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This content will become publicly available on September 24, 2025

Title: Training with a Visual-Haptic Simulator for Trocar Insertion
Trocar insertion is a critical first step of all minimally invasive surgery; however, it also carries a high risk for errors. Studies suggest that entry errors are the most common complication in laparoscopic surgery with 4% of errors leading to patient fatality. Surgeon error due to excessive force is often the cause for entry errors; however, adequate training has been shown to reduce the risk of these surgical errors. In practice, institutions lack widespread and relatively inexpensive means to train surgeons for trocar entry that does not involve patient risk. In our prior work, we presented a simple Stewart platform haptic device with a numerical model to simulate key force characteristics of trocar insertion. Evaluation in our first study was limited to device characterization. In this paper, we present a more robust haptic mechanism with higher fidelity linear actuators, an increased workspace, and tissue visualization to accompany haptic cues. We also present a novel upper module that allows for a sudden drop of the trocar after the final puncture event to create a more realistic simulation. We performed a user study with eight novices to investigate how well the device and visualization train users in the trocar insertion procedure. By the end of the experiment, subjects using the device had a normalized error reduction of roughly 85% on average, relative to themselves. This device shows potential for widespread training of trocar insertion, possibly leading to fewer complications and deaths following the procedure. Finally, our upper module also represents an innovative addition for traditional admittance-type haptic device designs, not typically capable of accurately representing motion in free space.  more » « less
Award ID(s):
2109635
PAR ID:
10550500
Author(s) / Creator(s):
; ; ;
Publisher / Repository:
Journal of Medical Robotics Research
Date Published:
Journal Name:
Journal of Medical Robotics Research
ISSN:
2424-905X
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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