Spatio-temporal linear decoding of brain state: Application to performance augmentation in high-throughput tasks

L. Parra, C. Christoforou, Adam Gerson, Mads Dyrholm, An Luo, M. Wagner, Paul Sajda

This review summarizes linear spatiotemporal signal analysis methods that derive their power from careful consideration of spatial and temporal features of skull surface potentials. BCIs offer tremendous potential for improving the quality of life for those with severe neurological disabilities. At the same time, it is now possible to use noninvasive systems to improve performance for time-demanding tasks. Signal processing and machine learning are playing a fundamental role in enabling applications of BCI and in many respects, advances in signal processing and computation have helped to lead the way to real utility of noninvasive BCI.

Accepted 26 December 2007
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