TY - GEN
T1 - Tensor-mass Model based real-time simulation of vessel deformation and force feedback for the interventional surgery training system
AU - Guo, Shuxiang
AU - Cai, Xiaojuan
AU - Gao, Baofeng
AU - Yang, Qiuxia
AU - Zhao, Yan
AU - Xiao, Nan
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/8/23
Y1 - 2017/8/23
N2 - 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.
AB - 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.
KW - Force feedback
KW - Real-time simulation
KW - Tensor-Mass Model (TMM)
KW - Virtual-reality based surgery training system
UR - http://www.scopus.com/inward/record.url?scp=85030314537&partnerID=8YFLogxK
U2 - 10.1109/ICMA.2017.8015856
DO - 10.1109/ICMA.2017.8015856
M3 - Conference contribution
AN - SCOPUS:85030314537
T3 - 2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017
SP - 433
EP - 438
BT - 2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th IEEE International Conference on Mechatronics and Automation, ICMA 2017
Y2 - 6 August 2017 through 9 August 2017
ER -