A study of white matter and skull inhomogeneous anisotropic tissue conductivities on EEG forward head modeling

Bashar, Md. Rezaul and Li, Yan and Wen, Peng (2008) A study of white matter and skull inhomogeneous anisotropic tissue conductivities on EEG forward head modeling. In: DMAI 2008: 1st IEEE International Workshop on Data Mining and Artificial Intelligence , 24-27 Dec 2008, Khulna, Bangladesh.

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Abstract

The aim of this study is to investigate the effects of white matter (WM) and skull inhomogeneous anisotropic tissue conductivities on human head modeling. The inhomogeneity of WM and skull is included using fractional anisotropy (FA) method and the anisotropy is included according to Volume constraint in the head model construction. A fivelayered spherical head model implemented using finite element method (FEM) is used as a volume conductor with a known current source to measure the electroencephalogram (EEG) on the head surface. Statistical measurement techniques are applied to analyze the EEGs obtained from inhomogeneous anisotropic head models and a homogeneous isotropic model. This study finds that the effects of WM and skull inhomogeneous anisotropy on EEG are significant.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Author's version deposited in accordance with the copyright policy of the publisher. Workshop held during 11th International Conference on Computer and Information Technology, ICCIT 2008
Depositing User: Dr Yan Li
Faculty / Department / School: Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited: 06 Feb 2009 05:35
Last Modified: 21 Aug 2014 22:47
Uncontrolled Keywords: fractional anisotropy; finite element method; inhomogeneous anisotropic conductivity; EEG; forward problem
Fields of Research (FOR2008): 01 Mathematical Sciences > 0103 Numerical and Computational Mathematics > 010301 Numerical Analysis
01 Mathematical Sciences > 0102 Applied Mathematics > 010202 Biological Mathematics
09 Engineering > 0903 Biomedical Engineering > 090399 Biomedical Engineering not elsewhere classified
Socio-Economic Objective (SEO2008): E Expanding Knowledge > 97 Expanding Knowledge > 970110 Expanding Knowledge in Technology
Identification Number or DOI: doi: 10.1109/ICCITECHN.2008.4803103
URI: http://eprints.usq.edu.au/id/eprint/4842

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