Mouse Pointer Controlled by Ocular Movements

Researchers oil Brain-Computer Interface (BCI) have tried to identify the origin of body movements in humans with limited success. This work looks at the problem using an ocular movement tracker based on ocular artifacts in electroencephalograph (EEG) readings, also called electro-oculogram (FOG). The movements are reflected into the EEG signals, which are passed through a multiple classifier, composed of two statistical classic methods (KNN and Bayesian-Gauss) and a Neural Network. The voltage levels of the EEG readings and their polarity provide the necessary information to track the focus of attention of the user in a computer screen. All of these artifacts have characteristic Curves which can be classified. Focusing on the eye movements, we have developed an eye tracker to recover the point of attention of the user on a computer screen.