IEEE Trans Biomed Eng. 2021 Feb;68(2):685-694. doi: 10.1109/TBME.2020.3011867. Epub 2021 Jan 20.
Virtual Reality (VR) simulators represent a remarkable educational opportunity in order to acquire and refine surgical practical skills. Nevertheless, there exists no consensus regarding a standard curriculum of simulation-based training. This study introduces an automatic, adaptive curriculum where the training session is real-time scheduled on the basis of the trainee's performances.
An experimental study using the master console of the da Vinci Research Kit (Intuitive Surgical Inc., Sunnyvale, US) was carried out to test this approach. Tasks involving fundamental skills of robotic surgery were designed and simulated in VR. Twelve participants without medical background along with twelve medical residents were randomly and equally divided into two groups: a control group, self-managing the training session, and an experimental group, undergoing the proposed adaptive training.
The performances of the experimental users were significantly better with respect to the ones of the control group after training (non-medical: p < 0.01; medical: p = 0.02). This trend was analogous in the non-medical and medical populations and no significant difference was identified between these two classes (even in the baseline assessment).
The analysis of the learning of the involved surgical skills highlighted how the proposed adaptive training managed to better identify and compensate for the trainee's gaps. The absence of initial difference between the non-medical and medical users underlines that robotic surgical devices require specific training before clinical practice.
This feasibility study could pave the way towards the improvement of simulation-based training curricula.
虚拟现实 (VR) 模拟器为获取和完善手术实践技能提供了绝佳的教育机会。然而，目前尚不存在关于基于模拟训练的标准课程的共识。本研究提出了一种自动适应课程，根据学员的表现实时安排培训课程。
本实验使用达芬奇研究套件（美国直觉外科公司）的主控制台进行，旨在测试这种方法。设计并在 VR 中模拟了涉及机器人手术基本技能的任务。十二名无医学背景的参与者和十二名住院医师被随机平均分为两组：对照组，自行管理培训课程；实验组，接受所提出的自适应培训。
实验组学员的表现明显优于对照组学员（非医学组：p < 0.01；医学组：p = 0.02）。这种趋势在非医学和医学人群中是相似的，而且这两个群体之间没有发现显著差异（甚至在基线评估中也没有）。
对所涉及手术技能的学习分析强调了所提出的自适应培训如何更好地识别和弥补学员的差距。非医学和医学用户之间在初始阶段没有差异，这表明机器人手术设备在临床实践之前需要进行特定的培训。
这项可行性研究为改进基于模拟的培训课程铺平了道路。
