Increase Information Transfer Rates in BCI by CSP Extension to Multi-class

Part of Advances in Neural Information Processing Systems 16 (NIPS 2003)

Bibtex Metadata Paper


Guido Dornhege, Benjamin Blankertz, Gabriel Curio, Klaus-Robert Müller


Brain-Computer Interfaces (BCI) are an interesting emerging technology that is driven by the motivation to develop an effective communication in- terface translating human intentions into a control signal for devices like computers or neuroprostheses. If this can be done bypassing the usual hu- man output pathways like peripheral nerves and muscles it can ultimately become a valuable tool for paralyzed patients. Most activity in BCI re- search is devoted to finding suitable features and algorithms to increase information transfer rates (ITRs). The present paper studies the implica- tions of using more classes, e.g., left vs. right hand vs. foot, for operating a BCI. We contribute by (1) a theoretical study showing under some mild assumptions that it is practically not useful to employ more than three or four classes, (2) two extensions of the common spatial pattern (CSP) algorithm, one interestingly based on simultaneous diagonalization, and (3) controlled EEG experiments that underline our theoretical findings and show excellent improved ITRs.