Abstract

Epilepsy is a neural disease caused by brain signal abnormalities. There are three phases in epilepsy, the pre-ictal, ictal, and post-ictal phase. To distinguish those phases, usually EEG signal is used. However, there is a study mentioning the connection between epilepsy and heart signals, so there is a probability to distinguish those phases using ECG. This study is made for distinguish the three phases in epilepsy and the normal condition of epilepsy patient using K Nearest Neighbors (KNN) algorithm. Dataset used in this study was from PhysioNet, obtained from long-Term EEG and ECG record of epileptic patient without history of cardiac disease. With the ability to do the identification of epilepsy phase, it is expected to help doctors and medical staffs to differ epileptic ECG signals for every different phases in epilepsy, and to prove the hypothesis whether the three phases in epilepsy can be distinguished from the heart signal.

Original languageEnglish
Title of host publicationCENIM 2020 - Proceeding
Subtitle of host publicationInternational Conference on Computer Engineering, Network, and Intelligent Multimedia 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages91-96
Number of pages6
ISBN (Electronic)9781728182834
DOIs
Publication statusPublished - 17 Nov 2020
Event2020 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2020 - Virtual, Surabaya, Indonesia
Duration: 17 Nov 202018 Nov 2020

Publication series

NameCENIM 2020 - Proceeding: International Conference on Computer Engineering, Network, and Intelligent Multimedia 2020

Conference

Conference2020 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2020
Country/TerritoryIndonesia
CityVirtual, Surabaya
Period17/11/2018/11/20

Keywords

  • ECG
  • Entropy
  • Epilepsy
  • Ictal
  • KNN
  • Post-Ictal
  • Pre-Ictal
  • RR Interval

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