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Published on: August 9, 2024
Multi-Information Fuzzy Fusion for Position and Orientation Prediction in Robot-Assisted Vascular Intervention
Zhi Hu1, Wenan Zhang2, Shaozong Xin1
1Laboratory of Intelligent Control and Robotics, Shanghai University of Engineering Science, Shanghai, China.
Summary
This study introduces a fuzzy fusion method for real-time catheter tracking in robot-assisted surgery, enhancing force feedback and improving surgical safety. The new approach offers greater system transparency compared to traditional methods.
Area of Science:
- Robotics
- Medical Engineering
- Vascular Surgery
Background:
- Force feedback is crucial for safety and efficiency in robot-assisted vascular surgery.
- Accurate modeling of catheter-vascular wall interaction is challenging due to complex contact dynamics (bending, torsion).
- System time delays degrade transparency and hinder precise control.
Purpose of the Study:
- To develop a real-time catheter position and orientation estimation method.
- To improve force feedback fidelity and system transparency in robot-assisted vascular surgery.
- To enhance surgical safety through improved control and feedback.
Main Methods:
- A multi-information fuzzy fusion prediction method incorporating prior surgical experience.
- Real-time estimation of catheter position and orientation.
- An extended Fitts' law formulation for dual-motion collaborative mode to estimate surgical movement time.
Main Results:
- The proposed method demonstrated superior system transparency compared to traditional extrapolation and Kalman prediction.
- Enhanced force feedback fidelity was achieved.
- Experimental validation confirmed the effectiveness of the fuzzy fusion approach.
Conclusions:
- The developed method significantly improves surgical safety in robot-assisted vascular procedures.
- It offers a promising solution for overcoming limitations in current robotic surgery systems.
- Real-time estimation and enhanced feedback contribute to more reliable surgical outcomes.
