A MULTISOURCES ELECTRIC WHEELCHAIR CONTROL BASED ON EEG SIGNALS AND FUZZY EYE TRACKING FUSION

Many persons with severe motor handicap are unable to use the manually operated electric-powered wheelchair (EPW) to gain their autonomy. As a consequence, some works propose alternative control techniques that replace the EPW manual command using a joystick, with more suitable techniques such as eye tracking and brain signals. Although such techniques are handicapped friendly, they suffer from many disadvantages when applied separately such as the high error rate and lack of the security constraint satisfaction. To tackle this problem, we propose, in this paper, a technique for wheelchair command using data fusion between EEG signals and a fuzzy logic eye tracker. As a single technique, the EEG signals convert the user's face expression to navigation command and the eye tracker system captures the user's gaze via the pc webcam, then the fuzzy controller decides about the user's gaze. The fusion of these subsystems achieves a success rate of 93% according to our experiments.