HCI International 2020 Late Breaking Papers Multimodality and Intelligence
22nd HCI International Conference HCII
2020 Copenhagen Denmark July 19 24
2020 Proceedings Constantine Stephanidis
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Constantine Stephanidis
Masaaki Kurosu
Helmut Degen
Lauren Reinerman-Jones (Eds.)
HCI International 2020 –Late Breaking Papers Multimodality and Intelligence 22nd HCI International Conference, HCII 2020 Copenhagen, Denmark, July 19–24, 2020
Proceedings
LectureNotesinComputerScience12424 FoundingEditors
GerhardGoos
KarlsruheInstituteofTechnology,Karlsruhe,Germany
JurisHartmanis
CornellUniversity,Ithaca,NY,USA
EditorialBoardMembers
ElisaBertino
PurdueUniversity,WestLafayette,IN,USA
WenGao
PekingUniversity,Beijing,China
BernhardSteffen
TUDortmundUniversity,Dortmund,Germany
GerhardWoeginger
RWTHAachen,Aachen,Germany
MotiYung
ColumbiaUniversity,NewYork,NY,USA
Moreinformationaboutthisseriesat http://www.springer.com/series/7409
ConstantineStephanidis • MasaakiKurosu • HelmutDegen •
LaurenReinerman-Jones(Eds.)
HCIInternational2020 – LateBreakingPapers MultimodalityandIntelligence 22ndHCIInternationalConference,HCII2020 Copenhagen,Denmark,July19–24,2020
Proceedings
Editors
ConstantineStephanidis UniversityofCreteandFoundation forResearchandTechnology – Hellas (FORTH)
Heraklion,Crete,Greece
HelmutDegen SiemensCorporation Princeton,NJ,USA
MasaakiKurosu TheOpenUniversityofJapan Chiba,Japan
LaurenReinerman-Jones UniversityofCentralFlorida Orlando,FL,USA
ISSN0302-9743ISSN1611-3349(electronic)
LectureNotesinComputerScience
ISBN978-3-030-60116-4ISBN978-3-030-60117-1(eBook) https://doi.org/10.1007/978-3-030-60117-1
LNCSSublibrary:SL3 – InformationSystemsandApplications,incl.Internet/Web,andHCI
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Foreword The22ndInternationalConferenceonHuman-ComputerInteraction,HCIInternational 2020(HCII2020),wasplannedtobeheldattheACBellaSkyHotelandBellaCenter, Copenhagen,Denmark,duringJuly19–24,2020.DuetotheCOVID-19pandemicand theresolutionoftheDanishgovernmentnottoalloweventslargerthan500peopleto behosteduntilSeptember1,2020,HCII2020hadtobeheldvirtually.Itincorporated the21thematicareasandaffi liatedconferenceslistedonthefollowingpage.
Atotalof6,326individualsfromacademia,researchinstitutes,industry,andgovernmentalagenciesfrom97countriessubmittedcontributions,and1,439papersand 238posterswereincludedinthevolumesoftheproceedingspublishedbeforethe conference.Additionally,333papersand144postersareincludedinthevolumes oftheproceedingspublishedaftertheconference,as “LateBreakingWork” (papers andposters).Thesecontributionsaddressthelatestresearchanddevelopmenteffortsin the fi eldandhighlightthehumanaspectsofdesignanduseofcomputingsystems.
ThevolumescomprisingthefullsetoftheHCII2020conferenceproceedingsare listedinthefollowingpagesandtogethertheybroadlycovertheentire fi eldof human-computerinteraction,addressingmajoradvancesinknowledgeandeffective useofcomputersinavarietyofapplicationareas.
IwouldliketothanktheProgramBoardChairsandthemembersoftheProgram BoardsofallThematicAreasandAffiliatedConferencesfortheirvaluablecontributionstowardsthehighestscientifi cqualityandtheoverallsuccessoftheHCIInternational2020conference.
Thisconferencewouldnothavebeenpossiblewithoutthecontinuousandunwaveringsupportandadviceofthefounder,conferencegeneralchairemeritusand conferencescientificadvisor,Prof.GavrielSalvendy.Forhisoutstandingefforts, Iwouldliketoexpressmyappreciationtothecommunicationschairandeditorof HCIInternationalNews,Dr.AbbasMoallem.
