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dc.contributor.authorZhong, Yongmin
dc.contributor.authorShirinzadeh, B.
dc.contributor.authorSmith, J.
dc.identifier.citationZhong, Yongmin and Shirinzadeh, Bijian and Smith, Julian. 2007. Soft tissue deformation with neural dynamics for surgery simulation. International Journal of Robotics and Automation 22 (1): pp. 1-9.

Soft tissue deformation is of great importance to virtual-reality-based-surgery simulation. This paper presents a new neural-dynamics-based methodology for simulation of soft tissue deformation from the perspective of energy propagation. A novel neural network is established to propagate the energy generated by an external force among mass points of a soft tissue. The stability of the proposed neural network system is proved by using the Lyapunov stability theory. A potential-based method is presented to derive the internal forces from the natural energy distribution established by the neural dynamics. Integration with a haptic device has been achieved for interactive deformation simulation with force feedback. The proposed methodology not only accommodates isotropic, anisotropic and inhomogeneous materials by simple modification of the control coefficients, but it also accepts large-range deformations.

dc.publisherACTA Press
dc.subjectSurgery simulation
dc.subjectsoft tissue deformation
dc.subjectneural dynamics
dc.subjectneural - networks and haptic feedback
dc.titleSoft tissue deformation with neural dynamics for surgery simulation
dc.typeJournal Article
dcterms.source.titleInternational Journal of Robotics and Automation
curtin.accessStatusFulltext not available

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