Robust epileptic seizure classification

Farrikh Alzami, Daxing Wang, Zhiwen Yu, Jia You, Hau San Wong, Guoqiang Han

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

A lot of feature vectors and sub-band signals are considered for Epileptic seizure classification. Unfortunately, not all the feature vectors and sub-band signals contribute to the final result. In view of this limitation, we propose a modified Differential Evolution Feature Selection algorithm (MDEFS), which searches the best feature vector subset and the sub-band signals to distinguish three groups of subjects (healthy, ictal and interictal). From the experiment results, it is observed that the bagging method based on the optimal feature subset (the standard deviation attribute in the delta sub-band signal, the time-lag attribute in the delta sub-band signal, fractal dimension in the alpha sub-band signal, the correlation dimension attribute in the alpha sub-band signal and the standard deviation attribute in the beta sub-band signal) selected by MDEFS results in highest classification accuracy of 98.67 %.
Original languageEnglish
Title of host publicationIntelligent Computing Theories and Application - 12th International Conference, ICIC 2016, Proceedings
PublisherSpringer Verlag
Pages363-373
Number of pages11
ISBN (Print)9783319422930
DOIs
Publication statusPublished - 1 Jan 2016
Event12th International Conference on Intelligent Computing Theories and Application, ICIC 2016 - Lanzhou, China
Duration: 2 Aug 20165 Aug 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9772
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th International Conference on Intelligent Computing Theories and Application, ICIC 2016
Country/TerritoryChina
CityLanzhou
Period2/08/165/08/16

Keywords

  • Bagging
  • Differential evolution
  • Discrete Wavelet Transform
  • Epileptic seizure classification
  • Feature selection

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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