Literature DB >> 11059168

Improving the accuracy of the boundary element method by the use of second-order interpolation functions.

J H Frijns1, S L de Snoo, R Schoonhoven.   

Abstract

The boundary element method (BEM) is a widely used method to solve biomedical electromagnetic volume conduction problems. The commonly used formulation of this method uses constant interpolation functions for the potential and flat triangular surface elements. Linear interpolation for the potential on a flat triangular mesh turned out to yield a better accuracy. In this paper, we introduce quadratic interpolation functions for the potential and quadratically curved surface elements, resulting from second-order spatial interpolation. Theoretically, this results in an accuracy that is inversely proportional to the third power of element size. The method is tested on a four concentric sphere geometry, representative for electroencephalogram modeling, and compared to previous solutions of this problem in literature. In addition, a cylindrical test configuration is used. We conclude that the use of quadratic interpolation functions for the potential and of quadratically curved surface elements in BEM results in a significant increase in accuracy and in some cases even a reduction of the computation time with the same number of nodes involved in the calculations.

Mesh:

Year:  2000        PMID: 11059168     DOI: 10.1109/10.871407

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  6 in total

1.  Fast realistic modeling in bioelectromagnetism using lead-field interpolation.

Authors:  B Yvert; A Crouzeix-Cheylus; J Pernier
Journal:  Hum Brain Mapp       Date:  2001-09       Impact factor: 5.038

2.  A regularised singularity approach to phoretic problems.

Authors:  Thomas D Montenegro-Johnson; Sébastien Michelin; Eric Lauga
Journal:  Eur Phys J E Soft Matter       Date:  2015-12-28       Impact factor: 1.890

3.  Accuracy of quadratic versus linear interpolation in noninvasive Electrocardiographic Imaging (ECGI).

Authors:  Subham Ghosh; Yoram Rudy
Journal:  Ann Biomed Eng       Date:  2005-09       Impact factor: 3.934

4.  Parallel implementation of the accelerated BEM approach for EMSI of the human brain.

Authors:  Y Ataseven; Z Akalin-Acar; C E Acar; N G Gençer
Journal:  Med Biol Eng Comput       Date:  2008-02-26       Impact factor: 2.602

Review 5.  Review on solving the forward problem in EEG source analysis.

Authors:  Hans Hallez; Bart Vanrumste; Roberta Grech; Joseph Muscat; Wim De Clercq; Anneleen Vergult; Yves D'Asseler; Kenneth P Camilleri; Simon G Fabri; Sabine Van Huffel; Ignace Lemahieu
Journal:  J Neuroeng Rehabil       Date:  2007-11-30       Impact factor: 4.262

6.  Effects of head models and dipole source parameters on EEG fields.

Authors:  Li Peng; Mingming Peng; Anhuai Xu
Journal:  Open Biomed Eng J       Date:  2015-02-27
  6 in total

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