Finite Element Simulation Of Electrode Implantation Process

In the process of deep brain stimulation surgery, the interaction between the implanted electrodes and the brain can cause bending deformation of the implanted electrodes, as a result, the stimulated part may not be the predetermined position, resulting in the failure of the operation. In this paper, we use the dynamics simulation software LS-DYNA building the model of implanting process. Then designing experimental platform, through the experimental data measured in the experiment platform, we verified the correctness of the simulation model. The model can help to reduce the operation error and improve the precision of target location.Then the paper introduced material properties of brain tissue and classical research methods, and compared different forms and scope of constitutive equation. This paper has selected mechanical model of Mooney-Rivlin as a nonlinear hyperelastic characteristics. Mooney-Rivlin constitutive equation need less material parameters, so it is very stable and at the same time can be used to predict other deformation results of calculation results. The paper has introduced material failure criteria of the brain tissue and selected Johnson-Cook model.Use the finite element simulation software LS-DYNA on electrode implanting dynamic simulation. This paper has solved the material parameters required by the model, then established corresponding geometric models, meshed, loaded and constraint, finally solved. Then the paper took analysis of the force of the electrode with different speed and the target displacement.In order to verify the validity of finite element model, the paper designed an experiment, including experiment requirements, experimental platform, experimental data acquisition and analysis processing, finally carried on the experiment. When the electrodes implanted in the brain with2mm/s, the sensors collected data and analyzed it, getting the graph of the electrode force. Then comparing with the results of finite element simulation, we validated the correctness of the simulation model, and analyzed the reason of the error between the experiment and the model.