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The construction of a two-dimensional reproducing kernel function and its application in a biomedical model

Issue title: Papers from the 4th International Conference on Biomedical Engineering and Biotechnology (ICBEB2015), 18-21 August 2015, Shanghai, China ``New Paradigms for Biomedical Engineering and Biotechnology''

Article type: Research Article

Authors: Guo, Qia; * | Shen, Shu-Tingb

Affiliations: [a] Department of Mathematics, Harbin Institute of Technology, Harbin, Heilongjiang, China | [b] Health Science Center, Peking University, Beijing, China

Correspondence: [*] Corresponding author: Qi Guo, Department of Mathematics, Harbin Institute of Technology, Harbin 150001, Heilongjiang, China. Tel.: +86 18946192559; E-mail:guoqi@hit.edu.cn

Keywords: Reproducing kernel, two-dimensional, cardiac tissue model, compact finite difference

DOI: 10.3233/THC-161171

Journal: Technology and Health Care, vol. 24, no. s2, pp. S477-S486, 2016

Published: 13 June 2016
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Abstract

BACKGROUND:

There are two major classes of cardiac tissue models: the ionic model and the FitzHugh-Nagumo model. During computer simulation, each model entails solving a system of complex ordinary differential equations and a partial differential equation with non-flux boundary conditions. The reproducing kernel method possesses significant applications in solving partial differential equations. The derivative of the reproducing kernel function is a wavelet function, which has local properties and sensitivities to singularity. Therefore, study on the application of reproducing kernel would be advantageous.

OBJECTIVE:

Applying new mathematical theory to the numerical solution of the ventricular muscle model so as to improve its precision in comparison with other methods at present.

METHODS:

A two-dimensional reproducing kernel function inspace is constructed and applied in computing the solution of two-dimensional cardiac tissue model by means of the difference method through time and the reproducing kernel method through space.

RESULTS:

Compared with other methods, this method holds several advantages such as high accuracy in computing solutions, insensitivity to different time steps and a slow propagation speed of error. It is suitable for disorderly scattered node systems without meshing, and can arbitrarily change the location and density of the solution on different time layers.

CONCLUSIONS:

The reproducing kernel method has higher solution accuracy and stability in the solutions of the two-dimensional cardiac tissue model.

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