“P300 speller” Brain-Computer Interface: Enhancement of P300 evoked potential by spatial filters

Abstract

Brain-Computer Interfaces (BCI) are communication systems that use brain activity to control a computer or other devices. The BCI system described in this study is based on the P300 speller BCI paradigm designed by Farwell an Donchin in 1988 [1]. A new unsupervised algorithm is proposed in this paper1. It is based on the projection of the raw EEG signal into the estimation of the P300 subspace. In this algorithm, brain responses to the target stimuli and to the non target stimuli are taken into account. They provide a better estimation of the P300 subspace main components. Data recorded on three subjects were used to evaluate the proposed method. The results are presented using a Bayesian linear discriminant analysis (BLDA) classifier.