball chop, reach)

Dynamic shuffling Speed Direction

Neurocognitive Demand

Visual Cognitive Efferent firing

Cognitive Dual task

External focus of control Reaction time

Examples:

Quad set with NMES

Straight leg raises while using UE to react to indicated BlazePod color

Knee extensions using visual EMG biofeedback Virtual Reality Glasses

Mini squats on rocker board with external perturbations while throwing/catching a ball

Standing TKE while using UE to react to indicated quickboard target

Visual Cognitive Decision making

Memory

Dual task

External focus of control Reaction time

Visual Cognitive Decision making

Memory

Dual task

External focus of control

Reaction time

Visual Cognitive Decision making

Memory

Dual task

External focus of control Reaction time

Weight shifts on force plates with visual feedback

Multi-directional cone stepping counting backward by 7’s and tossing HecoStix

Lateral lunges with sport cord perturbation and ball toss, landing on foam surface

Lateral slides with resistance band around knees, reacting to verbal cues (direction, speed) and catching ball

Rapid stepping in place with visual target, reacting to correct location on the board or surface (Quickboard)

Anterior step down from box with CLX band pulling into femoral IR and dynamic LE valgus (figure 8)

Lateral lunges with sport cord perturbation and ball toss toward indicated direction. Athlete must react to indicated direction using light up pods (i.e. antero-lateral or posterolateral)

Visual Cognitive Decision making

Memory

Dual task

External focus of control Reaction time

Cognitive

SL RDL standing on foam while catching a ball and performing RDL to the indicated cone (5 cones set up in front of the patient)

Single-leg balance with band resistance and valgus perturbations: The patient stands on a rocker board while resisting external forces, dribbling a basketball, and catching Hecostix with contralateral UE (figure 9)

Visual

Lateral Shuffles with BlazePod and Sport Specific Ball Catching (figure 11)

Exercise/Drill Variables/ progressions to enhance neuroplasticity

Visual targets (with/without distraction targets)

Auditory cues (i.e direction/speed)

Height/location of target

Sport specific task (i.e catching basketball or lacrosse ball with stick)

Neurocognitive Demand

Decision making

Memory

Dual task

External focus of control

Reaction time

Figure 1a. Forward/Backward Cone Stepping: Patient steps over cones, focusing on symmetry and 90-degree hip/knee/ankle flexion.

ing a ball or tapping light-up pods (BlazePods, Blazepod, San Diego, CA) with the upper extremity (Figure 2/Supplemental File 1). Patients can also perform knee extensions with NMES from 90 to 40 degrees with light resistance while performing hand taps with Blazepods (Figure 3/Supplemental File 2). Finally, standing terminal knee extensions with a resistance band behind the knee can be implemented using BlazePods to reinforce neural patterning (Figure 4/Supplemental File 3).

ACUTE PHASE (DAYS 8-21)

The acute phase of rehab builds upon the immediate postoperative phase, focusing on managing residual inflamma-

Examples:

Figure 1b. Lateral Cone Stepping: Patient steps laterally over cones, emphasizing controlled movement and core engagement.

tion, progressing range of motion, gait training, optimizing quadriceps firing. During this time, proprioceptive/balance training is introduced to increase neuromuscular control and prepare for more advanced stages of rehabilitation. An external focus of control is utilized to reinforce motor learning, as this has been shown to increase intracortical inhibition, which plays a role in increasing quadriceps firing.9

Double leg exercises such as mini squats and weight shifts are performed first advancing to single leg exercises such as balance and stepping drills as a progression. The mini squat is performed from 0 to 45 degrees of flexion for maximal quadriceps and hamstring co-activation. A neurocognitive challenge can easily be added by introducing

See Supplemental File 1 for video.

See Supplemental File 2 for video.

an unstable surface such as foam or a tilt board under the patient’s feet. The clinician can perturbate the surface so

See Supplemental File 3 for

that the patient must react and right the rocker board (Figure 5). As proprioception improves, the patient can catch objects or perform cognitive tasks such as counting, math problems, or responding to visual stimuli during the task. If the patient continues to demonstrate quad avoidance gait, standing terminal knee extension (TKE) exercises with Blazepods can be performed.

