Convergence of a genetic algorithm for estimating cardiac material properties

Author

Nair, Arun U. ; Taggart, David G. ; Vetter, Frederick J.

Author_Institution

Dept. of Mech. Eng., Rhode Island Univ., Kingston, RI, USA

fYear

2005

fDate

2-3 April 2005

Firstpage

154

Lastpage

156

Abstract

In this paper we present the results of a detailed study of a systematic numerical scheme for estimating material parameters for ventricular myocardium. The numerical scheme combines a real encoded genetic algorithm with nonlinear finite element analysis. The primary objective of this study was to determine optimal population size for the genetic algorithm so as obtain rapid convergence to actual material parameter values. Optimal parameter settings for the genetic algorithm and interdependencies of material parameters were determined through multiple optimization runs.

Keywords

biomechanics; cardiovascular system; finite element analysis; genetic algorithms; muscle; cardiac material properties estimation; genetic algorithm convergence; material interdependencies; nonlinear finite element analysis; systematic numerical scheme; ventricular myocardium; Algorithm design and analysis; Biological cells; Capacitive sensors; Convergence; Finite element methods; Genetic algorithms; Material properties; Myocardium; Slabs; Stress;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioengineering Conference, 2005. Proceedings of the IEEE 31st Annual Northeast

Print_ISBN

0-7803-9105-5

Electronic_ISBN

0-7803-9106-3

Type

conf

DOI

10.1109/NEBC.2005.1431970

Filename

1431970