A Critical Review on the Usage of Ensembles for BCI

Abstract

This chapter presents an up-to-date literature review on ICA in BCI applications by categorizing related studies into three classes (i.e., artifact removal, SNR en- hancement of task-related EEG signals, and electrode selection) according to the roles of ICA. The basic principles and methodologies behind these applications have been fully illustrated through examples with real EEG data. This chapter also describes an extended application of the ICA-based spatial filter in the develop- ment of a zero-training method for a motor imagery-based BCI. In summary, this chapter shows that ICA can make a substantial contribution to the practical design of BCI systems.