Reinforcing proper gait patterns in this phase is vital as soon as possible as the patient will be transitioning off crutches and utilizing the drop-lock brace only for ambulation. Gait compensations that commonly occur after ACLR include reduced knee flexion, increased hip flexion/circumduction, reduced knee extension moment, altered quadriceps-hamstring co-activation during stance, along with reduced ipsilateral stance time.33‑35 Stepping drills over cones can be utilized again here to challenge the neurocognitive system and reinforce proper mechanics.

Once the patient demonstrates appropriate gait mechanics and control with double leg exercises, lunging and stepping movements can be implemented to work towards single leg activity Lunges are performed as the patient steps to the side and lands on a flexed knee to approximately 30-45 degrees for maximal stability Each of these tasks are initiated straight in the frontal plane on a solid surface. In this phase, a ball toss or slight external perturbation may be added to incorporate additional core and lower extremity musculature with feedforward mechanisms.

Single leg exercises begin with eyes open, solid surface, and static positions, progressing with visual disturbances, varied surfaces, and dynamic UE tasks. Examples include

Figure 2. Blazepod Quad Set: Patient performs isometric quadriceps contraction with NMES while tapping corresponding Blazepods.

Figure 3. Blazepod Knee Extension: Patient performs assisted knee extension while tapping corresponding Blazepods.

Figure 4. Blazepod TKE: Patient performs standing terminal knee extensions with band resistance while tapping Blazepods.

video.

provides perturbations.

single leg balance on the floor with the knee slightly flexed to 30-45 degrees. This can be performed on various unstable surfaces with external perturbations, and/or a reactive sensorimotor task on a television screen in front of them (ex: using Senaptec Sensory station [Senaptec, Beaverton, OR], reacting to animals or solving math problems on the screen – Figure 6). Each of these exercises are vital to include early in the rehabilitation process in order to reinforce fundamental movement patterns and prepare the patient for more complex movements in the later stages.

INTERMEDIATE PHASE (WEEKS 4-8)

The intermediate phase of ACLR rehabilitation focuses on restoring full knee range of motion (ROM) to 0°-135°-145°, advancing lower extremity strength/endurance, balance, and neuromuscular control. Most patients will unlock and discharge their knee immobilizer in this phase, so it is imperative to prepare the neuromuscular system for dynamic environments in their daily life while focusing on limb confidence and closed kinetic chain (CKC) function.

CKC neuromuscular control exercises in the sagittal plane are initiated with an anterior step down on level ground. The patient is instructed to place their hands on their hips and tap the heel of the uninvolved leg on the ground in front of them while controlling dynamic lower extremity (LE) valgus and pelvic pronation. Initially, a mirror is used as an external focus of control. This can be progressed to an elevated surface using weights, and eventually with spiral band resistance to enhance the control of rotational patterns (Figure 7). The front step-down exercise can also be enhanced with the utilization of blazepods for

resistance band applying adduction and internal rotation force.

reactive stability. These progressions will be described in greater detail in Part 2 of this commentary

Figure 5. Rocker Board Squats: Patient performs mini squats on rocker board while clinician

Figure 6. Neurocognitive Single Leg Balance: Patient balances on surgical leg on rocker board while solving math problems on Senaptec Sensory Station (Beaverton, OR) and maintaining balance during perturbations.

Figure 7 Single leg step downs with spiral band resistance: Patient performs step-downs with

Figure 8a. Quickboard (Memphis, TN) Lateral Step: Patient performs lateral step onto Quickboard, focusing on knee stability and target reaction.

See Supplemental File 4 for video.

Frontal plane movements are progressed with lateral lunges and lateral stepping drills. Lateral stepping is introduced once the patient demonstrates appropriate sagittal plane control. This is performed with a resistance band placed around the knees while the patient steps laterally at the assigned speed (slow, medium, or fast) and direction. A ball is then thrown for additional neurocognitive engagement as the patient must react to both the verbal direction and direction of the ball. Faster speeds and reactive directions are reserved for the later stages.

