Ocular Artifact Removal from EEG Using Stationary Wavelet Enhanced ICA
نویسنده
چکیده
To analyze EEG accurately, it is necessary to remove artifacts from EEG, which gets coupled with signal at the time of recording and can’t be eliminated at preprocessing stage. Ocular artifact is most obvious artifact in EEG. In this paper, a new method using Stationary Wavelet Enhanced Independent Component Analysis with a novel thresholding, is proposed for ocular artifact removal from EEG. Proposed method incorporates strengths of Stationary Wavelet and Independent Component Analysis. Limitations of these method are minimized by using proposed novel thresholding technique, which is proved by results. Proposed denoising method with novel thresholding technique is analyzed in terms of correlation coefficient and mutual information. Superiority of proposed method is also proved by measuring frequency domain coherence between raw EEG data and noise free EEG data.
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