title: xDAWN algorithm to enhance evoked potentials: application to brain-computer interface.
abstract: A brain-computer interface (BCI) is a communication system that allows to control a computer or any other device thanks to the brain activity. The BCI described in this paper is based on the P300 speller BCI paradigm introduced by Farwell and Donchin . An unsupervised algorithm is proposed to enhance P300 evoked potentials by estimating spatial filters; the raw EEG signals are then projected into the estimated signal subspace. Data recorded on three subjects were used to evaluate the proposed method. The results, which are presented using a Bayesian linear discriminant analysis classifier , show that the proposed method is efficient and accurate.
authors.affiliation: GIPSA Laboratory, Centre National de la Recherche Scientifique (CNRS) Unité Mixte de Recherche (UMR), Grenoble, France. bertrand.rivet@gipsa-lab.inpg.fr
authors.forename: Bertrand
authors.initials: B
authors.lastname: Rivet
authors.forename: Antoine
authors.initials: A
authors.lastname: Souloumiac
authors.forename: Virginie
authors.initials: V
authors.lastname: Attina
authors.forename: Guillaume
authors.initials: G
authors.lastname: Gibert
mesh_terms: D000328:Adult; D000465:Algorithms; D001185:Artificial Intelligence; D001921:Brain / Q000502:physiology*; D004569:Electroencephalography / Q000379:methods*; D005071:Evoked Potentials / Q000502:physiology*; D006801:Humans; D008297:Male; D008328:Man-Machine Systems; D012815:Signal Processing, Computer-Assisted