A multimodal wheelchair control system based on EEG signals and Eye tracking fusion

Abstract

Controlling an electric powered wheelchair (EPW) is not always a simple task for certain types of disabled person. For example, persons suffering from the locked in syndrome or ALS. Many researchers use the eye tracking or the brain signals as alternative ways to control the EPW. The goal of this paper is to illustrate the EPW control performance amelioration when using multi sources compared to single source control. The first part is to elaborate separate control techniques using ElectroEncephalography (EEG) then eye tracking technologies. The second part, is combining these techniques using data fusion algorithms. Finally, testing the control performance with EEG, Eye tracking and EEG/Eye tracking.