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

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

doi:10.1109/TBME.2004.826699

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

IEEE Trans Biomed Eng. 2004 Jun;51(6):1067-72. doi: 10.1109/TBME.2004.826699.

Authors

Neng Xu¹, Xiaorong Gao, Bo Hong, Xiaobo Miao, Shangkai Gao, Fusheng Yang

Affiliation

¹ Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China. [email protected]

PMID: 15188880
DOI: 10.1109/TBME.2004.826699

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.

Publication types

Comparative Study
Evaluation Study
Research Support, Non-U.S. Gov't
Validation Study

MeSH terms

Algorithms*
Artificial Intelligence*
Brain / physiology*
Cognition / physiology*
Computer Peripherals
Databases, Factual
Electroencephalography / classification
Electroencephalography / methods*
Event-Related Potentials, P300 / physiology*
Humans
Pattern Recognition, Automated
Principal Component Analysis
Reproducibility of Results
Sensitivity and Specificity
Signal Processing, Computer-Assisted
User-Computer Interface*
Word Processing