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Visual Haptic Feedback for Training of Robotic Suturing.

François Jourdes1, Brice Valentin1, Jérémie Allard1

  • 1InSimo SAS, Strasbourg, France.

Frontiers in Robotics and AI
|February 21, 2022
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Summary

This study introduces a realistic suture simulation for robotic surgery training. It enhances realism with advanced modeling and visual cues, reducing the learning curve for surgical trainees.

Keywords:
collision detectionhapticsknot-tyingminimally invasive surgeryrobotic surgery trainingsurgical simulationvirtual reality

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Area of Science:

  • Robotics
  • Surgical Simulation
  • Medical Training

Background:

  • Current surgical robotic systems lack force feedback, necessitating extensive practice for novices to rely on visual cues for force control.
  • High forces are often applied by novices due to the absence of tactile sensation, impacting patient safety and surgical outcomes.
  • Previous studies show visual force feedback can reduce applied forces, highlighting the need for effective training tools.

Purpose of the Study:

  • To develop a realistic interactive suture simulation for training suturing and knot-tying in robotically-assisted surgery.
  • To enhance the realism of surgical simulations by incorporating advanced modeling techniques for tissue interaction.
  • To provide visual force feedback cues to aid trainees in learning appropriate force application.

Main Methods:

  • Development of a global coordinate wire model with novel constraints for tissue elongation simulation.
  • Implementation of continuous contact modeling to prevent instabilities during knot-tying simulations.
  • Integration of visual cues derived from mechanical force and constraint computations.

Main Results:

  • The developed simulation accurately models tissue deformation and interaction during suturing and knot-tying tasks.
  • Continuous contact modeling successfully prevented instabilities, particularly during knot tightening.
  • Visual force cues effectively supported trainees in modulating applied forces, mimicking real surgical scenarios.
  • The system-agnostic simulator demonstrated high realism when compared to tasks performed on the da Vinci Xi surgical system.

Conclusions:

  • The presented realistic suture simulation offers a valuable tool for training robotically-assisted surgery skills outside the operating room.
  • The advanced modeling and visual feedback mechanisms contribute to improved force control and reduced learning curves for surgical trainees.
  • This simulation technology has the potential to enhance surgical proficiency and patient safety in robotic surgery.