Method for establishing a virtual training system for surgery based on robot-assisted intracranial fine operation
By combining Qt modules, OpenGL modules, and the external library Chai3d, a surgical virtual training system was established. The Sigma.7 force feedback tactile device was integrated. Based on the cranium and LHDM model, a progressive layered constraint-driven cutting method was adopted to solve the problem of unrealistic incision edge and internal effects in the surgical virtual training system, and a balance between high-precision tactile feedback and computational efficiency was achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- TIANJIN UNIVERSITY OF TECHNOLOGY
- Filing Date
- 2026-02-11
- Publication Date
- 2026-05-29
AI Technical Summary
Existing surgical virtual training systems suffer from insufficient smoothness at the incision edges, unrealistic internal incision effects, and reduced realism in force feedback, thus affecting the immersion and precision of the operation.
A surgical virtual training system was built by combining Qt modules, OpenGL modules, and the external library Chai3d. The force feedback haptic device Sigma.7 was integrated. Based on the cranial brain model and LHDM model, a progressive hierarchical constraint-driven cutting method was adopted. Interactive operation was performed through the force feedback haptic device Sigma.7, and performance data was optimized.
It achieves real-time haptic feedback, enhances the immersiveness and interactive precision of operation, ensures the accuracy of brain tissue deformation, reduces computational overhead, improves incision smoothness and internal structural integrity, and provides a safe and reliable training method.
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