DocumentCode :
2735609
Title :
Parameter optimization technique using the response surface methodology
Author :
Koyamada, K. ; Saki, K. ; Itoch, T.
Author_Institution :
Dept. of Eng., Kyoto Univ., Japan
Volume :
2
fYear :
2004
fDate :
1-5 Sept. 2004
Firstpage :
2909
Lastpage :
2912
Abstract :
We propose a parameter optimization technique using the response surface methodology (RSM) for the accurate biological cell simulation which calculates cell behavior by numerically integrating the differential equation and generates action potentials, intracellular Ca transient, contraction, and intracellular ATP consumption by using parameter values of major ion permeability and amplitude of Ko dependency. Since most of these parameters cannot be directly measured by experiment, these are searched for by applying an optimization technique, that is, by minimizing an objective function defined as a difference between a measured and a calculated waveform of action potentials in a cardiac myocyte. We employ the RSM as the optimization technique. In the RSM, a quadratic polynomial is used in general, and a mathematical technique is used to calculate the extreme points. Because our parameter space cannot be approximated by a single quadratic polynomial surface, we adopt a recursive subdivision technique and use the coefficient of multiple determination to representing a response surface in each subspace for a criteria of the subdivision. We confirmed the effectiveness of the proposed technique by searching for parameters which are determined in advance.
Keywords :
biochemistry; bioelectric potentials; biology computing; calcium; cardiology; cellular biophysics; differential equations; integration; molecular biophysics; optimisation; polynomials; response surface methodology; Ca; action potentials; biological cell simulation; cardiac myocyte; cell behavior; cell contraction; differential equation; intracellular ATP consumption; intracellular Ca transient; ion permeability; numerical integration; parameter optimization technique; quadratic polynomial; recursive subdivision technique; response surface methodology; Bioinformatics; Biological cells; Biological system modeling; Cells (biology); Computational modeling; Differential equations; Optimization methods; Parameter estimation; Power system modeling; Response surface methodology; Parameter optimization; biological cell simulation; response surface methodology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-8439-3
Type :
conf
DOI :
10.1109/IEMBS.2004.1403827
Filename :
1403827
Link To Document :
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