Invariant common spatial patterns: Alleviating nonstationarities in Brain-Computer Interfacing

Benjamin Blankertz, Motoaki Kawanabe, Ryota Tomioka, Friederike U. Hohlefeld, Vadim Nikulin, Klaus Robert Müller

Research output: Chapter in Book/Report/Conference proceedingConference contribution

135 Citations (Scopus)

Abstract

Brain-Computer Interfaces can suffer from a large variance of the subject conditions within and across sessions. For example vigilance fluctuations in the individual, variable task involvement, workload etc. alter the characteristics of EEG signals and thus challenge a stable BCI operation. In the present work we aim to define features based on a variant of the common spatial patterns (CSP) algorithm that are constructed invariant with respect to such nonstationarities. We enforce invariance properties by adding terms to the denominator of a Rayleigh coefficient representation of CSP such as disturbance covariance matrices from fluctuations in visual processing. In this manner physiological prior knowledge can be used to shape the classification engine for BCI. As a proof of concept we present a BCI classifier that is robust to changes in the level of parietal α-activity. In other words, the EEG decoding still works when there are lapses in vigilance.

Original languageEnglish
Title of host publicationAdvances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference
Publication statusPublished - 2009
Externally publishedYes
Event21st Annual Conference on Neural Information Processing Systems, NIPS 2007 - Vancouver, BC, Canada
Duration: 2007 Dec 32007 Dec 6

Publication series

NameAdvances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference

Other

Other21st Annual Conference on Neural Information Processing Systems, NIPS 2007
Country/TerritoryCanada
CityVancouver, BC
Period07/12/307/12/6

ASJC Scopus subject areas

  • Information Systems

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