Performance Analysis of Entropy Methods in Detecting Epileptic Seizure from Surface Electroencephalograms

Emran Ali, Radhagayathri K. Udhayakumar, Maia Angelova, Chandan Karmakar

Research output: Chapter in Book/Report/Conference proceedingConference proceedingpeer-review

4 Citations (Scopus)

Abstract

Physiological signals like Electrocardiography (ECG) and Electroencephalography (EEG) are complex and nonlinear in nature. To retrieve diagnostic information from these, we need the help of nonlinear methods of analysis. Entropy estimation is a very popular approach in the nonlinear category, where entropy estimates are used as features for signal classification and analysis. In this study, we analyze and compare the performances of four entropy methods; namely Distribution entropy (DistEn), Shannon entropy (ShanEn), Renyi entropy (RenEn) and LempelZiv complexity (LempelZiv) as classification features to detect epileptic seizure (ES) from surface Electroencephalography (sEEG) signal. Experiments were conducted on sEEG data from 23 subjects, obtained from the CHB-MIT database of PhysioNet. ShanEn, RenEn and LempelZiv entropy are found to be potential features for accurate and consistent detection of ES from sEEG, across multiple channels and subjects.

Original languageEnglish
Title of host publication43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1082-1085
Number of pages4
ISBN (Electronic)9781728111797
DOIs
Publication statusPublished - 9 Dec 2021
Externally publishedYes
Event43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021 - Virtual, Online, Mexico
Duration: 1 Nov 20215 Nov 2021

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Conference

Conference43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021
Country/TerritoryMexico
CityVirtual, Online
Period1/11/215/11/21

Bibliographical note

Publisher Copyright:
© 2021 IEEE.

Keywords

  • Entropy
  • Epilepsy
  • Epileptic Seizure
  • sEEG
  • Seizure detection

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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