July2020ConstantineStephanidis
HCIInternational2020ThematicAreas andAffiliatedConferences ThematicAreas:
• HCI2020:Human-ComputerInteraction
• HIMI2020:HumanInterfaceandtheManagementofInformation
Affi liatedConferences:
• EPCE:17thInternationalConferenceonEngineeringPsychologyandCognitive Ergonomics
• UAHCI:14thInternationalConferenceonUniversalAccessinHuman-Computer Interaction
• VAMR:12thInternationalConferenceonVirtual,AugmentedandMixedReality
• CCD:12thInternationalConferenceonCross-CulturalDesign
• SCSM:12thInternationalConferenceonSocialComputingandSocialMedia
• AC:14thInternationalConferenceonAugmentedCognition
• DHM:11thInternationalConferenceonDigitalHumanModeling&Applications inHealth,Safety,Ergonomics&RiskManagement
• DUXU:9thInternationalConferenceonDesign,UserExperienceandUsability
• DAPI:8thInternationalConferenceonDistributed,AmbientandPervasive Interactions
• HCIBGO:7thInternationalConferenceonHCIinBusiness,Governmentand Organizations
• LCT:7thInternationalConferenceonLearningandCollaborationTechnologies
• ITAP:6thInternationalConferenceonHumanAspectsofITfortheAged Population
• HCI-CPT:SecondInternationalConferenceonHCIforCybersecurity,Privacyand Trust
• HCI-Games:SecondInternationalConferenceonHCIinGames
• MobiTAS:SecondInternationalConferenceonHCIinMobility,Transportand AutomotiveSystems
• AIS:SecondInternationalConferenceonAdaptiveInstructionalSystems
• C&C:8thInternationalConferenceonCultureandComputing
• MOBILE:FirstInternationalConferenceonDesign,OperationandEvaluationof MobileCommunications
• AI-HCI:FirstInternationalConferenceonArti ficialIntelligenceinHCI
ConferenceProceedings – FullListofVolumes 1.LNCS12181,Human-ComputerInteraction:DesignandUserExperience(PartI), editedbyMasaakiKurosu
2.LNCS12182,Human-ComputerInteraction:MultimodalandNaturalInteraction (PartII),editedbyMasaakiKurosu
3.LNCS12183,Human-ComputerInteraction:HumanValuesandQualityofLife (PartIII),editedbyMasaakiKurosu
4.LNCS12184,HumanInterfaceandtheManagementofInformation:Designing Information(PartI),editedbySakaeYamamotoandHirohikoMori
5.LNCS12185,HumanInterfaceandtheManagementofInformation:Interacting withInformation(PartII),editedbySakaeYamamotoandHirohikoMori
6.LNAI12186,EngineeringPsychologyandCognitiveErgonomics:Mental Workload,HumanPhysiology,andHumanEnergy(PartI),editedbyDonHarris andWen-ChinLi
7.LNAI12187,EngineeringPsychologyandCognitiveErgonomics:Cognitionand Design(PartII),editedbyDonHarrisandWen-ChinLi
8.LNCS12188,UniversalAccessinHuman-ComputerInteraction:Design ApproachesandSupportingTechnologies(PartI),editedbyMargheritaAntona andConstantineStephanidis
9.LNCS12189,UniversalAccessinHuman-ComputerInteraction:Applicationsand Practice(PartII),editedbyMargheritaAntonaandConstantineStephanidis
10.LNCS12190,Virtual,AugmentedandMixedReality:DesignandInteraction (PartI),editedbyJessieY.C.ChenandGinoFragomeni
11.LNCS12191,Virtual,AugmentedandMixedReality:IndustrialandEveryday LifeApplications(PartII),editedbyJessieY.C.ChenandGinoFragomeni
12.LNCS12192,Cross-CulturalDesign:UserExperienceofProducts,Services,and IntelligentEnvironments(PartI),editedbyP.L.PatrickRau
13.LNCS12193,Cross-CulturalDesign:ApplicationsinHealth,Learning, Communication,andCreativity(PartII),editedbyP.L.PatrickRau
14.LNCS12194,SocialComputingandSocialMedia:Design,Ethics,UserBehavior, andSocialNetworkAnalysis(PartI),editedbyGabrieleMeiselwitz
15.LNCS12195,SocialComputingandSocialMedia:Participation,UserExperience, ConsumerExperience,andApplicationsofSocialComputing(PartII),editedby GabrieleMeiselwitz
16.LNAI12196,AugmentedCognition:TheoreticalandTechnologicalApproaches (PartI),editedbyDylanD.SchmorrowandCaliM.Fidopiastis
17.LNAI12197,AugmentedCognition:HumanCognitionandBehaviour(PartII), editedbyDylanD.SchmorrowandCaliM.Fidopiastis
18.LNCS12198,DigitalHumanModeling&ApplicationsinHealth,Safety, Ergonomics&RiskManagement:Posture,MotionandHealth(PartI),edited byVincentG.Duffy
19.LNCS12199,DigitalHumanModeling&ApplicationsinHealth,Safety, Ergonomics&RiskManagement:HumanCommunication,Organizationand Work(PartII),editedbyVincentG.Duffy
20.LNCS12200,Design,UserExperience,andUsability:InteractionDesign(PartI), editedbyAaronMarcusandElizabethRosenzweig
21.LNCS12201,Design,UserExperience,andUsability:DesignforContemporary InteractiveEnvironments(PartII),editedbyAaronMarcusandElizabeth Rosenzweig
22.LNCS12202,Design,UserExperience,andUsability:CaseStudiesinPublicand PersonalInteractiveSystems(PartIII),editedbyAaronMarcusandElizabeth Rosenzweig
23.LNCS12203,Distributed,AmbientandPervasiveInteractions,editedbyNorbert StreitzandShin’ichiKonomi
24.LNCS12204,HCIinBusiness,GovernmentandOrganizations,editedbyFiona Fui-HoonNahandKengSiau
25.LNCS12205,LearningandCollaborationTechnologies:Designing,Developing andDeployingLearningExperiences(PartI),editedbyPanayiotisZaphirisand AndriIoannou
