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Estimating Regularity in Epileptic Seizure Time-Series Data: A Complexity-Measure Approach

Radhakrishnan, N and Gangadhar, BN (1998) Estimating Regularity in Epileptic Seizure Time-Series Data: A Complexity-Measure Approach. In: IEEE Engineering in Medicine and Biology Magazine, 17 (3). pp. 89-94.


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In the study of complex systems one maybe faced with experimental data collected on the variables without knowing much about the way in which these variables interact. The parts of such a complex system interact in a norisimple way [l]. Wolfram [2] found that there exists a complex dynamic state which may be even more complex than chaotic motions. Complex systems have been found to have an underlying deterministic model and exhibit chaotic dynamics in some cases, epilepsy in particular [3]. The use of quantitative measures for the analysis of these systems has helped gain better insight into system dynamics. In this article we apply Ziv-Lempel (LZ) complexity and approximate entropy (ApEn) as measures to quantify the regularity in the various epochs of epileptic seizure time-series data.

Item Type: Journal Article
Publication: IEEE Engineering in Medicine and Biology Magazine
Publisher: IEEE
Additional Information: ©1998 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Department/Centre: Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited: 25 Aug 2008
Last Modified: 19 Sep 2010 04:15
URI: http://eprints.iisc.ac.in/id/eprint/1429

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