Optimization of Hyperelastic Constitutive Model Coefficients for Soft Tissue by Imperialistic Competitive Algorithm Based on Experimental Data

The main target of this study is identification of the constitutive model of a soft tissue. For such a purpose a robotic tactile device (Robo-Tac-BMI) was used for breast tissue examinations and stress versus strain was collected for every test point during loading and unloading processes. Utilizing accurate experimental dataset for mechanical modeling of the tissue in conjunction with an optimization algorithm provides a reliable constitutive model of tissue’s mechanical behavior. Eight major hyperelastic models were adapted to the stress-strain data to find the most compatible constitutive equation applicable to the soft tissue mechanical behavior. For this purpose, a new optimization algorithm called Imperialist Competitive Algorithm (ICA) which is based on social and political strategy was used. The novelty of the present study is producing a realistic mathematical model with high accuracy of the soft tissue based on experimental data. The achieved hyperelastic model can be used for prediction of mechanical behavior of the breast tissue in surgery simulation for assistance and educational purposes. Other application of this model is clustering of healthy and cancerous tissue which facilitates the surgeon’s task in the diagnosis procedure. This application also makes the diagnosis procedure almost independent of using imaging techniques or performing biopsies. This model is useful in distinguishing cases where the soft tissue has altered from normal situation like tumors and cancer attacks.