26.LNCS12206,LearningandCollaborationTechnologies:HumanandTechnology Ecosystems(PartII),editedbyPanayiotisZaphirisandAndriIoannou
27.LNCS12207,HumanAspectsofITfortheAgedPopulation:Technologies, DesignandUserexperience(PartI),editedbyQinGaoandJiaZhou
28.LNCS12208,HumanAspectsofITfortheAgedPopulation:HealthyandActive Aging(PartII),editedbyQinGaoandJiaZhou
29.LNCS12209,HumanAspectsofITfortheAgedPopulation:Technologyand Society(PartIII),editedbyQinGaoandJiaZhou
30.LNCS12210,HCIforCybersecurityPrivacyandTrust,editedbyAbbasMoallem
31.LNCS12211,HCIinGames,editedbyXiaowenFang
32.LNCS12212,HCIinMobility,TransportandAutomotiveSystems:Automated DrivingandIn-VehicleExperienceDesign(PartI),editedbyHeidiKrömker
33.LNCS12213,HCIinMobility,TransportandAutomotiveSystems:Driving Behavior,UrbanandSmartMobility(PartII),editedbyHeidiKrömker
34.LNCS12214,AdaptiveInstructionalSystems,editedbyRobertA.Sottilareand JessicaSchwarz
35.LNCS12215,CultureandComputing,editedbyMatthiasRauterberg
36.LNCS12216,Design,OperationandEvaluationofMobileCommunications, editedbyGavrielSalvendyandJuneWei
37.LNCS12217,Arti ficialIntelligenceinHCI,editedbyHelmutDegenandLauren Reinerman-Jones
38.CCIS1224,HCIInternational2020Posters(PartI),editedbyConstantine StephanidisandMargheritaAntona
39.CCIS1225,HCIInternational2020Posters(PartII),editedbyConstantine StephanidisandMargheritaAntona
40.CCIS1226,HCIInternational2020Posters(PartIII),editedbyConstantine StephanidisandMargheritaAntona
41.LNCS12423,HCIInternational2020 – LateBreakingPapers:UserExperience DesignandCaseStudies,editedbyConstantineStephanidis,AaronMarcus, ElizabethRosenzweig,P.L.PatrickRau,AbbasMoallem,andMatthiasRauterberg
42.LNCS12424,HCIInternational2020 – LateBreakingPapers:Multimodalityand Intelligence,editedbyConstantineStephanidis,MasaakiKurosu,HelmutDegen, andLaurenReinerman-Jones
43.LNCS12425,HCIInternational2020 – LateBreakingPapers:Cognition,Learning andGames,editedbyConstantineStephanidis,DonHarris,Wen-ChinLi, DylanD.Schmorrow,CaliM.Fidopiastis,PanayiotisZaphiris,AndriIoannou, XiaowenFang,RobertSottilare,andJessicaSchwarz
44.LNCS12426,HCIInternational2020 – LateBreakingPapers:UniversalAccess andInclusiveDesign,editedbyConstantineStephanidis,MargheritaAntona,Qin Gao,andJiaZhou
45.LNCS12427,HCIInternational2020 – LateBreakingPapers:Interaction, KnowledgeandSocialMedia,editedbyConstantineStephanidis,GavrielSalvendy, JuneWay,SakaeYamamoto,HirohikoMori,GabrieleMeiselwitz,FionaFui-Hoon Nah,andKengSiau
46.LNCS12428,HCIInternational2020 – LateBreakingPapers:VirtualandAugmentedReality,editedbyConstantineStephanidis,JessieY.C.Chen,andGino Fragomeni
47.LNCS12429,HCIInternational2020 – LateBreakingPapers:DigitalHuman ModelingandErgonomics,MobilityandIntelligentEnvironments,editedby ConstantineStephanidis,VincentG.Duffy,NorbertStreitz,Shin’ichiKonomi,and HeidiKrömker
48.CCIS1293,HCIInternational2020 – LateBreakingPosters(PartI),editedby ConstantineStephanidis,MargheritaAntona,andStavroulaNtoa
49.CCIS1294,HCIInternational2020 – LateBreakingPosters(PartII),editedby ConstantineStephanidis,MargheritaAntona,andStavroulaNtoa
http://2020.hci.international/proceedings
ThefulllistwiththeProgramBoardChairsandthemembersoftheProgramBoardsof allthematicareasandaffi liatedconferencesisavailableonlineat:
http://www.hci.international/board-members-2020.php
HCIInternational2021 The23rdInternationalConferenceonHuman-ComputerInteraction,HCIInternational 2021(HCII2021),willbeheldjointlywiththeaffiliatedconferencesin WashingtonDC,USA,attheWashingtonHiltonHotel,July24–29,2021.Itwill coverabroadspectrumofthemesrelatedtohuman-computerinteraction(HCI), includingtheoreticalissues,methods,tools,processes,andcasestudiesinHCIdesign, aswellasnovelinteractiontechniques,interfaces,andapplications.Theproceedings willbepublishedbySpringer.Moreinformationwillbeavailableontheconference website: http://2021.hci.international/
GeneralChair
Prof.ConstantineStephanidis
UniversityofCreteandICS-FORTH
Heraklion,Crete,Greece
Email:general_chair@hcii2021.org
http://2021.hci.international/
Contents MultimodalInteraction
EyeMovementClassificationAlgorithms:EffectofSettings onRelatedMetrics.........................................3 AminG.Alhashim
AnAntenatalCareAwarenessPrototypeChatbotApplication UsingaUser-CentricDesignApproach...........................20 MohammedBahja,NourAbuhwaila,andJuliaBahja
AUser-CentricFrameworkforEducationalChatbotsDesign andDevelopment..........................................32 MohammedBahja,RawadHammad,andGibranButt
CollegeBot:AConversationalAIApproachtoHelpStudents NavigateCollege...........................................44 MohinishDaswani,KavinaDesai,MiliPatel,ReeyaVani, andMagdaliniEirinaki
