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This study introduces new camera navigation tasks to the Virtual Basic Laparoscopic Skill Trainer (VBLaST) for improved minimally invasive surgical training. The enhanced simulator offers objective scoring and cost reduction for surgical skill assessment.

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Area of Science:

  • Medical Simulation
  • Surgical Education
  • Human-Computer Interaction

Background:

  • The Fundamentals of Laparoscopic Surgery (FLS) trainer box is a standard for assessing minimally invasive surgical skills.
  • Virtual simulators like VBLaST offer objective scoring and cost-effectiveness for surgical training.
  • Existing VBLaST simulators cover core laparoscopic tasks but lack camera navigation training.

Purpose of the Study:

  • To extend the VBLaST platform by incorporating two new camera navigation tasks: pattern matching and path tracing.
  • To develop a comprehensive camera navigation simulator with a simplified hardware interface and automated metrics.
  • To evaluate the face validity and user experience of the new simulator with medical trainees.

Main Methods:

  • Designed and developed a comprehensive camera navigation simulator integrated into the VBLaST framework.
  • Included two virtual tasks: pattern matching and path tracing.
  • Tested face validity with medical students and residents, gathering feedback on usability and effectiveness.

Main Results:

  • The simulator was rated highly by subjects for its usefulness in training target centering and sizing skills.
  • The system features a simplified hardware interface, graphical user interface, and automated metrics.
  • Force feedback quality and usefulness received the lowest rating (2.62).

Conclusions:

  • The enhanced VBLaST simulator effectively trains camera navigation skills essential for minimally invasive surgery.
  • The system's objective scoring and cost-efficiency make it a valuable tool for surgical education.
  • Further refinement of force feedback may enhance the overall training experience.