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Spatiotemporal Representations of Rapid Visual Target Detection: A Single-Trial EEG Classification Algorithm
2014
IEEE Transactions on Biomedical Engineering
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Brain Computer Interface applications, developed for both healthy and clinical populations, critically depend on decoding brain activity in single trials. The goal of the present study was to detect distinctive spatio-temporal brain patterns within a set of event related responses. We introduce a novel classification algorithm, the Spatially Weighted FLD-PCA (SWFP), which is based on a 2-step linear classification of event-related responses, using Fisher Linear Discriminant (FLD) classifier and
doi:10.1109/tbme.2013.2289898
pmid:24216627
fatcat:6lidvdp2gfe77dcrptk5lbcpjm