UserExpectationsofSocialRobotsinDifferentApplications: AnOnlineUserStudy.......................................64 XiaoDou,Chih-FuWu,XiWang,andJinNiu
CreatingEmotionalAttachmentwithAssistiveWearables..............73 NedaFayaziandLoisFrankel
AuDimo:AMusicalCompanionRobottoSwitchingAudioTracks byRecognizingtheUsersEngagement...........................89 W.K.N.Hansika,LakinduYasassriNanayakkara, AdhishaGammanpila,andRavindradeSilva
TransmissionofRubbingSensationwithWearableStick-SlipDisplay andForceSensor..........................................107 HonokaHaramo,VibolYem,andYasushiIkei
ReadingAloudinHuman-ComputerInteraction:HowSpatialDistribution ofDigitalTextUnitsatanInteractiveTabletopContributestothe Participants’ SharedUnderstanding..............................117 SvenjaHeuser,BéatriceArend,andPatrickSunnen
SpeechRecognitionApproachforMotion-EnhancedDisplay inARM-COMSSystem......................................135 TeruakiIto,TakashiOyama,andTomioWatanabe
Individual’sNeutralEmotionalExpressionTrackingforPhysical ExerciseMonitoring........................................145
SalikRamKhanal,JaimeSampaio,JoãoBarroso,andVitorFilipe
ExploringPointerAssistedReading(PAR):UsingMouseMovements toAnalyzeWebUsers’ ReadingBehaviorsandPatterns...............156 IlanKirshandMikeJoy
TheEffectsofRobotAppearances,VoiceTypes,andEmotionsonEmotion PerceptionAccuracyandSubjectivePerceptiononRobots..............174 SangjinKo,XiaozhenLiu,JakeMamros,EmilyLawson,HaleySwaim, ChengkaiYao,andMyounghoonJeon
DevelopmentforTablet-BasedPerimeterUsingTemporalCharacteristics ofSaccadicDurations.......................................194
NaokiMaeshiba,KentaroKotani,SatoshiSuzuki,andTakafumiAsao
AutomaticPage-TurnerforPianistswithWearableMotionDetector.......209 SeyedAliMirazimzadehandVictoriaMcArthur
ASociableRoboticPlatformtoMakeCareerAdvicesforUndergraduates...219 W.K.MalithiMithsara,UdakaA.Manawadu, andP.RavindraS.DeSilva
DevelopmentandEvaluationofaPenTypeThermalSensationPresentation DeviceforSPIDAR-Tablet....................................231 KaedeNohara,YasunaKubo,MakotoSato,TakehikoYamaguchi, andTetsuyaHarada
CountMarks:Multi-fingerMarkingMenusforMobileInteraction withHead-MountedDisplays..................................241 JordanPollockandRobertJ.Teather
Single-ActuatorSimultaneousHapticRenderingforMultipleVitalSigns....261 JulietteRegimbal,NusaibaRadi,AntoineWeill–Duflos, andJeremyR.Cooperstock
DevelopmentofanInterfacethatExpressesTwinklingEyes bySuperimposingHumanShadowsonPupils......................271 YoshihiroSejima,MakikoNishida,andTomioWatanabe
MUCOR:AMultipartyConversationBasedRoboticInterfacetoEvaluate JobApplicants............................................280
H.A.S.D.Senaratna,UdakaA.Manawadu,W.K.N.Hansika, S.W.A.M.D.Samarasinghe,andP.RavindraS.DeSilva
UsabilityEvaluationofSmartphoneKeyboardDesignfromanApproach ofStructuralEquationModel..................................294
YinchengWang,JunyuHuo,YuqiHuang,KeWang,DiWu,andJiboHe
UnderstandingVoiceSearchBehavior:ReviewandSynthesisofResearch...305 ZhaopengXing,XiaojunYuan,DanWu,YemanHuang, andJavedMostafa
EvaluationofSpeechInputRecognitionRateofAR-BasedDrawing ApplicationonOperationMonitorforCommunicationSupportDuring EndoscopicSurgery.........................................321
TakutoYajima,TakeruKobayashi,KentaroKotani,SatoshiSuzuki, TakafumiAsao,KazutakaObama,AtsuhikoSumii, andTatsutoNishigori
TracKenzan:DigitalFlowerArrangementUsingTrackpadandStylusPen...332 AnnaYokokubo,YujiKato,andItiroSiio
MappingBetweenMindCyberneticsandAestheticStructureinReal-Time EEGArt................................................344
MinliZhang,YiyuanHuang,SalahUddinAhmed, andMohammadShidujaman
UserExperienceAnalysisforVisualExpressionAimingatCreating ExperienceValueAccordingtoTimeSpans........................363 CairenZhuoma,KeikoKasamatsu,andTakeoAinoya
AIinHCI Arny:AStudyofaCo-creativeInteractionModelFocused onEmotionFeedback.......................................377
SarahAbdellahi,MaryLouMaher,SafatSiddiqui,JebaRezwana, andAliAlmadan
TowardsIntelligentTechnologyinArtTherapyContexts...............397 WoudAlSadoun,NujoodAlwahaibi,andLeanAltwayan
ExplainableClassificationofEEGDataforanActiveTouchTaskUsing ShapleyValues............................................406 HaneenAlsuradi,WanjooPark,andMohamadEid
SANDFOXProjectOptimizingtheRelationshipBetweentheUser InterfaceandArtificialIntelligencetoImproveEnergyManagement inSmartBuildings.........................................417
ChristopheBortolaso,StéphanieCombettes,Marie-PierreGleizes, BerangereLartigue,MathieuRaynal,andStéphanieRey
SafetyAnalyticsforAISystems................................434 YangCai
Human-CenteredExplainableAI:TowardsaReflective SociotechnicalApproach.....................................449 UpolEhsanandMarkO.Riedl
