In modeling the mechanical behavior of soft tissues, the proper choice of an experiment for identifying material parameters is not an easy task. In this study, a finite element computational framework is used to virtually simulate and assess commonly used experimental setups: rotational rheometer tests, confined- and unconfined-compression tests, and indentation tests. Variance-based global sensitivity analysis is employed to identify which parameters in different experimental setups govern model prediction and are thus more likely to be determined through parameter identification processes. Therefore, a priori assessment of experimental setups provides a base for systematic and reliable parameter identification. It is found that in indentation tests and unconfined-compression tests, incompressibility of soft tissues (adipose tissue in this study) plays an important role at high strain rates. That means bulk stiffness constitutes the main part of the mechanism of tissue response; thus, these experimental setups may not be appropriate for identifying shear stiffness. Also, identified material parameters through loading–unloading shear tests at a certain rate might not be reliable for other rates, since adipose tissue shows highly strain rate dependent behavior. Frequency sweep tests at a wide-enough frequency range seem to be the best setup to capture the strain rate behavior. Moreover, analyzing the sensitivity of model parameters in the different experimental setups provides further insight about the model itself.

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