Stochastic hyperelastic constitutive laws and identification procedure for soft biological tissues with intrinsic variability.

Journal Article

In this work, we address the constitutive modeling, in a probabilistic framework, of the hyperelastic response of soft biological tissues. The aim is on the one hand to mimic the mean behavior and variability that are typically encountered in the experimental characterization of such materials, and on the other hand to derive mathematical models that are almost surely consistent with the theory of nonlinear elasticity. Towards this goal, we invoke information theory and discuss a stochastic model relying on a low-dimensional parametrization. We subsequently propose a two-step methodology allowing for the calibration of the model using standard data, such as mean and standard deviation values along a given loading path. The framework is finally applied and benchmarked on three experimental databases proposed elsewhere in the literature. It is shown that the stochastic model allows experiments to be accurately reproduced, regardless of the tissue under consideration.

Full Text

Duke Authors

Cited Authors

  • Staber, B; Guilleminot, J

Published Date

  • January 2017

Published In

Volume / Issue

  • 65 /

Start / End Page

  • 743 - 752

PubMed ID

  • 27764747

Electronic International Standard Serial Number (EISSN)

  • 1878-0180

International Standard Serial Number (ISSN)

  • 1751-6161

Digital Object Identifier (DOI)

  • 10.1016/j.jmbbm.2016.09.022

Language

  • eng