JFET_V3_N2_RP4 G. Wiselin Jiji L. Ganesan Journal on Future Engineering and Technology 2230 – 7184 3 2 23 27 Artifact removal, eye blink, blind source separation (BSS), independent component analysis (ICA), electroencephalogram (EEG) Eye blink artifacts and power line noise always disturb the electroencephalograms (EEG) recorded on the scalp and pose serious problems in its signal analysis and interpretation. In this paper, an Independent Component Analysis (ICA) algorithm was applied to extract eye movements and power noise of 50Hz in several sets of EEG data. It is confirmed that ICA method can isolate both superguassian artifacts (eye blinks) and subguassian interference (line noise). It showed that ICA algorithms could well preserve the nonlinear characteristics of EEG after removing the artifacts. Experiment results show that ICA algorithm is a quite powerful technique and suitable for EEG data processing in clinical engineering. November 2007 - January 2008 Copyright © 2008 i-manager publications. All rights reserved. i-manager Publications http://www.imanagerpublications.com/Article.aspx?ArticleId=661