Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article A Novel Semiblind Signal Extraction Approach for the Removal of Eye-Blink Artifact from EEGs | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2008 Article ID 857459 12 pages doi 2008 857459 Research Article A Novel Semiblind Signal Extraction Approach for the Removal of Eye-Blink Artifact from EEGs Kianoush Nazarpour 1 Hamid R. Mohseni 1 Christian W. Hesse 2 Jonathon A. Chambers 3 and Saeid Sanei1 1 Centre of Digital Signal Processing School of Engineering Cardiff University Cardiff CF24 3AA UK 2 F. C. Donders Centre for Cognitive Neuroimaging Kapittelweg 29 6525 EN Nijmegen The Netherlands 3 Advanced Signal Processing Group Department of Electronic and Electrical Engineering Loughborough University Loughborough LE11 3TU UK Correspondence should be addressed to Kianoush Nazarpour nazarpourk@ Received 5 December 2007 Accepted 11 February 2008 Recommended by Tan Lee A novel blind signal extraction BSE scheme for the removal of eye-blink artifact from electroencephalogram EEG signals is proposed. In this method in order to remove the artifact the source extraction algorithm is provided with an estimation of the column of the mixing matrix corresponding to the point source eye-blink artifact. The eye-blink source is first extracted and then cleaned artifact-removed EEGs are subsequently reconstructed by a deflation method. The a priori knowledge namely the vector corresponding to the spatial distribution of the eye-blink factor is identified by fitting a space-time-frequency STF model to the EEG measurements using the parallel factor PARAFAC analysis method. Hence we call the BSE approach semiblind signal extraction SBSE . This approach introduces the possibility of incorporating PARAFAC within the blind source extraction framework for single trial EEG processing applications and the respected formulations. Moreover aiming at extracting the eyeblink artifact it exploits the spatial as well as temporal prior information during the extraction procedure. Experiments on synthetic data and real EEG measurements
