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Comparison Study for Whitney (Raviart-Thomas) Type Source Models in Finite Element Method Based EEG Forward Modeling

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Details

Original languageEnglish
Pages (from-to)2648-2656
Number of pages9
JournalIEEE Transactions on Biomedical Engineering
Volume62
Issue number11
DOIs
Publication statusPublished - Nov 2015
Publication typeA1 Journal article-refereed

Abstract

This study concentrates on finite element method (FEM)
based electroencephalography (EEG) forward simulation in which the
electric potential evoked by neural activity in the brain is to be calculated
at the surface of the head. The main advantage of the FEM is that it allows
realistic modeling of tissue conductivity inhomogeneity. However, it is not
straightforward to apply the classical model of a dipolar source with the
FEM, due to its strong singularity and the resulting irregularity. The focus
of this study is on comparing different methods to cope with this problem.
In particular, we evaluate the accuracy of Whitney (Raviart-Thomas) type
dipole-like source currents compared to two reference dipole modeling
methods: the St. Venant and partial integration approach. Common
to all these methods is that they enable direct approximation of the
potential field utilizing linear basis functions. In the present context,
Whitney elements are particularly interesting, as they provide a simple
means to model a divergence-conforming primary current vector field
satisfying the square integrability condition. Our results show that a
Whitney type source model can provide simulation accuracy comparable
to the present reference methods. It can lead to superior accuracy under
optimized conditions with respect to both source location and orientation
in a tetrahedral mesh. For random source orientations, the St. Venant
approach turns out to be the method of choice over the interpolated
version of the Whitney model. The overall moderate differences obtained
suggest that practical aspects, such as the focality, should be prioritized
when choosing a source model.

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Field of science, Statistics Finland