A Study on Dual-Mode Hybrid Dynamics Finite Element Algorithm for Human Soft Tissue Deformation Simulation

The simulation of human soft tissue deformation is a key issue in the research of surgical simulators. The most mathematically accurate model for soft tissue behavior is the finite element model (FEM), being the most widely adopted numerical approach for nonlinear continuum mechanics equations. The total Lagrangian explicit dynamics (TLED) model is a nonlinear FEM that could simulate the nonlinear deformation of soft tissues accurately and in real time. However, the main problems faced by this method are the high computational cost and the real-time performance of the simulation. Therefore, the linear FEM is used for ensuring computational efficiency and real-time performance of the simulation, though it is inadequate for capturing true biomechanical behavior. Consequently, we have to solve the problems of real-time performance and computational efficiency of nonlinear finite elements in simulating soft tissue deformation. To address this computational challenge, we propose a Dual-Mode Hybrid Dynamics Finite Element Algorithm (DHD-FEA). First, we divide the deformed soft tissues into the surgical area and the non-surgical area. Then, the TLED nonlinear FEM is applied to the simulation of soft tissue deformation in the surgical area, ensuring the accuracy of the simulation effect. Simultaneously, the simulation of soft tissue deformation in the non-surgical area using the linear FEM improves the real-time performance of the simulation and reduces the overall computational cost. Numerical results demonstrate that the error rate in the simulation of the DHD-FEA is lower than that of the complete linear FEM, and the computational efficiency is higher than that of the TLED. Therefore, the DHD-FEA not only ensures the accuracy of soft tissue simulation in the surgical area but also reduces the computational cost.