Soft tissue material parameter identification using inverse FEA and 3D-DIC
Zohar Oddes & Dana Solav
An accurate numerical model for the interaction between the human body and an external device is essential for evaluating the performance of the device and for optimizing the device for each patient. However, in contrast to common engineering materials, the patient-specific mechanical parameters of soft biological tissues cannot be obtained using traditional mechanical testing in a non-destructive manner. As an added complication, the mechanical response of soft tissue is highly non-linear in nature which require multiple parameters for its description. Consequently, there may be different parameter sets that result in equally good agreement if the experimental data is insufficient. To tackle this non-uniqueness problem, we investigate which measurements must be conducted in order to ensure a unique and accurate set of material parameters. In this project we conduct controlled indentation tests on soft materials and record the full-field deformations of the surface around the point of indentation using a stereoscopic camera system and a 3D digital image correlation (3D-DIC) software. The experimental results are used as reference data for an inverse FEA process, in which the experiment is recreated in a numerical simulation and the unknown material parameters are optimized to best fit the real-life behavior. We then explore the applicability and the limitations of the proposed method with an aim to derive a reliable, standardized scheme, for identifying the material parameters of soft tissues.