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Title: Localization of abnormal EEG sources using blind source separation partially constrained by the locations of known sources
Authors: Latif, Mohamed Amin
Sanei, Saeid
Chambers, Jonathon
Shoker, Leor
Keywords: Blind source separation (BSS)
Electroencephalogram (EEG)
Partially constrained
Source localization
Issue Date: 2006
Publisher: © IEEE
Citation: LATIF, M.A. ...et al, 2006. Localization of abnormal EEG sources using blind source separation partially constrained by the locations of known sources. IEEE Signal Processing Letters, 13 (3), pp. 117-120.
Abstract: Electroencephalogram (EEG) source localization requires a solution to an ill-posed inverse problem. The additional challenge is to solve this problem in the context of multiple moving sources. An effective and simple technique for both separation and localization of EEG sources is therefore proposed by incorporating an algorithmically coupled blind source separation (BSS) approach. The method relies upon having a priori knowledge of the locations of a subset of the sources. The cost function of the BSS algorithm is constrained by this information, and the unknown sources are iteratively calculated. An important application of this method is to localize abnormal sources, which, for example, cause changes in attention, movement, and behavior. In this application, the Alpha rhythm was considered as the known sources. Simulation studies are presented to support the potential of the approach in terms of source localization.
Description: This article was published in the journal IEEE Signal Processing Letters [© IEEE] and is also available at: http://ieeexplore.ieee.org/ Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Version: Published
DOI: 10.1109/LSP.2005.862622
URI: https://dspace.lboro.ac.uk/2134/5597
ISSN: 1070-9908
Appears in Collections:Published Articles (Mechanical, Electrical and Manufacturing Engineering)

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