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Subject-independent mental state classification in single trials

: Fazli, S.; Popescu, F.; Danoczy, M.; Blankertz, B.; Müller, K.-R.; Grozea, C.


Neural Networks 22 (2009), No.9, pp.1305-1312
ISSN: 0893-6080
Journal Article
Fraunhofer FIRST ()

Current state-of-the-art in Brain computer Interfacing (BCI) involves tuning classifiers to subject-specific training data acquired from calibration sessions prior to functional BCI use Using a large database of EEG recordings from 45 subjects, who took part in movement imagination task experiments. we Construct an ensemble of classifiers derived from subject-specific temporal and spatial filters. The ensemble is then sparsified using quadratic regression with l(1) regularization such that the final classifier generalizes reliably to data of subjects not included in the ensemble Our offline results indicate that BCI-naive users Could start real-time BCI use Without any prior calibration at only very limited loss of performance.