Automatic removal of eye-blink artifacts based on ICA and peak detection algorithm

Authors:
Junfeng Gao;Yong Yang;Pan Lin;Pei Wang
Affiliations:
Research Institute of Biomedical Engineering, Xi'an Jiaotong University, Xi'an, China;School of Information Technology, Jiangxi University of Finance and Economics, Nanchang, China and School of Life Science and Technology, University of Electronic Science and Technology of China, ...;Functional NeuroImaging Laboratory Center for Mind/Brain Sciences, University of Trent, Italy;Research Institute of Biomedical Engineering, Xi'an Jiaotong University, Xi'an, China
Venue:
CAR'10 Proceedings of the 2nd international Asia conference on Informatics in control, automation and robotics - Volume 1
Year:
2010

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Abstract

In this study a novel technique is proposed to automatically remove eye-blink artifacts from EEG signals. EEG signal is decomposed into independent components by independent component analysis (ICA) method. First, we demonstrate that feature-extraction method is not very suitable for identifying eyeblink artifacts components. Hence a peak detection algorithm of independent component is proposed to identify eye-blink artifacts components. Finally, the proposed artifact removal method is evaluated on some contaminated EEG signals, and the results show that it is able to effectively remove eye-blink artifacts from EEG signals with little distortion of underlying brain signals.