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

Chandrakar Kamath

Research output: Contribution to journalArticle

5 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)96-106
Number of pages11
JournalInternational Journal of Biomedical Engineering and Technology
Volume11
Issue number1
DOIs
Publication statusPublished - 01-01-2013
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering

Cite this

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A classification system to discriminate epileptic patients using multi-valued coarse-graining Lempel-Ziv complexity. / Kamath, Chandrakar.

In: International Journal of Biomedical Engineering and Technology, Vol. 11, No. 1, 01.01.2013, p. 96-106.

Research output: Contribution to journalArticle

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