BCI Competition 2003—Data Set IIb: Enhancing P300 Wave Detection Using ICA-Based Subspace Projections for BCI Applications

N. Xu, X. Gao, B. Hong, X. Miao, S. Gao, F. Yang
2004 IEEE Transactions on Biomedical Engineering  
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. Index Terms-Brain-computer interface (BCI), independent component analysis, infomax, P300 detection.
doi:10.1109/tbme.2004.826699 pmid:15188880 fatcat:audyc4jckrg35bkgx2mqgz7xzy