Robot-Assisted Surgical Training Over Several Days in a Virtual Surgical\n Environment with Divergent and Convergent Force Fields
Yousi A. Oquendo, Zonghe Chua, Margaret M. Coad, Ilana Nisky, Anthony Jarc, Sherry M. Wren, Thomas S. Lendvay, Allison M. Okamura
- 发表年份
- 2021
- 引用次数
- 2
- 访问权限
- 开放获取
摘要
Surgical procedures require a high level of technical skill to ensure\nefficiency and patient safety. Due to the direct effect of surgeon skill on\npatient outcomes, the development of cost-effective and realistic training\nmethods is imperative to accelerate skill acquisition. Teleoperated robotic\ndevices allow for intuitive ergonomic control, but the learning curve for these\nsystems remains steep. Recent studies in motor learning have shown that visual\nor physical exaggeration of errors helps trainees to learn to perform tasks\nfaster and more accurately. In this study, we extended the work from two\nprevious studies to investigate the performance of subjects in different force\nfield training conditions, including convergent (assistive), divergent\n(resistive), and no force field (null).\n
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