Microsurgery involves the dexterous manipulation of delicate tissue or fragile structures such as small blood vessels, nerves, etc., under a microscope. To address the limitation of imprecise manipulation of human hands, robotic systems have been developed to assist surgeons in performing complex microsurgical tasks with greater precision and safety. However, the steep learning curve for robot-assisted microsurgery (RAMS) and the shortage of well-trained surgeons pose significant challenges to the widespread adoption of RAMS. Therefore, the development of a versatile training system for RAMS is necessary, which can bring tangible benefits to both surgeons and patients. In this paper, we present a Tactile Internet-Based Micromanipulation System (TIMS) based on a ROS-Django web-based architecture for microsurgical training. This system can provide tactile feedback to operators via a wearable tactile display (WTD), while real-time data is transmitted through the internet via a ROS-Django framework. In addition, TIMS integrates haptic guidance to `guide' the trainees to follow a desired trajectory provided by expert surgeons. Learning from demonstration based on Gaussian Process Regression (GPR) was used to generate the desired trajectory. User studies were also conducted to verify the effectiveness of our proposed TIMS, comparing users' performance with and without tactile feedback and/or haptic guidance.

翻译：显微手术涉及在显微镜下对脆弱组织或微小结构（如小血管、神经等）进行灵巧操作。为了解决人手操作不精确的局限性，机器人系统已被开发用于辅助外科医生以更高的精度和安全性完成复杂的显微手术任务。然而，机器人辅助显微手术（RAMS）陡峭的学习曲线以及训练有素外科医生的短缺，对其广泛应用构成了重大挑战。因此，开发一种面向RAMS的多功能训练系统十分必要，这将为外科医生和患者带来切实益处。本文提出了一种基于ROS-Django网络架构的触觉互联网微操纵系统（TIMS），用于显微手术训练。该系统可通过可穿戴触觉显示器（WTD）向操作者提供触觉反馈，同时通过ROS-Django框架实现实时数据的互联网传输。此外，TIMS集成了触觉引导功能，以“引导”受训者沿专家外科医生设定的期望轨迹进行操作。基于高斯过程回归（GPR）的示教学习被用于生成期望轨迹。我们还开展了用户研究，通过比较有无触觉反馈和/或触觉引导时用户的操作表现，验证了所提出的TIMS的有效性。