xDAWN Algorithm to Enhance Evoked Potentials: Application to Brain-Computer Interface

被引：351

作者：

Rivet, Bertrand ^{[1
,2
]}

Souloumiac, Antoine ^{[2
]}

Attina, Virginie ^{[3
,4
,5
]}

Gibert, Guillaume ^{[3
,4
,5
]}

机构：

[1] CNRS, GIPSA Lab, UMR 5216, Grenoble Inst Technol, F-38000 Grenoble, France

[2] CEA, LIST, Stochast Proc & Spectra Lab, F-91191 Gif Sur Yvette, France

[3] INSERM, Natl Inst Hlth & Med Res, F-69500 Lyon, France

[4] Inst Federatif Neurosci IFR 19, F-69000 Lyon, France

[5] Univ Lyon 1, F-69500 Lyon, France

来源：

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING | 2009年 / 56卷 / 08期

关键词：

Brain-computer interface (BCI); P300; speller; spatial enhancement; xDAWN algorithm; BCI COMPETITION 2003; MENTAL PROSTHESIS; SEPARATION; ENSEMBLE;

D O I：

10.1109/TBME.2009.2012869

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

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 [1]. 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 [2], show that the proposed method is efficient and accurate.

引用

页码：2035 / 2043

页数：9

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