Lunges are progressed to diagonal lunges in both the anterior and posterior direction and upon unstable surfaces. Rotation may be added when the patient is further along in the rehab process. Multi-directional lunges are progressed with resistance using a sport cord or manual external perturbation. A visual stimulus on the ground can also be added using target lights or the QuickBoard Device (Figure 8a). The patient can lunge onto the indicated surface, reacting to the correct position on the board (Figure 8b).

Stepping exercises can be advanced in this stage to emphasize speed, coordination, and endurance. Patients perform in-place stepping drills while reacting to visual targets on the Quick Board (Figure 9a/Supplemental File 6). This can also be performed with a reaction target (Figure 9b/Supplemental File 7). The Quick Board may facilitate various single and dual-leg coordination exercises while assessing accuracy, reaction time, and limb symmetry.

Finally, single leg tasks can also be combined into a functional task such as a single leg Romanian Deadlift (SL RDL). This can be performed on various surfaces, unweighted or weighted with kettlebells (KB). Tasks such as

Lunge with Catch: Patient performs lateral lunge towards Blazepod (San Diego, CA) while catching a ball.

See Supplemental File 5 for video.

9a. Quickboard (Memphis, TN) Foot Fire: Patient performs rapid stepping in place while tapping targets on Quickboard.

See Supplemental File 6 for video.

SL RDL with KB exchanges may be incorporated, where the patient performs an RDL holding the bottom position while

Figure 8b. Reactive Lateral

Figure

Figure 9b. Quickboard (Memphis, TN) Foot Fire with Reactive Taps: Patient performs rapid stepping in place while reacting to visual targets on the screen.

See Supplemental File 7 for video.

exchanging a weighted KB from hand to hand to challenge the limits of stability. Another option is the SL RDL with star drill, where the patient catches a ball and touches a series of 5 cones placed on the floor while in the bottom of the RDL position, allowing for incorporation of UE, visual system, and SL stability SL RDL with CLX tubing wrapped around the thigh is used for proprioceptive input to control dynamic LE valgus, adduction and internal rotation. These single-leg balance exercises with extremity movement are designed to engage multiple muscle groups while enhancing dynamic stabilization.

As exercise complexity increases, patients often exhibit deteriorating movement patterns, which can heighten their risk of injury For those demonstrating significant pelvic drop and hip internal rotation on the stance leg during functional tasks, a targeted exercise using a resistance band can be implemented. The band is strategically placed around the athlete’s limb to replicate adduction and internal rotation forces commonly experienced during dynamic movements. The athlete then performs sport-specific tasks, such as dribbling a basketball or throwing/kicking a soccer ball, while balancing on an unstable surface (e.g., rocker board). Simultaneously, the practitioner applies external perturbations by pulling on the resistance band and tapping the board (Figure 10). Alternatively, the practitioner can pull the band medially to recreate knee valgus forces. To increase the neurocognitive challenge, BlazePods can be introduced on the floor for the athlete to tap with their contralateral extremity during the task.

To introduce dynamic lateral movements focused on rapid visual processing and change of direction movements,

lateral shuffling is introduced with BlazePods. Four Blazepods are placed in a straight line in front of the patient on top of cones for enhanced visibility As the BlazePod lights up, the athlete performs a lateral shuffle towards the illuminated pod while staying low and maintaining balance. Simultaneously, the clinician tosses a ball towards the athlete. The athlete must catch the ball mid-shuffle, continue moving towards the BlazePod, and tap the lit pod with the ball before shuffling back to the starting position. This drill can be progressed by placing the pods on the floor so that the athlete must maintain a lower stance and with quicker speeds (Figure 11/Supplemental File 8). The exercise is designed to enhance reaction time, hand-eye coordination, lateral speed, and agility while keeping the athlete engaged in multiple tasks simultaneously Each progressive variation simulates the visual-cognitive demands of sport, training the athlete to maintain control and react effectively to external stimuli while executing complex movements.

