Tissue conductivity anisotropy inhomogeneity study in EEG head modelling

Bashar, Md. Rezaul and Li, Yan and Wen, Peng (2008) Tissue conductivity anisotropy inhomogeneity study in EEG head modelling. In: BIOCOMP 2008: International Conference on Bioinformatics and Computational Biology, 14-17 Jul 2008, Las Vegas, NV. USA.

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Abstract

This study investigates the effects of anisotropic inhomogeneous tissue conductivity with local variations on the electroencephalogram (EEG) forward computation. Human head modelling for the forward computation using finite element method (FEM) requires a large set of elements to represent the head geometry. Anatomically, the electrical property of each element is different, even though it represents the same type of tissue. At microscopic level, tissues are anisotropic and inhomogeneous. However, most of the researchers implement the computation for the homogeneous case. This paper presents a numerical approach to model a human head by using statistical conductivity approximation (SCA) technique for the computation based on white matter (WM) and skull anisotropic inhomogeneity. FEM is used to model the head volume conductor with WM and skull anisotropic inhomogeneous conductivity estimated by the volume constrained method. A current dipole is also used inside the gray matter to simulate the brain electrical activity. The experimental results show that the anisotropic inhomogeneous tissue conductivity has effects on the scalp EEG..


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Speech)
Refereed: Yes
Item Status: Live Archive
Additional Information: No evidence of copyright restrictions on web site.
Depositing User: Dr Yan Li
Faculty / Department / School: Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited: 06 Feb 2009 02:05
Last Modified: 02 Jul 2013 23:13
Uncontrolled Keywords: anisotropy; inhomogeneous; finite element method; statistical conductivity approximation; head model; electroencephalogram
Fields of Research (FOR2008): 01 Mathematical Sciences > 0104 Statistics > 010406 Stochastic Analysis and Modelling
10 Technology > 1004 Medical Biotechnology > 100402 Medical Biotechnology Diagnostics (incl. Biosensors)
09 Engineering > 0903 Biomedical Engineering > 090302 Biomechanical Engineering
Socio-Economic Objective (SEO2008): E Expanding Knowledge > 97 Expanding Knowledge > 970110 Expanding Knowledge in Technology
URI: http://eprints.usq.edu.au/id/eprint/4858

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