The application of Independent Component Analysis in the pattern extraction of Mental EEG
Daoxin Zhang · Microcomputer Development · 2002
ICA is applied to the mental EEG signal analysis. In one side, our experiment results show that ICA can effectively detect, separate and remove a wide variety of artefacts from EEG recordings. For another, the ICA algorithm is used to the pattern extraction of mental EEG signals from different mental tasks. By studying the EEG independent sources and their projection on human scalp, we can find that some steady independent components always appear when the subject repeats the same mental tasks. The results will provide us a promising method in the classification of mental tasks and the research on Brain-Computer Interface(BCI) technology.