BCI competition 2003-data set IIb: enhancing P300 wave detection using ICA-based subspace projections for BCI applications

Author

Xu, Neng ; Gao, Xiaorong ; Hong, Bo ; Miao, Xiaobo ; Gao, Shangkai ; Yang, Fusheng

Author_Institution

Dept. of Biomed. Eng., Tsinghua Univ., Beijing, China

Volume

51

Issue

6

fYear

2004

fDate

6/1/2004 12:00:00 AM

Firstpage

1067

Lastpage

1072

Abstract

An algorithm based on independent component analysis (ICA) is introduced for P300 detection. After ICA decomposition, P300-related independent components are selected according to the a priori knowledge of P300 spatio-temporal pattern, and clear P300 peak is reconstructed by back projection of ICA. Applied to the dataset IIb of BCI Competition 2003, the algorithm achieved an accuracy of 100% in P300 detection within five repetitions.

Keywords

electroencephalography; handicapped aids; independent component analysis; medical signal detection; medical signal processing; spatiotemporal phenomena; BCI Competition 2003; BCI applications; ICA-based subspace projections; P300 spatio-temporal pattern; P300 wave detection; back projection; independent component analysis; Biomedical engineering; Discrete wavelet transforms; Electrocardiography; Electroencephalography; Enterprise resource planning; Humans; Independent component analysis; Magnetic analysis; Scalp; Signal processing algorithms; Algorithms; Artificial Intelligence; Brain; Cognition; Computer Peripherals; Databases, Factual; Electroencephalography; Event-Related Potentials, P300; Humans; Pattern Recognition, Automated; Principal Component Analysis; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; User-Computer Interface; Word Processing;

fLanguage

English

Journal_Title

Biomedical Engineering, IEEE Transactions on

Publisher

ieee

ISSN

0018-9294

Type

jour

DOI

10.1109/TBME.2004.826699

Filename

1300804