A new muscle artifact removal technique to improve the interpretation of the ictal scalp electroencephalogram.
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 technique (BSS). This method is demonstrated on a synthetic data set. The method out-performed a low pass filter with different cutoff frequencies and an Independent Component Analysis (ICA) based technique for muscle artifact removal. The first preliminary results of a clinical study on 26 ictal EEGs of patients with refractory epilepsy illustrated that the removal of muscle artifact results in a better interpretation of the ictal EEG, leading to an earlier detection of the seizure onset and a better localization of the seizures onset zone. These findings make the current method indispensable for every Epilepsy Monitoring Unit.
De Clercq
Wim
W
Department of Electrical Engineering (ESAT/SCD), Katholieke Universiteit Leuven, Leuven, Belgium. E-mail: wim.declercq@esat.kuleuven.ac.be.
Vergult
Anneleen
A
Vanrumste
Bart
B
Van Hees
Johan
J
Palmini
Andre
A
Van Paesschen
Wim
W
Van Huffel
Sabine
S