title: Geometric subspace methods and time-delay embedding for EEG artifact removal and classification.
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.
authors.affiliation: Department of Computer Science, Colorado State University, Fort Collins, CO 80523, USA. anderson@cs.colostate.edu
authors.forename: Charles W
authors.initials: CW
authors.lastname: Anderson
authors.forename: James N
authors.initials: JN
authors.lastname: Knight
authors.forename: Tim
authors.initials: T
authors.lastname: O'Connor
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Kirby
authors.forename: Artem
authors.initials: A
authors.lastname: Sokolov
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001921:Brain / Q000502:physiology*; D003143:Communication Devices for People with Disabilities; D004569:Electroencephalography / Q000379:methods*; D005071:Evoked Potentials / Q000502:physiology*; D006801:Humans; D008328:Man-Machine Systems; D010363:Pattern Recognition, Automated / Q000379:methods*; D014584:User-Computer Interface