@inproceedings{3ba13d9db8c74fd196d486ecd4e0d915,
title = "Identification of Epilepsy Phase Based on Time Domain Feature Using ECG Signals",
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.",
keywords = "ECG, Entropy, Epilepsy, Ictal, KNN, Post-Ictal, Pre-Ictal, RR Interval",
author = "Islamiyah, {Wardah R.} and Wulandari, {Diah P.} and Sarasati, {Nadhira N.} and Suprapto, {Yoyon K.} and Purnami, {Santi W.} and Juniani, {Anda I.}",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2020 ; Conference date: 17-11-2020 Through 18-11-2020",
year = "2020",
month = nov,
day = "17",
doi = "10.1109/CENIM51130.2020.9297979",
language = "English",
series = "CENIM 2020 - Proceeding: International Conference on Computer Engineering, Network, and Intelligent Multimedia 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "91--96",
booktitle = "CENIM 2020 - Proceeding",
address = "United States",
}