CONCLUSION

In conclusion, incorporating neurocognitive training into ACL rehabilitation is essential to reduce re-injury rates and promote optimal recovery. Traditional rehabilitation methods that focus on physical aspects such as strength and range of motion, are missing a key element. Addressing neuromuscular control and cognitive function is equally crucial. Neurocognitive exercises that focus on dual-tasking and reactive/feed forward activities enhance proprioception, dynamic stability, and motor planning, and better

Figure 10. Rocker Board Balance with Ball Catches and Valgus Resistance: Patient balances on rocker board while catching a ball and resisting valgus force from a band.

Figure 11. Reactive Lateral Shuffle Drill: Patient performs lateral shuffles towards illuminated BlazePods (San Diego, CA) while catching and tapping the pod with a ball.

See Supplemental File 8 for video.

mimic the real world and sporting environment, which is when most ACL injuries and re-injuries occur These exercises not only improve the immediate functional outcomes,

but also foster beneficial neuroplasticity, ensuring better long-term joint stability and movement efficiency. Clinically, it is vital to understand that neuro-cognitive training is a dynamic principle and should not be isolated to the beginning stages of rehabilitation. Instead, integrating neurocognitive training from the pre-operative phase through full recovery with sport specific drills is vital and provides a comprehensive approach, addressing the multifaceted demands of returning to both sport and competition, but it does not end here. It is essential to use neurocognitive training as an injury prevention mechanism and should be incorporated in both injured and non-injured athletes at any level of competition. Ultimately, the authors’ goal with this strategy is to bridge the gap between rehabilitation and performance, while enhancing the long-term resilience of the knee joint. Overall, the authors believe by including neuromuscular and neurocognitive exercises early and throughout the rehabilitation process, it reduces the likelihood of re-injury and supports patients in achieving a higher quality of life post-ACLR.

COI STATEMENT

No funding was provided for this manuscript. Kevin Wilk serves on the medical advisory board for BlazePods and receives educational grant funds from Quickboard. No other relevant author disclosures.

Submitted: August 12, 2024 CDT, Accepted: October 01, 2024 CDT

The Author(s)

1. Wilk KE. Anterior cruciate ligament injury prevention & rehabilitation: Let’s get it right. J Orthop Sports Phys Ther. 2015;45(10):729-730. doi:10.2519/jospt.2015.0109

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SUPPLEMENTARY MATERIALS

Figure 2/Supplemental File 1

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Neurocognitive and Neuromuscular Rehabilitation

Techniques after ACL

Injury, Part 1: Optimizing Recovery in the Acute Post-Operative Phase- A Clinical Commentary

Keywords: Anterior cruciate ligament reconstruction, neurocognitive training, neuroplasticity, proprioception, motor control https://doi.org/10.26603/001c.124945

International Journal of Sports Physical Therapy

Anterior cruciate ligament (ACL) injury rates are on the rise, despite improved surgical techniques and prevention programs. While traditional rehabilitation emphasizes the restoration of motion, strength, and physical performance, emerging research highlights the importance of addressing neurocognitive deficits that can persist after injury These deficits, including altered proprioception, impaired motor control and muscle recruitment, as well as heightened reliance on visual feedback, can significantly increase the risk of re-injury and impede return to sport. The purpose of this clinical commentary is to outline a proposed comprehensive approach to rehabilitation that challenges the neurocognitive system to optimize rehabilitation outcomes and reduce reinjury risk. Thus, this clinical commentary discusses the rationale for integrating neurocognitive training into all phases of ACLR rehabilitation, from initial injury to eight weeks post-surgery. It details the neurophysiological changes caused by ACL injury and presents evidence supporting the use of exercises that challenge visual attention, decision-making, and motor planning. A comprehensive rehabilitation framework incorporating both physical and neurocognitive components is proposed, aiming to improve long-term outcomes and reduce re-injury risk.

