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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第一著者: Saeidiasl, Leila
フォーマット: 学位論文
言語:English
出版事項: 2015
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spelling my.utm.776972018-06-29T21:29:30Z http://eprints.utm.my/id/eprint/77697/ Simulated electroencephalography (EEG) source localization using integrated meromorphic approximation 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 NonPeerReviewed application/pdf en http://eprints.utm.my/id/eprint/77697/1/LeilaSaeidiaslPFS2015.pdf Saeidiasl, Leila (2015) Simulated electroencephalography (EEG) source localization using integrated meromorphic approximation. PhD thesis, Universiti Teknologi Malaysia, Faculty of Science. http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:95466
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
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
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
publishDate 2015
url http://eprints.utm.my/id/eprint/77697/1/LeilaSaeidiaslPFS2015.pdf
http://eprints.utm.my/id/eprint/77697/
http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:95466
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