Journal
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
Volume 4, Issue 2, Pages 108-117Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.bspc.2009.01.004
Keywords
Seizure; SOBI; RPCL; Clustering; Localization; BSS
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Localization of seizure sources prior to neurosurgery is crucial. In this paper, a new method is proposed to localize the seizure sources from multi-channel electroencephalogram (EEG) signals. Blind source separation based on second order blind identification (SOBI) is primarily applied to estimate the brain source signals in each window of the EEG signals. A new clustering method based on rival penalized competitive learning (RPCL) is then developed to cluster the rows of the estimated unmixing matrices in all the windows. The algorithm also includes pre and post-processing stages. By multiplying each cluster center to the EEG signals, the brain signal sources are approximated. According to a complexity value measure, the main seizure source signal is separated from the others. This signal is projected back to the electrodes' space and is subjected to the dipole source localization using a single dipole model. The simulation results verify the accuracy of the system. in addition, correct localization of the seizure source is consistent with the clinical tests derived using the simultaneous intracranial recordings. (C) 2009 Elsevier Ltd. All rights reserved.
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