NRI: Guiding with Touch: Haptic Cueing of Surgical Techniques on Virtual and Robotic Platforms

虚拟现实使外科医生能够在不给患者带来风险的情况下进行手术培训。然而，外科受训者收到的反馈是延迟的、主观的和定性的，从而缺乏对快速获得技能的支持。该项目将通过使用基于触摸的线索提供性能反馈来提高手术性能和培训，这些线索传达运动质量和策略，而不是任务结果，如手术时间。这将使受训者得到即时和定量的反馈，并提高难以训练的运动技能的表现。如果这项研究被证明是成功的，就有机会在外科医生的培训方式上做出有意义的改变。血管内手术领域中的协作机器人可以采取多种形式，从模拟患者特定手术的虚拟现实模拟器，实现高保真手术排练，到用于将柔性机器人工具导航到解剖位置的外科手术系统。这样的系统需要大量的技能来使用，反过来，在授予与机器人一起操作的认证之前，需要严格的培训协议。迄今为止，训练协议依赖于熟练观察者的实践和主观反馈，并且在这些系统上获得技能可能是低效的。此外，缺乏获取技能的客观衡量标准。本项目将根据基于运动的性能指标研究对受训者使用触觉反馈，并将评价该反馈模式在模拟和机器人血管内手术任务的性能和培训期间的潜在作用。特别是，该项目将评估提供具体的性能反馈，突出在运动空间中的任务策略的好处，并提供这种直接反馈的学习和保留的任务的效果。

Virtual reality has enabled surgeons to train on procedures without risk to patients. However, the feedback surgical trainees receive is delayed, subjective, and qualitative, thereby lacking support for rapid acquisition of skill. This project will enhance surgical performance and training by providing performance feedback using touch-based cues that convey movement quality and strategies rather than task outcomes like procedure time. This will allow trainees to get feedback that is immediate and quantitative, and result in improved performance in difficult-to-train motor skills. Should this research prove successful, there is an opportunity to make meaningful changes in how surgeons are trained. Co-robots in the endovascular surgical domain can take several forms, from a virtual reality simulator that mimics patient-specific procedures, enabling high-fidelity procedural rehearsal, to telesurgical systems that are used to navigate flexible robotic tools to anatomical locations. Such systems require significant skill to use and, in turn, a rigorous training protocol before certification to operate with the robot is granted. To date, training protocols rely on practice and subjective feedback by a skilled observer, and acquisition of skill on these systems can be inefficient. Furthermore, there is a lack of objective metrics of skill acquisition. This project will investigate the use of haptic feedback to trainees based on motion-based performance metrics, and will evaluate the potential role of this feedback modality during performance and training for simulated and robotic endovascular surgical tasks. In particular, the project will evaluate the benefit of providing specific performance feedback that highlights task strategies in the motion space, and the effect of providing such directed feedback on learning and retention of the task.