ThePowerofAugmentedRealityandArtificialIntelligenceDuring theCovid-19Outbreak.......................................467 ChutisantKerdvibulvechandLiming(Luke)Chen
V-Dream:ImmersiveExplorationofGenerativeDesignSolutionSpace.....477 MohammadKeshavarzi,ArdavanBidgoli,andHansKellner
UsabilityinMixedInitiativeSystems............................495 SachinKumarswamy
HumanVersusMachineandHuman-MachineTeamingonMasked LanguageModelingTasks....................................505 MingQianandDavisQian
UsingArtificialIntelligencetoPredictAcademicPerformance...........517 ArsénioReis,TâniaRocha,PauloMartins,andJoãoBarroso
WhyDidtheRobotCrosstheRoad?:AUserStudyofExplanation inHuman-RobotInteraction...................................527 ZacharyTaschdjian
AuthorIndex ............................................539
MultimodalInteraction EyeMovementClassificationAlgorithms: EffectofSettingsonRelatedMetrics AminG.Alhashim(B)
TheUniversityofOklahoma,Norman,OK73069,USA alhashim@ou.edu
https://about.me/am1ngh
Abstract. Thebasicbuildingblockofanyeyetrackingresearchisthe eyefixations.Theseeyefixationsdependonmorefinedatagatheredby theeyetrackerdevice,therawgazedata.Therearemanyalgorithmsthat canbeusedtotransformtherawgazedataintoeyefixation.However, thesealgorithmsrequireoneormorethresholdstobeset.Aknowledge ofthemostappropriatevaluesforthesethresholdsisnecessaryinorder forthesealgorithmstogeneratethedesiredoutput.Thispaperexamines theeffectofasetofdifferentsettingsofthetwothresholdsrequiredfor theidentification-dispersionthresholdtypeofalgorithms:thedispersion anddurationthresholdsonthegeneratedeyefixations.Sincethiswork isatitsinfancy,thegoalofthispaperistogenerateandvisualizethe resultofeachsettingandleavethechoiceforthereaderstodecideon whichsettingfitstheirfutureeyetrackingresearch.
Keywords: Eyetracking · Eyemovementclassificationalgorithms · Fixationdurationmetric
1Introduction Itisalmostimpossibletofindaneyetrackingstudythatdoesnotutilizethe eyefixationsinonewayortheother.Eyefixationscanbeusedasastandalone metricorasabasisforothermetricssuchasfixationsequences.(Holmqvist etal. 2015)Theseeyefixationsarearesultofatransformationprocessdone ontherawgazedatabeingproducedbytheeyetrackerdevices.Thereare differentcategoriesofalgorithmsthatcanbeusedtodosuchtransformation (Duchowski 2007;SalvucciandGoldberg 2000).Thefocusofthispaperisthe identification-dispersionthreshold(I-DT)category.Thiscategoryofalgorithms hastwothresholdsthatneedtobeset:thedispersionthresholdandtheduration thresholdwhichareexplainedinSect.2.4.2.1andSect.2.4.2.2,respectively. SalvucciandGoldberg(2000)andBlignaut(2009)suggestedadispersion thresholdbetween0.5◦ and1.0◦ whileJacobandKarn(2003)decidedtofix itto2.0◦ .Similarly,SalvucciandGoldberg(2000)andJacobandKarn(2003) suggestedavaluebetween100msand200msforthedispersionthresholdwhile Nystr¨omandHolmqvist(2010)suggestedashorterperiodbetween80msand c SpringerNatureSwitzerlandAG2020 C.Stephanidisetal.(Eds.):HCII2020,LNCS12424,pp.3–19,2020. https://doi.org/10.1007/978-3-030-60117-1 1
150ms.Table 1 summarizesthedifferentvaluessuggestedbydifferentresearchers intheliterature.
Thispaperexplorestheeffectofsomeofsuggestedvalues,besideothers, forthedispersionanddurationthresholdsontheresultingeyefixationsand scanpathsequenceswithoutstatisticallytestingforanysignificantdifference betweenanyofthedifferentsettings.
Table1. Summaryofsomethesuggestedvaluesforthedispersionanddurationthresholdsoftheidentification-dispersionthreshold(I-DT)algorithmsintheliterature
Toexploretheeffectofthedifferentsettingsofthedispersionandduration thresholdsonthegeneratedeyefixationsbytheI-DTalgorithmsandthenon thescanpathstringsbuiltbasedontheeyefixations,theprocessleadingtothe finalresult,thescanpathstrings,isexplainedindetails.Theprocessconsistsof foursteps:(1)cleaningtherawgazedatapacketsgeneratedbytheeyetracker device(Sect. 2.4.1),(2)selecting/calculatingthethresholdvaluesfortheI-DT algorithm(Sect. 2.4.2),(3)computingtheeyefixationsusingtheI-DTalgorithm, and(4)computingthescanpathstringsbasedontheeyefixations(Sect. 2.4.3). Theeyefixationsandscanpathstringsresultingfromthedifferentsettings ofthedispersionanddurationthresholdsarereportedinSect. 2.5.Thepaper endswithadiscussion(Sect. 3)andaconclusion(Sect. 4).
2Methods 2.1Apparatus
TobiiProTX300(120Hz)EyeTrackersystemwitha24-inchmonitorwasused tocollecttherawgazedatapackets.Theeyetrackerwaspositionedbelowthe monitorandwasnotindirectcontactwiththeparticipant.Differentvaluesfor thevisualangleaccuracyweretestedfortheireffectontheeyefixationsand thescanpathsequencesasdescribedinSect.2.4.2.1.Thedistancefromtheparticipant’seyesandtheeyetrackerdeviceiscalculateddynamicallyandaddress alsoinSect.2.4.2.1alongwiththevisualangleaccuracy.Thedifferentthresholds thathavebeentestedtodefinetheeyefixationsarediscussedinSect.2.4.2.2.
