Pattern Recognition of EEG Signals during Right and Left Motor Imagery based on Quasi-AR Model

Abstract

A system which transforms signals from the brain into control signals is known as a brain-computer interface (BCI). Classification of EEG signals is a difficult task, especially when the derived classification result is to be used to control an electronic device, because in this case the classification has to be performed on a single-trial basis (i.e. not averaged).

In this paper, statistical pattern recognition method based on Quasi-AR model is introduced and is applied to discriminate the EEG signals during right and left motor imagery.