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Title: Canonical correlation analysis applied to remove muscle artifacts from the electroencephalogram
Authors: De Clercq, Wim ×
Vergult, Anneleen
Vanrumste, Bart
Van Paesschen, Wim
Van Huffel, Sabine #
Issue Date: Dec-2006
Publisher: Institute of Electrical and Electronics Engineers
Series Title: IEEE Transactions on Biomedical Engineering vol:53 issue:12 Pt 1 pages:2583-2587
Abstract: The electroencephalogram (EEG) is often contaminated by muscle artifacts. In this paper, a new method for muscle artifact removal in EEG is presented, based on canonical correlation analysis (CCA) as a blind source separation (BSS) technique. This method is demonstrated on a synthetic data set. The method outperformed a low-pass filter with different cutoff frequencies and an independent component analysis (ICA)-based technique for muscle artifact removal. In addition, the method is applied on a real ictal EEG recording contaminated with muscle artifacts. The proposed method removed successfully the muscle artifact without altering the recorded underlying ictal activity.
ISSN: 0018-9294
Publication status: published
KU Leuven publication type: IT
Appears in Collections:ESAT - STADIUS, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics
Research Group Experimental Neurology
Laboratory for Epilepsy Research
Technologiecluster ESAT Elektrotechnische Engineering
Electrical Engineering (ESAT) TC, Technology Campus Geel
Electrical Engineering (ESAT) TC, Technology Campus Diepenbeek
× corresponding author
# (joint) last author

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