A VR teaching method and system for ventricular surgery based on force feedback
By constructing a force-tactile feature waveform retrieval and synthesis model based on multimodal biomechanical data, dynamically matching force feedback signals and combining them with electromyographic signal evaluation, the problems of inaccurate force feedback and incomplete evaluation in VR ventricle surgery training were solved, achieving high-fidelity feedback and multi-dimensional evaluation, thus improving training effectiveness.
CN122090694AInactive Publication Date: 2026-05-26THE FIRST AFFILIATED HOSPITAL OF FUJIAN MEDICAL UNIV
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Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- THE FIRST AFFILIATED HOSPITAL OF FUJIAN MEDICAL UNIV
- Filing Date
- 2026-04-27
- Publication Date
- 2026-05-26
- Estimated Expiration
- Not applicable · inactive patent
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Abstract
This invention discloses a VR ventricular surgery teaching method and system based on force-tactile feedback, comprising: acquiring a multimodal biomechanical annotation dataset and a virtual surgical scene model; constructing a force-tactile feature waveform retrieval and synthesis model based on the two; dynamically matching and generating corresponding force feedback driving signals from the multimodal biomechanical annotation dataset according to the real-time interaction state between the virtual instruments and the virtual surgical scene model; using the force-tactile feature waveform retrieval and synthesis model to drive the force feedback device to perform ventricular puncture operation training, and simultaneously collecting the trainee's surface electromyography signal data and virtual instrument interaction data; based on the collected data and expert data, generating a comprehensive evaluation report including spatial accuracy, operation quality, and electromyography control efficiency indicators through a multi-dimensional operation quantitative evaluation model. This invention achieves high-fidelity force-tactile feedback and in-depth quantitative analysis of operational skills.
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