Improving braincomputer interface classification using adaptive common spatial patterns
An adaptive common spatial patterns method is proposed for EEG spatial filtering. The method is evaluated for intra- and inter-subject classifications. The method is compared to existing techniques and shows superior performance. The effects of adding misclassified trials to training data are investigated. The method is potentially applicable to various real-time BCI tasks.
braincomputer interface adaptive common spatial patterns electroencephalography nonstationarity