Visual Haptic Feedback for Training of Robotic Suturing

Author:

Jourdes François,Valentin Brice,Allard Jérémie,Duriez Christian,Seeliger Barbara

Abstract

Current surgical robotic systems are teleoperated and do not have force feedback. Considerable practice is required to learn how to use visual input such as tissue deformation upon contact as a substitute for tactile sense. Thus, unnecessarily high forces are observed in novices, prior to specific robotic training, and visual force feedback studies demonstrated reduction of applied forces. Simulation exercises with realistic suturing tasks can provide training outside the operating room. This paper presents contributions to realistic interactive suture simulation for training of suturing and knot-tying tasks commonly used in robotically-assisted surgery. To improve the realism of the simulation, we developed a global coordinate wire model with a new constraint development for the elongation. We demonstrated that a continuous modeling of the contacts avoids instabilities during knot tightening. Visual cues are additionally provided, based on the computation of mechanical forces or constraints, to support learning how to dose the forces. The results are integrated into a powerful system-agnostic simulator, and the comparison with equivalent tasks performed with the da Vinci Xi system confirms its realism.

Publisher

Frontiers Media SA

Subject

Artificial Intelligence,Computer Science Applications

Reference44 articles.

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Surgical Stress: The Muscle and Cognitive Demands of Robotic and Laparoscopic Surgery;Annals of Surgery Open;2023-04-28

2. Reduced finite element modelling and closed-loop control of pneumatic-driven soft continuum robots;2023 IEEE International Conference on Soft Robotics (RoboSoft);2023-04-03

3. Telesurgery and Robotics: Current Status and Future Perspectives;Biomedical Engineering;2023-01-25

4. Robotic Microsurgery;Robotic Surgery Devices in Surgical Specialties;2023

5. FEM-Based Dynamic Model for Cable-Driven Parallel Robots with Elasticity and Sagging;Mechanisms and Machine Science;2023

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