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Invariant Common Spatial Patterns: Alleviating Nonstationarities in Brain-Computer Interfacing
Benjamin Blankertz · Motoaki Kawanabe · Ryota Tomioka · Friederike Hohlefeld · Vadim Nikulin · Klaus-Robert Müller

Wed Dec 05 05:20 PM -- 05:30 PM (PST) @ None

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 Raleigh 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 alpha-activity. In other words, the EEG decoding still works when there are lapses in vigilance.

Author Information

Benjamin Blankertz (Berlin Institute of Technology)
Motoaki Kawanabe (Fraunhofer FIRST)
Ryota Tomioka (Microsoft Research Cambridge)
Friederike Hohlefeld
Vadim Nikulin
Klaus-Robert Müller (TU Berlin)

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