Simulated electroencephalography (EEG) source localization using integrated meromorphic approximation

Epilepsy is a chronic brain dysfunction in which neurons and neuronal network malfunction cause symptoms of a seizure. A seizure is an abnormal electrical discharge from the brain appearing at a small area of the brain. The seizure affected zone loses its normal task abilities and might react uncont...

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Main Author:	Saeidiasl, Leila
Format:	Thesis
Language:	English
Published:	2015
Subjects:	Q Science (General)
Online Access:	http://eprints.utm.my/id/eprint/77697/1/LeilaSaeidiaslPFS2015.pdf
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id	my-utm-ep.77697
record_format	uketd_dc
spelling	my-utm-ep.776972018-06-29T21:29:30Z Simulated electroencephalography (EEG) source localization using integrated meromorphic approximation 2015-09 Saeidiasl, Leila Q Science (General) Epilepsy is a chronic brain dysfunction in which neurons and neuronal network malfunction cause symptoms of a seizure. A seizure is an abnormal electrical discharge from the brain appearing at a small area of the brain. The seizure affected zone loses its normal task abilities and might react uncontrollably. Electroencephalography (EEG) is one of the useful instruments in diagnosing many brain disorders like epilepsy. This non-invasive modality is used to localize brain regions involved during the generation of epileptic discharges. At present, many quantitative methods for identifying and localizing the epileptogenic focus from EEG have been invented by scientists around the world. Under quasi-static assumptions, Maxwell’s equations governing the spatial behaviour of the electromagnetic fields lead to Partial Differential Equations (PDE) of elliptic type in domains of R3. This thesis presents a new method based on integrated new EEG source detection, Cortical Brain Scanning (CBS) with meromorphic approximation to identify the sources on the brain scalp, which have highly abnormal activities when a patient is having a seizure attack. Boundary measurements for meromorphic approximation method are considered as isotropic and homogeneous in each layer (brain, skull, and scalp). The proposed method is applied on simulated and published EEG data obtained from epileptic patients. The method can enhance the localizations of sources in comparison to other methods, such as Low Resolution Brain Electromagnetic Tomography (LORETA), Minimum Norm Estimation (MNE), and Weight Minimum Norm Estimate (WMNE), coupled with meromorphic approximation. Standard validation metrics including Root Sum Square (RSS), Mean Square Error (MSE), and Receiver Operating Characteristic Curve (ROC) are used to verify the result. The proposed method produces promising results in enhancing the source of localization accuracy of epileptic foci. 2015-09 Thesis http://eprints.utm.my/id/eprint/77697/ http://eprints.utm.my/id/eprint/77697/1/LeilaSaeidiaslPFS2015.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:95466 phd doctoral Universiti Teknologi Malaysia, Faculty of Science Faculty of Science
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	Q Science (General)
spellingShingle	Q Science (General) Saeidiasl, Leila Simulated electroencephalography (EEG) source localization using integrated meromorphic approximation
description	Epilepsy is a chronic brain dysfunction in which neurons and neuronal network malfunction cause symptoms of a seizure. A seizure is an abnormal electrical discharge from the brain appearing at a small area of the brain. The seizure affected zone loses its normal task abilities and might react uncontrollably. Electroencephalography (EEG) is one of the useful instruments in diagnosing many brain disorders like epilepsy. This non-invasive modality is used to localize brain regions involved during the generation of epileptic discharges. At present, many quantitative methods for identifying and localizing the epileptogenic focus from EEG have been invented by scientists around the world. Under quasi-static assumptions, Maxwell’s equations governing the spatial behaviour of the electromagnetic fields lead to Partial Differential Equations (PDE) of elliptic type in domains of R3. This thesis presents a new method based on integrated new EEG source detection, Cortical Brain Scanning (CBS) with meromorphic approximation to identify the sources on the brain scalp, which have highly abnormal activities when a patient is having a seizure attack. Boundary measurements for meromorphic approximation method are considered as isotropic and homogeneous in each layer (brain, skull, and scalp). The proposed method is applied on simulated and published EEG data obtained from epileptic patients. The method can enhance the localizations of sources in comparison to other methods, such as Low Resolution Brain Electromagnetic Tomography (LORETA), Minimum Norm Estimation (MNE), and Weight Minimum Norm Estimate (WMNE), coupled with meromorphic approximation. Standard validation metrics including Root Sum Square (RSS), Mean Square Error (MSE), and Receiver Operating Characteristic Curve (ROC) are used to verify the result. The proposed method produces promising results in enhancing the source of localization accuracy of epileptic foci.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Saeidiasl, Leila
author_facet	Saeidiasl, Leila
author_sort	Saeidiasl, Leila
title	Simulated electroencephalography (EEG) source localization using integrated meromorphic approximation
title_short	Simulated electroencephalography (EEG) source localization using integrated meromorphic approximation
title_full	Simulated electroencephalography (EEG) source localization using integrated meromorphic approximation
title_fullStr	Simulated electroencephalography (EEG) source localization using integrated meromorphic approximation
title_full_unstemmed	Simulated electroencephalography (EEG) source localization using integrated meromorphic approximation
title_sort	simulated electroencephalography (eeg) source localization using integrated meromorphic approximation
granting_institution	Universiti Teknologi Malaysia, Faculty of Science
granting_department	Faculty of Science
publishDate	2015
url	http://eprints.utm.my/id/eprint/77697/1/LeilaSaeidiaslPFS2015.pdf
_version_	1747817810162089984

Simulated electroencephalography (EEG) source localization using integrated meromorphic approximation

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