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：显微外科手术涉及在显微镜下对微小血管、神经等脆弱组织或结构进行灵巧操作。为弥补人手工操作精度不足的局限，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显微外科任务。然而，机器人辅助显微外科手术（RAMS）陡峭的学习曲线以及训练有素外科医生的短缺，严重阻碍了RAMS的广泛应用。因此，开发一种通用的RAMS训练系统至关重要，该系统可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显微操作训练系统（TIMS），用于显微外科训练。该系统可通过可穿戴触觉显示设备（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，可"引导"受训者跟随由专家外科医生提供的期望轨迹。基于高斯过程回归（GPR）的示教学习用于生成期望轨迹。通过用户研究，我们验证了所提TIMS的有效性，对比了有无触觉反馈和/或触觉引导条件下用户的操作表现。