### 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 language | English |
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Title of host publication | Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference |

Publication status | Published - 2009 |

Event | 21st Annual Conference on Neural Information Processing Systems, NIPS 2007 - Vancouver, BC, Canada Duration: 2007 Dec 3 → 2007 Dec 6 |

### Publication series

Name | Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference |
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### Other

Other | 21st Annual Conference on Neural Information Processing Systems, NIPS 2007 |
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Country | Canada |

City | Vancouver, BC |

Period | 07/12/3 → 07/12/6 |

### ASJC Scopus subject areas

- Information Systems

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## Cite this

*Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference*(Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference).