An Eye-Controlled Wheelchair: Design of a Novel Human-Computer Interface(HCI) for Patients with Motor Neuron Disease

By 2025, approximately 65 million people will be users of Electric Power Wheelchairs(EPW’s), which significantly boost quality of life(NCBI). However, a challenge gone undocumented in academic research is that many patients are unable to use EPW joysticks due to a variety of impairments in motor function, sensation, or cognition. Therefore, it was decided that an EOG(electrooculography)-based mobility aid would allow users to control the wheelchair via eye signals collected from a pair of glasses consisting of 3 electrodes placed on the outer canthi and left mastoid. Signals were filtered using a 0.5 - 19.5 Hertz Butterworth filter, and interpreted by an adaptive thresholding detection algorithm. Wheelchair construction involved conversion of a manual wheelchair to motorized. The three subsystems, sensing, interpretation, and movement, were individually and holistically examined to conclude that the final product achieved a signal detection accuracy rate of ~89%, and ultimately achieved its goal of being the first everyday, cost-effective alternative to traditional EPW's.