Epilepsy detection on EEG data using backpropagation, firefly algorithm and simulated annealing

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

16 Citations (Scopus)

Abstract

Epilepsy is a central system disorder of human brain in which nerve cell activity becomes disrupted, causing seizures or periods of unsual behaviour, sensations and sometimes loss of consciousness. The electroencephalogram (EEG) is a measure of brain waves can be used in evaluation of brain disorders, one of which epilepsy. In this paper, epilepsy detection system on EEG data is built using combination of backpropagation and simulated annealing. Firefly algorithm and simulated annealing are used to determine optimal learning rate and number of unit hidden on backpropagation process. Then learning rate and number of unit hidden are used for trainning and validation backpropagation testing process on EEG data epilepsi detection. The percentages of success rate detection epilepsy EEG data obtained for 93.3% using the learning rate 0.93 and the number of hidden layer units as much as 7 to mean square error of 0.00535.

Original languageEnglish
Title of host publicationProceedings - 2016 2nd International Conference on Science and Technology-Computer, ICST 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages167-171
Number of pages5
ISBN (Electronic)9781509043576
DOIs
Publication statusPublished - 13 Mar 2017
Event2nd International Conference on Science and Technology-Computer, ICST 2016 - Yogyakarta, Indonesia
Duration: 27 Oct 201628 Oct 2016

Publication series

NameProceedings - 2016 2nd International Conference on Science and Technology-Computer, ICST 2016

Conference

Conference2nd International Conference on Science and Technology-Computer, ICST 2016
Country/TerritoryIndonesia
CityYogyakarta
Period27/10/1628/10/16

Keywords

  • EEG
  • backpropagation
  • epilepsy
  • firefly algorithm
  • simulated annealing

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