A new muscle artifact removal technique to improve the interpretation of the ictal scalp electroencephalogram

Wim De Clercq; Anneleen Vergult; Bart Vanrumste; Johan Van Hees; Andre Palmini; Wim Van Paesschen; Sabine Van Huffel

doi:10.1109/IEMBS.2005.1616571

A new muscle artifact removal technique to improve the interpretation of the ictal scalp electroencephalogram

Conf Proc IEEE Eng Med Biol Soc. 2005:2006:944-7. doi: 10.1109/IEMBS.2005.1616571.

Authors

Wim De Clercq¹, Anneleen Vergult, Bart Vanrumste, Johan Van Hees, Andre Palmini, Wim Van Paesschen, Sabine Van Huffel

Affiliation

¹ Department of Electrical Engineering (ESAT/SCD), Katholieke Universiteit Leuven, Leuven, Belgium. E-mail: [email protected].

PMID: 17282340
DOI: 10.1109/IEMBS.2005.1616571

Abstract

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.