Controlling a Wheelchair by Use of EOG Signal

Abstract

In this paper EOG signal processing and developing a low cost signal interface for wheelchair with high accuracy and reliability for severely disabled people is presented. Here the signal processing is done on a microcontroller which reduces the cost drastically rather than using a computer. Eye movement is detected by processing EOG signal, and associates the eye movement to motion commands of the wheelchair such as forward, reverse, left and right. A 99% accurate classification has been demonstrated experimentally.

Online classification algorithm for eye-movement-based communication systems using two temporal EEG sensors

“…A number of human-machine interfaces (HMIs) have been based on electrooculography (EOG) signals to detect and classify eye movements [13][14][15][16][17][18][19][20], because EOG is a simple and easy method to measure eye movement. However, EOG would be inappropriate for some applications, such as driving a car [21], which would reduce the field of vision.…”

Guiding Wheelchair Motion Based on EOG Signals Using Tangent Bug Algorithm

“…While other researches has focused on Human Computer Interfaces (HCI) based on EOG signals, where the user will be allowed to perform other simple tasks beside wheelchair motion control [14]. Although, only few focused on using EOG signals solely to control the wheelchair [15] and [16].…”

Eye-tracking capabilities of low-cost EOG system

“…Eye-tracking systems are used in many applications, such as gaze tracking studies [1], PC interaction for people with disabilities [2], [3], [4], controlling a wheelchair [5], [6], entertainment and games, operators interfaces, etc. Currently, there are different methods to track gaze direction, with varying difficulty and cost.…”