Title :
xDAWN Algorithm to Enhance Evoked Potentials: Application to Brain–Computer Interface
Author :
Rivet, Bertrand ; Souloumiac, Antoine ; Attina, Virginie ; Gibert, Guillaume
Author_Institution :
GIPSA Lab., Grenoble Inst. of Technol., Grenoble, France
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.
Keywords :
Bayes methods; bioelectric potentials; brain-computer interfaces; electroencephalography; medical disorders; medical signal processing; signal classification; spatial filters; unsupervised learning; Bayesian linear discriminant analysis classifier; EEG signal; P300 speller BCI paradigm; brain activity; brain-computer interface; evoked potential; neuromuscular disorder; spatial filter; unsupervised algorithm; xDAWN algorithm; Application software; Bayesian methods; Brain computer interfaces; Communication system control; Computer interfaces; Control systems; Electroencephalography; Laboratories; Linear discriminant analysis; Spatial filters; Stochastic processes; Brain–computer interface (BCI); P300 speller; spatial enhancement; xDAWN algorithm; Adult; Algorithms; Artificial Intelligence; Brain; Electroencephalography; Evoked Potentials; Humans; Male; Man-Machine Systems; Signal Processing, Computer-Assisted;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.2009.2012869