BAYES IAN BASED BRAIN SOURCE LOCALIZATION TECHNIQUE USING EEG SIGNALS

Brain Source localization from EEG/MEG is an ill-posed inverse problem with high uncertainty in the solution. This source localization information is used to diagnose various brain disorders such as epilepsy, schizophrenia, stress, depression and Alzheimer. Different algorithms are proposed for t...

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Main Author: JATOI, MUNSIF ALI
Format: Thesis
Language: English
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-utpedia.21912 /
Published: 2016
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access: http://utpedia.utp.edu.my/21912/1/2016%20-ELECTRICAL%20%26%20ELECTRONIC%20-%20BAYESIAN%20BASED%20BRAIN%20SOURCE%20LOCALIZATION%20TECHNIQUE%20USING%20EEG%20SIGNALS%20-%20MUNSIF%20ALI%20JATOI.pdf
http://utpedia.utp.edu.my/21912/
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spelling utp-utpedia.219122021-09-27T08:26:16Z http://utpedia.utp.edu.my/21912/ BAYES IAN BASED BRAIN SOURCE LOCALIZATION TECHNIQUE USING EEG SIGNALS JATOI, MUNSIF ALI TK Electrical engineering. Electronics Nuclear engineering Brain Source localization from EEG/MEG is an ill-posed inverse problem with high uncertainty in the solution. This source localization information is used to diagnose various brain disorders such as epilepsy, schizophrenia, stress, depression and Alzheimer. Different algorithms are proposed for the solution of this ill-posed problem which include minimum norm estimation (MNE), second order Laplacian based low resolution brain electromagnetic tomography (LORET A), standardized LORETA (sLORETA), exact LORETA, subspace based multiple signal classifier (MUSIC), Beamformer and Bayesian framework based multiple source priors (MSP). The solution provided by each of the algorithms mentioned above is characterized by various parameters which include the accuracy, computational complexity and localization error. The existing algorithms suffer from low resolution (LORETA family), high computational time (subspace algorithms and FOCUSS, WMNLORETA) and no validation. 2016-01 Thesis NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/21912/1/2016%20-ELECTRICAL%20%26%20ELECTRONIC%20-%20BAYESIAN%20BASED%20BRAIN%20SOURCE%20LOCALIZATION%20TECHNIQUE%20USING%20EEG%20SIGNALS%20-%20MUNSIF%20ALI%20JATOI.pdf JATOI, MUNSIF ALI (2016) BAYES IAN BASED BRAIN SOURCE LOCALIZATION TECHNIQUE USING EEG SIGNALS. PhD thesis, Universiti Teknologi PETRONAS.
institution Universiti Teknologi Petronas
collection UTPedia
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
JATOI, MUNSIF ALI
BAYES IAN BASED BRAIN SOURCE LOCALIZATION TECHNIQUE USING EEG SIGNALS
description Brain Source localization from EEG/MEG is an ill-posed inverse problem with high uncertainty in the solution. This source localization information is used to diagnose various brain disorders such as epilepsy, schizophrenia, stress, depression and Alzheimer. Different algorithms are proposed for the solution of this ill-posed problem which include minimum norm estimation (MNE), second order Laplacian based low resolution brain electromagnetic tomography (LORET A), standardized LORETA (sLORETA), exact LORETA, subspace based multiple signal classifier (MUSIC), Beamformer and Bayesian framework based multiple source priors (MSP). The solution provided by each of the algorithms mentioned above is characterized by various parameters which include the accuracy, computational complexity and localization error. The existing algorithms suffer from low resolution (LORETA family), high computational time (subspace algorithms and FOCUSS, WMNLORETA) and no validation.
format Thesis
author JATOI, MUNSIF ALI
author_sort JATOI, MUNSIF ALI
title BAYES IAN BASED BRAIN SOURCE LOCALIZATION TECHNIQUE USING EEG SIGNALS
title_short BAYES IAN BASED BRAIN SOURCE LOCALIZATION TECHNIQUE USING EEG SIGNALS
title_full BAYES IAN BASED BRAIN SOURCE LOCALIZATION TECHNIQUE USING EEG SIGNALS
title_fullStr BAYES IAN BASED BRAIN SOURCE LOCALIZATION TECHNIQUE USING EEG SIGNALS
title_full_unstemmed BAYES IAN BASED BRAIN SOURCE LOCALIZATION TECHNIQUE USING EEG SIGNALS
title_sort bayes ian based brain source localization technique using eeg signals
publishDate 2016
url http://utpedia.utp.edu.my/21912/1/2016%20-ELECTRICAL%20%26%20ELECTRONIC%20-%20BAYESIAN%20BASED%20BRAIN%20SOURCE%20LOCALIZATION%20TECHNIQUE%20USING%20EEG%20SIGNALS%20-%20MUNSIF%20ALI%20JATOI.pdf
http://utpedia.utp.edu.my/21912/
_version_ 1741195802754154496
score 11.62408

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