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Sensitivity Analysis of Cardiac Electrophysiological Models Using Polynomial Chaos

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3 Author(s)
Geneser, S.E. ; Sci. Comput. & Imaging Inst., Utah Univ., Salt Lake City, UT ; Kirby, R.M. ; Sachse, F.B.

Mathematical models of biophysical phenomena have proven useful in the reconstruction of experimental data and prediction of biological behavior. By quantifying the sensitivity of a model to certain parameters, one can place an appropriate amount of emphasis in the accuracy with which those parameters are determined. In addition, investigation of stochastic parameters can lead to a greater understanding of the behavior captured by the model. This can lead to possible model reductions, or point out shortcomings to be addressed. We present polynomial chaos as a computationally efficient alternative to Monte Carlo for assessing the impact of stochastically distributed parameters on the model predictions of several cardiac electrophysiological models

Published in:

Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the

Date of Conference:

17-18 Jan. 2006