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 outperformed 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