EEG artifact elimination by extraction of ICA-component features using image processing algorithms

[Display omitted] •Machine-driven EEG artifact removal through automated selection of ICs is proposed.•Feature vectors extracted from IC via image processing algorithms are used.•LDA classification identifies range filter as powerful feature (accuracy rate 88%).•The method does not depend on direct...

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Veröffentlicht in:	Journal of neuroscience methods Jg. 243; S. 84 - 93
Hauptverfasser:	Radüntz, T., Scouten, J., Hochmuth, O., Meffert, B.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Netherlands Elsevier B.V 30.03.2015
Schlagworte:	Adult Algorithms Artifact elimination Brain - physiology Discriminant Analysis EEG Electroencephalography - methods Executive Function - physiology Female Geometric features Humans ICA Image processing Image Processing, Computer-Assisted - methods Independent component analysis Linear Models Local binary patterns Male Middle Aged Pattern Recognition, Automated - methods Range filter Signal Processing, Computer-Assisted Signal-To-Noise Ratio 68U99 68U10 68T10 Image processing ICA EEG Independent component analysis Artifact elimination 92C55 Geometric features Local binary patterns Range filter 68-04 92C50
ISSN:	0165-0270, 1872-678X, 1872-678X
Online-Zugang:	Volltext
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