2.2Participants
One35-yearoldmalestudentfromtheUniversityofOklahomatookpartinthe experiment.Theparticipantdoesnothaveanyvisualimpairments.
2.3Procedure
Theparticipanthasbeenaskedtoreadamedialtextthatcontainssomedifficult words(Fig. 1).Thisreadingtaskwasproceededbyacalibrationsessionforthe uservision.Theparticipanthasbeenaskedtomoveawayfromtheeyetracker deviceoncehefinishedreadingthetexttoavoidrecordinganyunrelatedgaze datapacketstotheexperiment.
Fig.1. Themedicalparagraphdisplayedtotheparticipant
ThevisionoftheparticipanthasbeencalibratedusingtheMatlabfunction, HandleCalibWorkflow,providedbyTobiiTechnologyInc.intheMatlabbinding API(TobiiTechnologyInc. 2015).Thisscriptispartofthe RealtimeEyeTrackingSample exampleandwasusedwithoutmodification.Attheendofthecalibrationprocess,aplotfortheoffsetbetweeneacheyegazedataandthecalibration pointsisshown(Fig. 2).Theparticipantwillbedirectedtopress‘y’onthe keyboardifthecalibrationprocessissuccessfulor‘n’torepeatthecalibration. Aftersuccessfullycompletingthecalibrationprocessandpressing‘y’onthe keyboard,thetextforthereadingtaskwasshownimmediatelyandtheeye trackerdevicestartedrecordingtherawgazedatapacketsafterpausingfor3s. Therawgazedatapacketscanbeobtainedbycallingthe readGazeData function intheMatlabbindingAPI.
Fig.2. Theoffsetbetweeneachleft(showninred)andright(showningreen)eyegaze dataandthecalibrationpointsoftheparticipant(showninblue)(Colorfigureonline)
2.4DataAnalysis 2.4.1DataCleaning
Eachrawgazedatapacketholds13piecesofinformationabouteacheye.More informationabouteachpieceoftherawgazedatacanbefoundinTobiiAnalytics SDKDeveloperGuideavailableasaPDFfilewhendownloadingtheTobiiAnalyticsSDK(TobiiTechnologyInc. 2015)ordirectlyviaAcuitywebsite(Tobii TechnologyInc. 2013).Oneofthepiecesofinformationintherawgazedata packetisthe validitycode.Thiscoderepresentshowconfidenttheeyetracker systemwaswhenassigningaparticulareyegazedatapackettoaparticulareye. Thiscoderangesfrom0(mostconfident)to4(leastconfident).
Avaliditycodeof0assignedtoaraweyedatapacketcapturedataspecific pointintimefortheleftandtherighteyeindicatesthattheeyetrackerisvery certainthateachofthedatapacketsisassociatedwiththecorrespondingeye. Ontheotherhand,ifthevaliditycodeoftherawdatapacketofoneeyeis0 and4fortheother,theeyetrackerdetectsaneyeanditismostprobablythe eyethathasavaliditycodeof0.
TheDataValidityCodestableintheTobiiAnalyticsSDKDeveloperGuide summarizesallthepossiblecombinationsofthevaliditycodesofthetwoeyes. Thetableshowsthatavaliditycodeof1ofoneeyeisonlypossiblewitha validitycodeof3ormoreoftheothereye.Also,theonlypossiblecombination ofavaliditycodeof2ofoneeyeisavaliditycodeof2oftheothereyewhich meansthattheeyetrackerdetectedoneeyebutitisnotcertainwhicheye,left orright,thisrawgazedatapacketrepresents.
Sinceweareinterestedincapturingthegazeofbotheyeswithhighlevel ofcertainty,anyrawgazedatapacketcapturedatanyspecificpointintime thatholdsavalidlycodevaluethatisnot0foranyeyewillbediscarded.The rawgazedatapacketsforbotheyes,afterfilteringtheinvalidpackets,willbe combinedintoasinglearrayof26columns;13identicalcolumnsforeacheye.
2.4.2ThresholdsSelection InorderfortheI-DTalgorithmtorun,twothresholdsmustbeprovidedalongsidetherawgazedatapackets.Oneofthesethresholdsisthemaximumdispersion(Sect.2.4.2.1)andtheotheristheminimumduration(Sect.2.4.2.2).
2.4.2.1DispersionThreshold. Thedispersionthresholdrepresentsthemaximum distancethattheID-Talgorithmshouldtoleratewhencomputingtheeyefixationspoints.Thisdistancehasthesamemeasurementunitofthecoordinates oftheprovidedgazedata.Thevalueassignedtothisthresholddependsonthe visualerroranglethattheeyetrackersystemsuffersfrom.Tobii,intheProduct DescriptionofitsTobiiProTX300EyeTracker(TobiiTechnologyInc. 2010), reportsavisualerroranglebetween0.4◦ and0.6◦ fordifferentconditions.
Thisvalueassignedtothedispersionthresholdmeansifagroupofrawgaze pointsisincloseproximitytoeachotherandthemaximumdistancebetween anytwoofthemislessthanthisdispersionthresholdvalue,thenthesegroupof rawgazepointsisconsolidatedintoasinglepointcalledaneyefixationgiven thattheysatisfytheminimumdurationthresholdexplainedinSect.2.4.2.2.
