Geometric subspace methods and time-delay embedding for EEG artifact removal and classification.

Charles W Anderson; James N Knight; Tim O'Connor; Michael J Kirby; Artem Sokolov

doi:10.1109/tnsre.2006.875527

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Geometric subspace methods and time-delay embedding for EEG artifact removal and classification.

Charles W Anderson·James N Knight·Tim O'Connor·Michael J Kirby·Artem Sokolov

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Abstract

Generalized singular-value decomposition is used to separate multichannel electroencephalogram (EEG) into components found by optimizing a signal-to-noise quotient. These components are used to filter out artifacts. Short-time principal components analysis of time-delay embedded EEG is used to represent windowed EEG data to classify EEG according to which mental task is being performed. Examples are presented of the filtering of various artifacts and results are shown of classification of EEG from five mental tasks using committees of decision trees.

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Algorithms Artifacts Brain Communication Devices for People with Disabilities Electroencephalography Evoked Potentials Humans Man-Machine Systems Pattern Recognition, Automated User-Computer Interface Evaluation Study Journal Article Research Support, U.S. Gov't, Non-P.H.S.

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Charles W Anderson, James N Knight, Tim O'Connor, Michael J Kirby, Artem Sokolov. 2006. Geometric subspace methods and time-delay embedding for EEG artifact removal and classification.. https://doi.org/10.1109/tnsre.2006.875527

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