Investigation of entropy and complexity measures for detection of seizures in the neonate

Research output: Chapter in Book/Report/Conference proceedingsChapterpeer-review

Abstract

The performance of three Entropy/complexity measures in detecting EEG seizures in the neonate were investigated in this study. A dataset containing EEG recordings from 11 neonates, with documented electrographic seizures, was employed in this study. Based on patient independent tests Shannon Entropy was found to provide the best in discrimination between seizure and non-seizure EEG in the neonate. Lempel-Ziv complexity and Multi-scale Entropy were second and third respectively, while Sample Entropy did not prove a useful feature for discriminating seizure patterns from non-seizure patterns.

Original languageEnglish
Title of host publicationBIOSIGNALS 2008 - Proceedings of the 1st International Conference on Bio-inspired Systems and Signal Processing
Pages17-22
Number of pages6
Publication statusPublished - 2008
EventBIOSIGNALS 2008 - 1st International Conference on Bio-inspired Systems and Signal Processing - Funchal, Madeira, Portugal
Duration: 28 Jan 200831 Jan 2008

Publication series

NameBIOSIGNALS 2008 - Proceedings of the 1st International Conference on Bio-inspired Systems and Signal Processing
Volume2

Conference

ConferenceBIOSIGNALS 2008 - 1st International Conference on Bio-inspired Systems and Signal Processing
Country/TerritoryPortugal
CityFunchal, Madeira
Period28/01/0831/01/08

Keywords

  • Complexity
  • EEG
  • Entropy
  • Neonatal
  • Seizures

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