Level of Evidence: 5

INTRODUCTION

Female athletes in sports like soccer, basketball, and volleyball, as well as gymnasts, and male football players, face a heightened risk of injury These injuries are often triggered by unanticipated or decelerating movements, and the injury that is sustained disrupts the body’s normal sensory input and motor control, leading to neuroplastic changes in the brain.8 Research has shown that these changes can

200 Montgomery Hwy, Suite 150 Birmingham, AL, 35216 kwilkpt@hotmail.com a Wilk KE, Ivey M, Thomas ZM, Lupowitz L. Neurocognitive and Neuromuscular Rehabilitation Techniques after ACL Injury, Part 1: Optimizing Recovery in the Acute Post-Operative Phase- A Clinical Commentary. IJSPT. Published online November 2, 2024:1373-1385. doi:10.26603/001c.124945

Corresponding Author: Kevin Wilk

manifest as decreased reaction times, processing speeds, and proprioception, further contributing to the risk of injury.9‑13

NEUROPLASTICITY AND ACL INJURY

NEUROCOGNITIVE REHABILITATION: A COMPREHENSIVE APPROACH

PRINCIPLES OF NEUROCOGNITIVE REHABILITATION

ACL REHABILITATION AND THE INCLUSION OF NEUROCOGNITIVE STRATEGIES

PRE-OPERATIVE PHASE

Motor and cognitive dual-tasking exercises are implemented, where patients perform functional and cognitive tasks simultaneously This approach promotes agonist/an-

IMMEDIATE POST-OPERATIVE PHASE (DAYS 1-7)

Table

Exercise/Drill Variables/ progressions to enhance neuroplasticity

Quad sets

Straight leg raises (3 way)

Knee extensions (90-40 deg)

Mini squats Standing TKEs

NMES EMG biofeedback

Reactive cognitive motor task (BlazePods)

Surface (i.e. foam, rocker board)

Resistance

Dual task (i.e ball toss or HecoStix)

Reactive cognitive motor task (BlazePods, Neurocognitive Sensory station)

Perturbations

Cognitive task (counting, memory, etc.)

Altered vision Contralateral limb/ UE task

Gait/stepping drills:

Weight shifts

Cone stepping

Lateral lunges

Lateral stepping (slides)

Quick Board stepping drills

CKC neuromuscular exercises:

Anterior/ lateral step

downs

Multidirectional lunges

Speed Direction (ant/ post/lateral)

Dual task (i.e ball toss or HecoStix)

Cognitive task (counting, memory, etc.)

Reactive cognitivemotor task

Resistance Surface

Dual task (i.e ball toss or HecoStix)

Perturbation/ resistance from CLX band

Cognitive task (counting, memory, etc.)

Reactive cognitive motor task (BlazePods)

Resistance Surface

Single leg balance:

SL RDL with UE task

SL balance with band perturbations

Dual task (i.e. ball toss)

Direction (star drill on floor)

Visual targets

Perturbation (KB exchange/ resistance band)

UE task (i.e cable row, med ball chop, reach)

Dynamic shuffling Speed Direction

Neurocognitive Demand

Visual Cognitive Efferent firing

Cognitive Dual task

External focus of control Reaction time

Examples:

Quad set with NMES

Straight leg raises while using UE to react to indicated BlazePod color

Knee extensions using visual EMG biofeedback Virtual Reality Glasses

Mini squats on rocker board with external perturbations while throwing/catching a ball

Standing TKE while using UE to react to indicated quickboard target

Visual Cognitive Decision making

Memory

Dual task

External focus of control Reaction time

Visual Cognitive Decision making

Memory

Dual task

External focus of control

Reaction time

Visual Cognitive Decision making

Memory

Dual task

External focus of control Reaction time

Weight shifts on force plates with visual feedback

Multi-directional cone stepping counting backward by 7’s and tossing HecoStix

Lateral lunges with sport cord perturbation and ball toss, landing on foam surface

Lateral slides with resistance band around knees, reacting to verbal cues (direction, speed) and catching ball

Rapid stepping in place with visual target, reacting to correct location on the board or surface (Quickboard)

Anterior step down from box with CLX band pulling into femoral IR and dynamic LE valgus (figure 8)

