Parameter Estimation for a Mechatronic Probe of Robot assisted Minimally Invasive Surgery Using Inverse Finite Element Analysis

There is a need to provide haptic and tactile feedback to surgeons during robot-assisted minimally invasive surgery (RMIS). Such feedback is also essential for palpation based diagnostic during cancer removal using MIS. There have been recent efforts at developing a mechatronic finger to mimic some of the palpation capabilities of a human finger. These mechatronic fingers typically record force-displacement characteristics, in order to infer material properties for diagnostic purposes. This paper presents a non-linear finite element based approach for tissue property identification, based on force-displacement characteristics produced by a mechatronic finger, during mechanical palpations. We use finite element modeling and the NewtonRaphson method to estimate soft tissue parameters. To obtain the ground truth data, a sphere-soft tissue indentation experiment is conducted on a silicone phantom and the sphere-tissue interaction is modeled using finite element software ABAQUS. To account for the large deformation behavior of the soft tissue, the Arruda-Boyce hyperelastic model is chosen. Then inverse finite element analysis and the Newton-Raphson method is employed to identify the shear modulus ( ) of the hyperelastic model, employing the static sphere-tissue indentation data as input. The results show that the proposed method can identify soft tissue parameters accurately and robustly with a relatively fast convergence rate. The force-tissue deflection curves predicted by the identified soft tissue parameter are in good agreement with experimental measurements. Keyword: Inverse finite element analysis, Medical tool, Soft tissue, Newton-Raphson method