Motor imagery based BCI for a maze game

Abstract

Electroencephalogram (EEG) signals generated out of motor imagery (MI) can be used for Brain Computer Interfacing (BCI). In order to accomplish this goal, we have classified four different MI tasks using two hybrid features of bispectrum of EEG through a RBF kernel support vector machine. As a demonstration of its applicability for a non-invasive BCI, we design and develop a BCI maze game, where a player plays the game in real time using his brain signals.