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  • Title: Canonical correlation analysis applied to remove muscle artifacts from the electroencephalogram.
    Author: De Clercq W, Vergult A, Vanrumste B, Van Paesschen W, Van Huffel S.
    Journal: IEEE Trans Biomed Eng; 2006 Dec; 53(12 Pt 1):2583-7. PubMed ID: 17153216.
    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.
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