Development of an EOG Classification System for SCI Prosthetic Hand Movement
By Fawzan Hussain
Senior Category (Grades 11-12)
Study | Big Data / AI, Biology, Engineering and Computer Science
In 2016, it was estimated that over 85,556 people live with a Spinal Cord Injury (SCI). People with Spinal Cord Injuries (SCI) often struggle to move certain muscle groups and overcome barriers for comfortable living. Through using an Electrooculogram (EOG)- based Human Computer Interface (HCI), people with SCI can use their eye movements and blinking patterns to comfortably control things such as a robotic hand. This led the researcher to obtain EOG signals from volunteers and see if there are any correlations between the data using machine learning. The researcher found that the Machine Learning Algorithm consistently predicted the ‘Left Movement’, regardless of the input. This demonstrates that with more datapoints, these signals can be used as a novel method to potentially control a robotic hand.
