Tensor-mass Model based real-time simulation of vessel deformation and force feedback for the interventional surgery training system

Shuxiang Guo, Xiaojuan Cai, Baofeng Gao*, Qiuxia Yang, Yan Zhao, Nan Xiao

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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Abstract

Mass Spring Model (MSM) and Finite Element Method (FEM) are two basic methods for soft model deformation simulation. However, MSM has a high computation efficiency but low accuracy which is only a coarse approximation of the real biological soft tissue while FEM is inverse on the two sides. To achieve realistic and real-time simulation at the same time, in this paper, we proposed an improved non-linear elastic tensor-mass modelling method, which realizes fast computation of non-linear mechanical deformations, and it is suitable for simulating the hollow biological tissue surface. Based on the tensor-mass concept, we applied the tensors of triangles to the surface vessel model, which is distinguished from the current study of tetrahedral tensors while simulating solid tissue, such as liver. Also, we applied an extension of an efficient implicit numerical analytical method for the simulation. Moreover, we introduced a haptic force feedback device for interactions between the vessel model and the virtual medical instrument which improves the realism of the simulation. A set of experiments, including the interactive deformation of the physical vessel model, and the stress-strain data analyses of different nodes and a single node, were conducted to validate the realism, accuracy, steadiness of the TMM model during the simulation. The simulation results showed high efficiency and real time performance over 91 fps which is about 30% higher than the current realistic simulation method in the training system.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages433-438
Number of pages6
ISBN (Electronic)9781509067572
DOIs
Publication statusPublished - 23 Aug 2017
Event14th IEEE International Conference on Mechatronics and Automation, ICMA 2017 - Takamatsu, Japan
Duration: 6 Aug 20179 Aug 2017

Publication series

Name2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017

Conference

Conference14th IEEE International Conference on Mechatronics and Automation, ICMA 2017
Country/TerritoryJapan
CityTakamatsu
Period6/08/179/08/17

Keywords

  • Force feedback
  • Real-time simulation
  • Tensor-Mass Model (TMM)
  • Virtual-reality based surgery training system

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Guo, S., Cai, X., Gao, B., Yang, Q., Zhao, Y., & Xiao, N. (2017). Tensor-mass Model based real-time simulation of vessel deformation and force feedback for the interventional surgery training system. In 2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017 (pp. 433-438). Article 8015856 (2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICMA.2017.8015856