Solving the EEG forward problems in a realistic geometry head model by means of the finite difference method

Jing Li, Kun Wang, Jun Liu, Shan An Zhu, Bin He

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

There are two important problems in the field of Electroencephalogram (EEG); EEG forward problem and inverse problem. The EEG forward problem is an important component of the EEG inverse problem. In realistic geometry head models, EEG source analysis depends on the accuracy and the efficiency of the numerical method chosen for solving the Forward Problem, as there is no analytical solution for realistic geometry models. A finite difference method (FDM) has been implemented to solve the 3-dimensional isotropic EEG forward problem. Then, the effects of dipole eccentricity, spacing of finite difference elements and number of grid nodes on the solution accuracy and efficiency are discussed by comparing the FDM numerical solutions with the analytic solutions on a three-concentric-sphere model. Finally, the FDM has been applied to a realistic-shaped head model to solve the EEG forward problem. The present computer simulation results suggest that FDM is convenient to solve the potential distribution in irregular shaped objects, and provides an effective tool for the EEG forward problem in realistic geometry head models.

Original languageEnglish (US)
Pages (from-to)1736-1741
Number of pages6
JournalChinese Journal of Sensors and Actuators
Volume20
Issue number8
StatePublished - Aug 2007

Keywords

  • Dipole
  • Electroencephalogram
  • Finite difference method
  • Forward problem
  • Volume conduction

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