Title: A classification system to discriminate epileptic patients using multi-valued coarse-graining Lempel-Ziv complexity

Authors: Chandrakar Kamath

Addresses: Electronics and Communication Department, Manipal Institute of Technology, Manipal-576104, India

Abstract: A classification system to discriminate epileptic subjects from healthy subjects is proposed. All the previous research to detect epileptic seizures/patients using Lempel-Ziv complexity measure had used Binary Coarse-Graining (BLZC). In this work, we show that employing multi-valued coarse-graining Lempel-Ziv complexity (MLZC) improves the performance of classification. This finding is confirmed using Receiver Operating Characteristic (ROC) plots. Both the measures yielded excellent results with the MLZC showing improved results with, a sensitivity of 96.6%, specificity of 100%, precision of 100% and an accuracy of 98.3%. The classification system in this paper will be a valuable asset to the clinician in the separation of epileptic patients from the healthy group.

Keywords: electroencephalogram; EEG; coarse graining; epilepsy detection; multi-valued Lempel-Ziv complexity; classification systems; epileptic patient identification.

DOI: 10.1504/IJBET.2013.053717

International Journal of Biomedical Engineering and Technology, 2013 Vol.11 No.1, pp.96 - 106

Received: 08 Sep 2012
Accepted: 06 Jan 2013

Published online: 27 Sep 2014 *

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