Identification of Epileptic Seizures using Autoencoders and Convolutional Neural Network

Contemporary application of machine learning has paved a way for the medical diagnosis automation without any manual intervention. Once such application is early deduction of the epileptic seizures. Earlier identification of seizures aids specialists towards diagnosis. This paper analyzes on the det...

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Main Authors: Divya, P., Aruna Devi, B., Prabakar, S., Porkumaran, K., Kannan, R., Nor, N.B.M., Elamvazuthi, I.
Format: Conference or Workshop Item
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.29196 /
Published: Institute of Electrical and Electronics Engineers Inc. 2021
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124149874&doi=10.1109%2fICIAS49414.2021.9642570&partnerID=40&md5=89497753288aa6a94a71584f390ba27f
http://eprints.utp.edu.my/29196/
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spelling utp-eprints.291962022-03-25T01:11:40Z Identification of Epileptic Seizures using Autoencoders and Convolutional Neural Network Divya, P. Aruna Devi, B. Prabakar, S. Porkumaran, K. Kannan, R. Nor, N.B.M. Elamvazuthi, I. Contemporary application of machine learning has paved a way for the medical diagnosis automation without any manual intervention. Once such application is early deduction of the epileptic seizures. Earlier identification of seizures aids specialists towards diagnosis. This paper analyzes on the detection of EEG epileptic seizures using Autoencoders, Convolutional Neural Network (CNN), and a multi class Stacked Autoencoder-CN model. These prediction models were analyzed on the intracranial EEG data set from15 real time patients, CHB-MIT dataset and P300 dataset. The results in python, proved for Stacked Autoencoder-Convolution Neural (SAE-CN) model to give optimum and effective solution in terms of higher speed and reduction in training time of the classifier and better probability of 0.925. This analysis proposes the idea of pre-prepared systems for other EEGrelated applications. © 2021 IEEE. Institute of Electrical and Electronics Engineers Inc. 2021 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124149874&doi=10.1109%2fICIAS49414.2021.9642570&partnerID=40&md5=89497753288aa6a94a71584f390ba27f Divya, P. and Aruna Devi, B. and Prabakar, S. and Porkumaran, K. and Kannan, R. and Nor, N.B.M. and Elamvazuthi, I. (2021) Identification of Epileptic Seizures using Autoencoders and Convolutional Neural Network. In: UNSPECIFIED. http://eprints.utp.edu.my/29196/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description Contemporary application of machine learning has paved a way for the medical diagnosis automation without any manual intervention. Once such application is early deduction of the epileptic seizures. Earlier identification of seizures aids specialists towards diagnosis. This paper analyzes on the detection of EEG epileptic seizures using Autoencoders, Convolutional Neural Network (CNN), and a multi class Stacked Autoencoder-CN model. These prediction models were analyzed on the intracranial EEG data set from15 real time patients, CHB-MIT dataset and P300 dataset. The results in python, proved for Stacked Autoencoder-Convolution Neural (SAE-CN) model to give optimum and effective solution in terms of higher speed and reduction in training time of the classifier and better probability of 0.925. This analysis proposes the idea of pre-prepared systems for other EEGrelated applications. © 2021 IEEE.
format Conference or Workshop Item
author Divya, P.
Aruna Devi, B.
Prabakar, S.
Porkumaran, K.
Kannan, R.
Nor, N.B.M.
Elamvazuthi, I.
spellingShingle Divya, P.
Aruna Devi, B.
Prabakar, S.
Porkumaran, K.
Kannan, R.
Nor, N.B.M.
Elamvazuthi, I.
Identification of Epileptic Seizures using Autoencoders and Convolutional Neural Network
author_sort Divya, P.
title Identification of Epileptic Seizures using Autoencoders and Convolutional Neural Network
title_short Identification of Epileptic Seizures using Autoencoders and Convolutional Neural Network
title_full Identification of Epileptic Seizures using Autoencoders and Convolutional Neural Network
title_fullStr Identification of Epileptic Seizures using Autoencoders and Convolutional Neural Network
title_full_unstemmed Identification of Epileptic Seizures using Autoencoders and Convolutional Neural Network
title_sort identification of epileptic seizures using autoencoders and convolutional neural network
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2021
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124149874&doi=10.1109%2fICIAS49414.2021.9642570&partnerID=40&md5=89497753288aa6a94a71584f390ba27f
http://eprints.utp.edu.my/29196/
_version_ 1741197203710410752
score 11.62408

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