Background:
The difficulty of laparoscopic procedures and the specific psychomotor skills required support the need for a training system for intensive and repetitive practice to acquire the specific skills. The present VR training systems have some limitations with respect to the soft tissue models in the training system. This is associated with the need for a real-time simulation, which requires a balance between computational cost and accuracy.
Objective:
The primary objective of the study is to develop a two dimensional wave equation model that closely mimics the soft tissue manipulation in a laparoscopic procedure for a VR training system.
Methods:
A novel mathematical model based on the wave equation is prepared to represent the interaction between the laparoscopic tool and the soft tissue. The parameters within the model are determined through experimental analysis of a soft tissue phantom. The experimental setup involves a linear actuator applying force to the soft tissue phantom to generate deformation. Data acquisition is conducted through a camera and a robotic force acquisition system which measures force, displacement of the linear actuator and records a video. Through image processing, the displacements of the markers on the phantom’s x-y plane during its deformation are determined and these parameters are used to develop the model, which finally is validated through a comparative analysis.
Results:
The results from the developed model are observed and compared statistically as well as graphically with the finite element model based on deformation data. The results show that the deformation data between the developed model and the available model is significantly similar.
Conclusion:
This study demonstrates the adaptability of the wave equation to meet the needs of the specific surgical procedure through modification of the model based on the experimental data. Moreover, the comparative analysis further corroborates the relevance and validity of the model for the surgical training system.
Polytopic model based interaction control for soft tissue manipulation