Thecalculationofthedispersionthresholddependsontwofactors:thedistanceoftheuserfromtheeyetrackersystemandthevisualerrorangleofthe eyetrackersystem.Thedistanceoftheuserfromtheeyetrackersystemcanbe elicitedfromtherawgazedatapacketsgeneratedbytheeyetrackersystemas theeye z-coordinate valueinmillimeters(moreinformationcanbefoundinthe TobiiAnalyticsSDKDeveloperGuide).Theaveragevalueofthesez-coordinates forbotheyesconstitutestheuser’seyedistancefromtheeyetrackersystem.
ThevisualerroranglereportedintheProductDescriptiondocumentofthe TobiiTX300EyeTracker(TobiiTechnologyInc. 2010)isgenerallybetween0.4◦ and0.6◦ dependingonthelightingconditions.Visualerroranglesof0.4◦ ,0.5◦ , and0.6◦ wereusedtocalculatethedispersionthreshold.
Thedispersionthreshold(inmillimeter)iscalculatedasfollows:
dispersionTheshold = eyeDistance ∗ sin(visualErrorAngle)
Afterpluggingtheeyedistance,whichisusually650mm,andvisualerror anglestotheequation,dispersionthresholdsof4.5mm,5.7mm,and6.8mm wereobtained.Figure 3 visuallyillustratethecalculationprocess.
Tobiiprovidesthe2-dimensionaleyegazepositionsinwhatiscalledActive DisplayCoordinateSystem(ADCS).Thissystemencodesthexandycoordinatesforthegazepositionofbotheyesusingvaluesbetween0and1(seeFig. 4). Avalueof(0,0)indicatesagazepositionatthetopleftcorneroftheactive displayareawhichisthemonitorinourcase.Ontheotherhand,avalueof
Differentpositioningsystems
(1,1)representsagazepositionatthelowerrightcorneroftheactivedisplay area.Formoreinformationaboutthissystem,refertotheTobiiAnalyticsSDK DeveloperGuide.
Sincethedispersionthresholdmeasurementsystemisdifferentfromthemeasurementsystemoftheeyegazepositions,theeyegazepositionswillbeconvertedtothedispersionthresholdmeasurementsystemwhichisthemillimeter system.ToconvertfromtheADCSsystemwhichistheeyegazepositionsmeasurementsystem,aknowledgeofthesizeoftheactivedisplay,themonitor,used inthestudyisnecessary.ThemonitorattachedtoTobiiTX300EyeTrackersystemmeasures508mminlengthand287mminwidth.Theconversionfromthe ADCSsystemtothemillimetersystemisstraightforward.Thex-coordinatesof eacheyegazepositionneedstobemultipliedbythelengthofthescreenwhich is508mmandthey-coordinatesneedstobemultipliedbythewidthofthe monitorwhichis287mm.
2.4.2.2DurationThreshold. Thedurationthresholdrepresentstheminimum time(inmilliseconds)afterwhichasetoftherawgazedatapackets,ifthey satisfythemaximumdispersionthreshold,willbeturnedintoaneyefixation point.Thecommondurationthresholdsuggestedbytheliteraturerangesfrom 50to200ms(SalvucciandGoldberg 2000;JacobandKarn 2003;Blaschecket al.2017;Nystr¨omandHolmqvist 2010;Blignaut 2009).Fourdifferentduration thresholds,namely,50,100,150,and200mswillbeexaminedfortheireffecton
Fig.3. Dispersionthresholdcalculations
Fig.4.
thegeneratedeyefixationsbytheI-DTalgorithm.Alongwiththesecommon durationthresholdvalues,twomorevalues,500and1000ms,wereinvestigated.
2.4.3FindingScanpathStrings Findingthescanpathstringforeachcombinationofthedispersionandduration thresholds’valuesgoesthroughtwostages.Thefirststageentailsdetermining thecoordinatesoftheboundingboxesoftheeachareaofinterest(AOI)for thesentences(Sect.2.4.3.1)andwords(Sect.2.4.3.3).Thesecondstageentails implementingascriptthatcomputationallydecidestowhichAOI(orAOIs) eachoftheeyefixationsbelongs(Sect.2.4.3.2).Aneyefixationwillbelongto morethanoneAOIincasetheAOIsareinterleaving.Inthecasewherenoone AOIinterleaveswithanother,eacheyefixationwillfallintoasingleAOI.
2.4.3.1DeterminingAOICoordinatesofSentences. TheeasiestwaytodeterminethecoordinatesofanyAOIistodescribeitasasetofrectangles(see Fig. 5).Doingsowillensuresmootherimplementationofthealgorithmthatwill findthescanpathstring.AnyrectangularAOIcanbedescribedby2points. Theupper-leftcornerandthelower-rightcornerpointsareusedheretodescribe eachAOI.AsingleAOIcouldbedescribedbymultiplerectanglesasinthecase oftheAOIAandAOIBinFig. 5
Fig.5. RepresentingtheAOIofthesentencesasasetofrectangles.AnAOIcan beacombinationofmultiplerectangleslikeAOIAwhichisacombinationoftwo rectangles:thefirstrectanglehasthecoordinates(476,155)and(1508,262)andthe secondrectanglehasthecoordinates(476,262)and(1096,372)
2.4.3.2FindingtheScanpathStringofSentences. Afterdeterminingthecoordinatesoftherectanglesthatspecifyallthesentences’AOIs,ascriptwillbe
executedtodeterminethescanpathstringforeachsetofeyefixations.The ScanpathFinder scriptgoesthroughtheeyefixationsonebyoneanddeterminesto whichAOI(orAOIs)eacheyefixationpointbelongs.Todeterminewhetheran eyefixationpointthatisrepresentedby(x, y )iswithinanAOIrepresentedby (xul , yul )and(xlr , ylr ),thefollowingBooleanvalueiscalculated:
Thevalueof d is true whentheeyefixationpointisinsidetheAOIoronits boundary,anditis false whentheeyefixationpointisoutsidetheAOI.Figure 6 illustratestheideapictorially.
