Parameters identification in constitutive models for soft tissues mechanics

In the framework of the formulation of constitutive models for soft biological tissues an important challenge pertains to the parameters evaluation. Complex constitutive models are adopted for a phenomenological description of the biomechanical response, charac-terised by anisotropy, material non-linearity, almost-incompressibility and large strain and displacement. The present work describes a procedure for estimating the constitu-tive parameters to be adopted, by fitting predicted model results with specific experi-mental data. The approach provides an inverse analysis that uses the stress-strain history given by experimental data and attempts to estimate the parameter values that would yield the best fit for the constitutive model. This action is performed using an optimiza-tion procedure based on a specific algorithm formulated by coupling stochastic and a deterministic techniques. A solution is presented with regard to the periodontal ligament and oesophageal tissues. The reference to different soft biological tissues points out the ability of the approach to properly interpret different configurations and responses. The accuracy and completeness of experimental data influences reliability and completeness of solution. Result validation is performed by comparison of the experimental data and model results