Lateral lunges with sport cord perturbation and ball toss toward indicated direction. Athlete must react to indicated direction using light up pods (i.e. antero-lateral or posterolateral)

Visual Cognitive Decision making

Memory

Dual task

External focus of control Reaction time

Cognitive

SL RDL standing on foam while catching a ball and performing RDL to the indicated cone (5 cones set up in front of the patient)

Visual

Lateral Shuffles with BlazePod and Sport Specific Ball Catching (figure 11)

Exercise/Drill Variables/ progressions to enhance neuroplasticity

Visual targets (with/without distraction targets)

Auditory cues (i.e direction/speed)

Height/location of target

Sport specific task (i.e catching basketball or lacrosse ball with stick)

Neurocognitive Demand

Decision making

Memory

Dual task

External focus of control

Reaction time

Figure 1a. Forward/Backward Cone Stepping: Patient steps over cones, focusing on symmetry and 90-degree hip/knee/ankle flexion.

ACUTE PHASE (DAYS 8-21)

The acute phase of rehab builds upon the immediate postoperative phase, focusing on managing residual inflamma-

Examples:

Figure 1b. Lateral Cone Stepping: Patient steps laterally over cones, emphasizing controlled movement and core engagement.

See Supplemental File 1 for video.

See Supplemental File 2 for

an unstable surface such as foam or a tilt board under the patient’s feet. The clinician can perturbate the surface so

See Supplemental File 3 for

Single leg exercises begin with eyes open, solid surface, and static positions, progressing with visual disturbances, varied surfaces, and dynamic UE tasks. Examples include

Figure 2. BlazePod Quad Set: Patient performs isometric quadriceps contraction with NMES while tapping corresponding BlazePods (San Diego, CA).

Figure 3. BlazePod Knee Extension: Patient performs assisted knee extension while tapping corresponding BlazePods (San Diego, CA).

video.

Figure 4. Blazepod TKE: Patient performs standing terminal knee extensions with band resistance while tapping BlazePods (San Diego, CA).

video.

provides perturbations.

INTERMEDIATE PHASE (WEEKS 4-8)

resistance band applying adduction and internal rotation force.

reactive stability. These progressions will be described in greater detail in Part 2 of this commentary

Figure 5. Rocker Board Squats: Patient performs mini squats on rocker board while clinician

Figure 7 Single leg step downs with spiral band resistance: Patient performs step-downs with

Figure 8a. Quickboard (Memphis, TN) Lateral Step: Patient performs lateral step onto Quickboard, focusing on knee stability and target reaction.

See Supplemental File 4 for video.

Lunge with Catch: Patient performs lateral lunge towards Blazepod (San Diego, CA) while catching a ball.

See Supplemental File 5 for video.

9a. Quickboard (Memphis, TN) Foot Fire: Patient performs rapid stepping in place while tapping targets on Quickboard.

See Supplemental File 6 for video.

SL RDL with KB exchanges may be incorporated, where the patient performs an RDL holding the bottom position while

Figure 8b. Reactive Lateral

Figure

Figure 9b. Quickboard (Memphis, TN) Foot Fire with Reactive Taps: Patient performs rapid stepping in place while reacting to visual targets on the screen.

See Supplemental File 7 for video.

To introduce dynamic lateral movements focused on rapid visual processing and change of direction movements,

CONCLUSION

Figure 10. Rocker Board Balance with Ball Catches and Valgus Resistance: Patient balances on rocker board while catching a ball and resisting valgus force from a band.

Figure 11. Reactive Lateral Shuffle Drill: Patient performs lateral shuffles towards illuminated BlazePods (San Diego, CA) while catching and tapping the pod with a ball.

See Supplemental File 8 for video.

mimic the real world and sporting environment, which is when most ACL injuries and re-injuries occur These exercises not only improve the immediate functional outcomes,

COI STATEMENT

No funding was provided for this manuscript. Kevin Wilk serves on the medical advisory board for BlazePods and receives educational grant funds from Quickboard. No other relevant author disclosures.

Submitted: August 12, 2024 CST, Accepted: October 01, 2024 CST

© The Author(s)