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. Author manuscript; available in PMC: 2024 Jan 1.
Published in final edited form as: J Biomech. 2022 Nov 25;146:111397. doi: 10.1016/j.jbiomech.2022.111397

Fig. 7. Assessment of parameter identifiability with sensitivity analysis and cost function visualization.

Fig. 7.

The cost function spaces for each two-parameter model indicate unique and identifiable global minima with respect to parameters in the Fung and Ogden models (B,D). However, the cost functions for both the Mooney-Rivlin and Arruda-Boyce models (A,C) exhibit little to no sensitivity with respect to one material parameter. The symmetric sensitivity matrices (upper right hand corners) for the Arruda-Boyce model confirms this finding. Sensitivity matrices for the Fung and Ogden models reveal greater identifiability of the Fung nonlinear parameter compared to the nonlinear parameter in the Ogden model.