DocumentCode :
992686
Title :
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
Link To Document :
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