Abstract

Current virtual reality-based (VR) simulators for robot-assisted minimally invasive surgery (RAMIS) training lack effective teaching and coaching. Our objective was to develop an automated teaching framework for VR training in RAMIS. Second, we wanted to study the effect of such real-time teaching cues on surgical technical skill acquisition. Third, we wanted to assess skill in terms of surgical technique in addition to traditional time and motion efficiency metrics. We implemented six teaching cues within a needle passing task on the da Vinci Skills Simulator platform (noncommercial research version). These teaching cues are graphical overlays designed to demonstrate ideal surgical technique, e.g., what path to follow while passing needle through tissue. We created three coaching modes: TEACH (continuous demonstration), METRICS (demonstration triggered by performance metrics), and USER (demonstration upon user request). We conducted a randomized controlled trial where the experimental group practiced using automated teaching and the control group practiced in a self-learning manner without automated teaching. We analyzed data from 30 participants (14 in experimental and 16 in control group). After three practice repetitions, control group showed higher improvement in time and motion efficiency, while experimental group showed higher improvement in surgical technique compared to their baseline measurements. The experimental group showed more improvement than the control group on a surgical technique metric (at what angle is needle grasped by an instrument), and the difference between groups was statistically significant. In a pilot randomized controlled trial, we observed that automated teaching cues can improve the performance of surgical technique in a VR simulator for RAMIS needle passing. Our study was limited by its recruitment of nonsurgeons and evaluation of a single configuration of coaching modes.

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