School of Biomedical Engineering, Science, & Health Systems

Stephen Abbate

School of Biomedical Engineering, Science, & Health Systems

Biomedical Engineering

Faculty Mentor: Dr. Hasan Ayaz

Biomedical Engineering

Adrian Curtain Co-Mentor

Electromyography-based controller that allows for seamless human-computer interaction

Human-computer interaction is becoming an increasingly integral part of society, thus causing a push new methods of interaction. The following project’s goal was to design a device that employs Electromyography (EMG) to measure muscle signals in order to act as a computer controller. EMG refers to the process of measuring changes in muscle cell’s electrical potential resulting from contraction. An Olimex EKG Arduino shield was used to amplify low muscular signals to the 0-5V range, suitable for an Arduino Uno to digitize. In order to act as a controller, the system must analyze the live data to find indications that a specific gesture was performed. This was done by identifying specific frequencies, using Matlab’s FFT function, that correspond to different gestures. Iterative testing showed placing surface electrodes on the forearm and one ground on the elbow, produced the most distinct waveforms. Also, a 1 MB circular buffer was designed to store incoming data while previous data is being analyzed by the Matlab, guaranteeing that no data points are lost. Overall, the project successfully operates as a basic computer controller and provides opportunity for implementation in medical devices, such as for prosthetic control.