Framework for estimating active brain sources using MUSIC and Root MUSIC

Subspace techniques are widely used for direction of arrival (DOA) problems in telecommunications and position location applications for estimating the location of sources from where the signal is originated. This source estimation problem is analogues to the source estimation problem in EEG signal...

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Main Authors: Jatoi, M.A., Kamel, N., Musavi, S.H.A.
Format: Article
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.20090 /
Published: Institute of Electrical and Electronics Engineers Inc. 2017
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020056012&doi=10.1109%2fICIEECT.2017.7916546&partnerID=40&md5=6628f9461202abc64c4f60e46f20b96a
http://eprints.utp.edu.my/20090/
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spelling utp-eprints.200902018-04-22T14:40:46Z Framework for estimating active brain sources using MUSIC and Root MUSIC Jatoi, M.A. Kamel, N. Musavi, S.H.A. Subspace techniques are widely used for direction of arrival (DOA) problems in telecommunications and position location applications for estimating the location of sources from where the signal is originated. This source estimation problem is analogues to the source estimation problem in EEG signal processing commonly termed as EEG inverse problem. The EEG inverse problem goes for estimation of active source inside the brain which is responsible for overall electromagnetic activity. This estimation provides useful basis to understand the physiological, neural and cognitive behavior of human brain which ultimately can be used for cure of many CNS related disease such as epilepsy and tumour etc. This research discuss most commonly used subspace techniques such as Multiple Signal classifier (MUSIC) and Root MUSIC for general DOA problem and produces some results by using MATLAB for arbitrary number of sources and varied number of element. Thus, the same methodology can be adopted for localization of active brain sources with few exceptions such as forward head modeling and sensor positions. © 2017 IEEE. Institute of Electrical and Electronics Engineers Inc. 2017 Article PeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020056012&doi=10.1109%2fICIEECT.2017.7916546&partnerID=40&md5=6628f9461202abc64c4f60e46f20b96a Jatoi, M.A. and Kamel, N. and Musavi, S.H.A. (2017) Framework for estimating active brain sources using MUSIC and Root MUSIC. ICIEECT 2017 - International Conference on Innovations in Electrical Engineering and Computational Technologies 2017, Proceedings . http://eprints.utp.edu.my/20090/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description Subspace techniques are widely used for direction of arrival (DOA) problems in telecommunications and position location applications for estimating the location of sources from where the signal is originated. This source estimation problem is analogues to the source estimation problem in EEG signal processing commonly termed as EEG inverse problem. The EEG inverse problem goes for estimation of active source inside the brain which is responsible for overall electromagnetic activity. This estimation provides useful basis to understand the physiological, neural and cognitive behavior of human brain which ultimately can be used for cure of many CNS related disease such as epilepsy and tumour etc. This research discuss most commonly used subspace techniques such as Multiple Signal classifier (MUSIC) and Root MUSIC for general DOA problem and produces some results by using MATLAB for arbitrary number of sources and varied number of element. Thus, the same methodology can be adopted for localization of active brain sources with few exceptions such as forward head modeling and sensor positions. © 2017 IEEE.
format Article
author Jatoi, M.A.
Kamel, N.
Musavi, S.H.A.
spellingShingle Jatoi, M.A.
Kamel, N.
Musavi, S.H.A.
Framework for estimating active brain sources using MUSIC and Root MUSIC
author_sort Jatoi, M.A.
title Framework for estimating active brain sources using MUSIC and Root MUSIC
title_short Framework for estimating active brain sources using MUSIC and Root MUSIC
title_full Framework for estimating active brain sources using MUSIC and Root MUSIC
title_fullStr Framework for estimating active brain sources using MUSIC and Root MUSIC
title_full_unstemmed Framework for estimating active brain sources using MUSIC and Root MUSIC
title_sort framework for estimating active brain sources using music and root music
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2017
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020056012&doi=10.1109%2fICIEECT.2017.7916546&partnerID=40&md5=6628f9461202abc64c4f60e46f20b96a
http://eprints.utp.edu.my/20090/
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score 11.62408

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