eprintid: 4579
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/45/79
datestamp: 2023-11-09 16:16:16
lastmod: 2023-11-09 16:16:16
status_changed: 2023-11-09 15:58:45
type: conference_item
metadata_visibility: show
creators_name: Hyder, R.
creators_name: Kamel, N.
creators_name: Tang, T.B.
creators_name: Bornot, J.
title: Brain source localization techniques: Evaluation study using simulated EEG data
ispublished: pub
keywords: Electroencephalography; Engineering; Industrial engineering, Asymmetric activation; Brain source localization; Electrical tomography; Inversion techniques; Localization problems; Minimum norm estimate; Simulated dipoles; Source localization, Biomedical engineering
note: cited By 3; Conference of 3rd IEEE Conference on Biomedical Engineering and Sciences, IECBES 2014 ; Conference Date: 8 December 2014 Through 10 December 2014; Conference Code:111205
abstract: Several methods have been proposed over the past few decades as a solution to the brain sources localization problem using EEG signals. In this paper the performances of different brain source localization techniques, including the Minimum Norm Estimates (MNE), Low Resolution Electrical Tomography (LORETA) and Multiple Sparse Priors (MSP), are assessed and compared. Due to the lack of the baseline, the evaluation is conducted using simulated dipolar source distributions constrained to the cortical surface. We corroborate in the superiority of MSP over LORETA and MNE in accurately estimating the locations of the simulated sources, however we found that MNE and LORETA may account as a better measure for asymmetric activations. © 2014 IEEE.
date: 2014
publisher: Institute of Electrical and Electronics Engineers Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84925679324&doi=10.1109%2fIECBES.2014.7047651&partnerID=40&md5=3308f5b22acc7cca1cdcbc384ddf17cc
id_number: 10.1109/IECBES.2014.7047651
full_text_status: none
publication: IECBES 2014, Conference Proceedings - 2014 IEEE Conference on Biomedical Engineering and Sciences: "Miri, Where Engineering in Medicine and Biology and Humanity Meet"
pagerange: 942-947
refereed: TRUE
isbn: 9781479940844
citation:   Hyder, R. and Kamel, N. and Tang, T.B. and Bornot, J.  (2014) Brain source localization techniques: Evaluation study using simulated EEG data.  In: UNSPECIFIED.