Epilepsy detection from EEG signals using artificial neural network

In the field of medical science, one of the major recent researches is the diagnosis of the abnormalities in brain. Electroencephalogram (EEG) is a record of neuro signals that occur due the different electrical activities in the brain. These signals can be captured and processed to get the useful i...

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Main Authors:	Sallam, Amer A., M. Nomani, Kabir, Ahmed, Abdulghani Ali, Farhan, Khalid, Tarek, Ethar
Format:	Book Section
Language:	English
Published:	Springer Singapore 2019
Subjects:	QA76 Computer software
Online Access:	http://umpir.ump.edu.my/id/eprint/24657/ http://umpir.ump.edu.my/id/eprint/24657/ http://umpir.ump.edu.my/id/eprint/24657/ http://umpir.ump.edu.my/id/eprint/24657/2/10.1%20Epilepsy%20detection%20from%20EEG%20signals%20using%20artificial%20neural%20network.pdf

id	ump-24657
recordtype	eprints
spelling	ump-246572019-10-09T06:04:56Z http://umpir.ump.edu.my/id/eprint/24657/ Epilepsy detection from EEG signals using artificial neural network Sallam, Amer A. M. Nomani, Kabir Ahmed, Abdulghani Ali Farhan, Khalid Tarek, Ethar QA76 Computer software In the field of medical science, one of the major recent researches is the diagnosis of the abnormalities in brain. Electroencephalogram (EEG) is a record of neuro signals that occur due the different electrical activities in the brain. These signals can be captured and processed to get the useful information that can be used in early detection of some mental and brain diseases. Suitable analysis is essential for EEG to differentiate between normal and abnormal signals in order to detect epilepsy which is one of the most common neurological disorders. Epilepsy is a recurrent seizure disorder caused by abnormal electrical discharges from the brain cells, often in the cerebral cortex. This research focuses on the usefulness of EGG signal in detecting seizure activities in brainwaves. Artificial Neural Network (ANN) is used to train the data set. Then tests are conducted on the test data of EEG signals to identify normal (non-seizure) and abnormal (seizure) states of the brain. Finally, accuracy is computed to evaluate the performance of ANN. The experiments are carried out on CHB-MIT Scalp EEG Database. The experiments show plausible results from the proposed approach in terms of accuracy. Springer Singapore 2019 Book Section PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/24657/2/10.1%20Epilepsy%20detection%20from%20EEG%20signals%20using%20artificial%20neural%20network.pdf Sallam, Amer A. and M. Nomani, Kabir and Ahmed, Abdulghani Ali and Farhan, Khalid and Tarek, Ethar (2019) Epilepsy detection from EEG signals using artificial neural network. In: International Conference on Intelligent Computing & Optimization. Advances in Intelligent Systems and Computing . Springer Singapore, Singapore, pp. 320-327. ISBN 978-3-030-00979-3 https://doi.org/10.1007/978-3-030-00979-3_33 https://doi.org/10.1007/978-3-030-00979-3_33
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	QA76 Computer software
spellingShingle	QA76 Computer software Sallam, Amer A. M. Nomani, Kabir Ahmed, Abdulghani Ali Farhan, Khalid Tarek, Ethar Epilepsy detection from EEG signals using artificial neural network
description	In the field of medical science, one of the major recent researches is the diagnosis of the abnormalities in brain. Electroencephalogram (EEG) is a record of neuro signals that occur due the different electrical activities in the brain. These signals can be captured and processed to get the useful information that can be used in early detection of some mental and brain diseases. Suitable analysis is essential for EEG to differentiate between normal and abnormal signals in order to detect epilepsy which is one of the most common neurological disorders. Epilepsy is a recurrent seizure disorder caused by abnormal electrical discharges from the brain cells, often in the cerebral cortex. This research focuses on the usefulness of EGG signal in detecting seizure activities in brainwaves. Artificial Neural Network (ANN) is used to train the data set. Then tests are conducted on the test data of EEG signals to identify normal (non-seizure) and abnormal (seizure) states of the brain. Finally, accuracy is computed to evaluate the performance of ANN. The experiments are carried out on CHB-MIT Scalp EEG Database. The experiments show plausible results from the proposed approach in terms of accuracy.
format	Book Section
author	Sallam, Amer A. M. Nomani, Kabir Ahmed, Abdulghani Ali Farhan, Khalid Tarek, Ethar
author_facet	Sallam, Amer A. M. Nomani, Kabir Ahmed, Abdulghani Ali Farhan, Khalid Tarek, Ethar
author_sort	Sallam, Amer A.
title	Epilepsy detection from EEG signals using artificial neural network
title_short	Epilepsy detection from EEG signals using artificial neural network
title_full	Epilepsy detection from EEG signals using artificial neural network
title_fullStr	Epilepsy detection from EEG signals using artificial neural network
title_full_unstemmed	Epilepsy detection from EEG signals using artificial neural network
title_sort	epilepsy detection from eeg signals using artificial neural network
publisher	Springer Singapore
publishDate	2019
url	http://umpir.ump.edu.my/id/eprint/24657/ http://umpir.ump.edu.my/id/eprint/24657/ http://umpir.ump.edu.my/id/eprint/24657/ http://umpir.ump.edu.my/id/eprint/24657/2/10.1%20Epilepsy%20detection%20from%20EEG%20signals%20using%20artificial%20neural%20network.pdf
first_indexed	2023-09-18T22:37:27Z
last_indexed	2023-09-18T22:37:27Z
_version_	1777416690303238144

Epilepsy detection from EEG signals using artificial neural network

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