Fig.6. DeterminingifaneyefixationpointisinsidetheAOIrepresentedby(xul ,yul ) =(476,262)and(xlr ,ylr )=(1096,372):(a)illustratesaneyefixationwithcoordinates (x, y )=(615,325)thatresidesinsidetheAOIand(b)illustratesaneyefixationwith coordinates(x, y )=(1200,325)thatresidesoutsidetheAOI
2.4.3.3DeterminingAOICoordinatesofWords. Inordertobuildthescanpath stringatalowerlevelofgranularity,i.e.,tothewordslevel,theboundingboxfor eachwordmustbedetermined.Sincethereare69wordsinthemedicalparagraph (Fig. 1),itwillbetediousanderror-pronetomanuallyfindthecoordinatesof eachworkAOI.Tomaketheprocesssystematicandlesssusceptibletoerrors, the WordsBoundingBoxCoordinatesFinder scripthasbeenimplemented.This Matlabscripshowsthestimuli,whichisinourcasethemedicalparagraph,inthe samedimensionsasitwouldappeartotheparticipant.Inorderforthescriptto generatethecoordinatesoftheAOIsofthewords,theuserofthescriptneeds firsttomovethemousecursortotherightthentotheleftboundaryofthe stimuliandclick.Thisstepwillrecordthex-coordinatesoftheleftandright boundaryofthestimulithatwillbeusedinthesubsequentstepstodetermine thecoordinatesoftheboundaryboxesofthoseAOIsthatfallontheleftand
rightedgesofthestimuli.Second,theuserofthescriptisrequiredtomovethe mousecursorverticallyandclickontheboundaryofeachlinestartingfromthe upperboundaryofthefirstlineandendingwiththelowerboundaryofthelast line.Thisstepwillrecordthey-coordinatesoftheboundaryboxesthatwillbe definedinthenextstep.Nowthattheleftandrightboundaryofthestimulias wellastheboundaryofeachrowhasbeencaptured,theuserofthescriptneeds togooverthetextandclickontheimaginarymiddleverticallineboundary betweeneachtwowords.
Theimaginarymiddleverticallineboundarybetweenanytwowordsisshown asadashedlineinFig. 7.TheuserofthescriptneedstohitanEnter/Return afterclickingontheboundarybetweenthelasttwowordsineachline.When theuserofthescriptreachesthelastlineandfollowsthatwithanEnter/Return click,thescriptwillgeneratethecoordinatesoftheAOIswiththeirlabels.The labelsoftheseAOIsarebasedonearlierinformationprovidedtothescriptabout thenameofeachparagraphAOIandthenumberofwordsitcontains.
2.4.3.4FindingtheScanpathStringofWords. Findingthescanpathstringofthe wordsfollowsexactlythesameprocedurementionedinSect.2.4.3.2.However, thealgorithmisprovidedwiththecoordinatesoftheAOIs’boundingboxesof thewordsinsteadoftheAOI’sboundingboxesofthesentences.
2.5Results
Theprocessofdeterminingtheeyefixationsfromtherawgazedatahasbeen testedononeparticipantandtheresultisdiscussedinSect. 2.5.1.Thescanpath stringsbasedonthesentenceslevelispresentedinSection 2.5.2 andbasedon thewordslevelispresentedinSect. 2.5.3
Fig.7. Illustrationoftheboundingboxesofthewords’AOIs
2.5.1DeterminingtheEyeFixations TheI-DTalgorithmhasbeenexecuted12times,usingallthepossiblecombinationsoftheselectedvaluesforthedispersionanddurationthresholds.Areading taskofashortmedicalparagraph(Fig. 1)thatconsistsofatotalof69words hasbeengiventooneparticipanttocollecttherawgazedataanduseinthe I-DTalgorithm.
Figure 8 showstheeyefixationsgeneratedbytheI-DTalgorithmusingthe differentvaluesforthedurationthresholdbutkeepingthedispersionthreshold fixedto0.4◦ .Similarly,Fig. 9 andFig. 10 showtheeyefixationsgeneratedby theI-DTalgorithmwiththedifferentvaluesofthedurationthresholdbutfixing thedispersionthresholdto0.5◦ and0.6◦ ,respectively.Table 2 summarizesthe numberofeyefixationsgeneratedbytheI-DTalgorithmunderthedifferent settings.Generally,thenumberofeyefixationsmonotonicallydecreasesasthe durationthresholdvalueincreases.Thenumberofeyefixationsunderdifferent valuesofthedurationthresholdtendstobelessthanforthosewithhigher dispersionthresholdvalueasshowninFig. 11.
Table2. SummaryofthenumberofeyefixationsgeneratedbytheI-DTalgorithm underthedifferentsettings
Fig.8. TheeyefixationsgeneratedbytheI-DTalgorithmusingadispersionthreshold valueof0.4◦ andthedifferentdurationthresholdvalues
Fig.9. TheeyefixationsgeneratedbytheI-DTalgorithmusingadispersionthreshold valueof0.5◦ andthedifferentdurationthresholdvalues
Fig.10. TheeyefixationsgeneratedbytheI-DTalgorithmusingadispersionthreshold valueof0.6◦ andthedifferentdurationthresholdvalues
