P300 Speller brain-computer interface: enhancement of P300 evoked potential by spatial filters P300

Bertrand Rivet (1) , Antoine Souloumiac (2) , Guillaume Gibert (3) , Virginie Attina (3)

1 GIPSA-MPACIF - GIPSA - Machines Parlantes, Agents Communicants & Interaction Face-à-face
2 LOAD (CEA, LIST) - Laboratoire Outils d'Analyse des Données (CEA, LIST)
3 Dynamique Cérébrale et Cognition

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.

Keywords: Spectrum analysis; Bayesian linear discriminant analysis; spatial filter; unsupervised algorithm; EEG; electroencephalography; signal processing; statistical analysis; BCI; Brain-Computer Interface

Domains: Signal and Image processing; Methodology [stat.ME]; Neurons and Cognition [q-bio.NC]

Bertrand Rivet, Antoine Souloumiac, Guillaume Gibert, Virginie Attina. P300 Speller brain-computer interface: enhancement of P300 evoked potential by spatial filters P300. EUSIPCO 2008 - 16th European Signal Processing Conference, Aug 2008, Lausanne, Switzerland. ⟨hal-00315815⟩