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:微外科手术涉及在显微镜下对微妙的组织或小型血管、神经等脆弱结构进行过度操纵。为解决对人体手的不精确操纵的限制问题,已经开发了机器人系统,以协助外科医生以更精确和安全的方式执行复杂的微观外科任务;然而,机器人辅助微外科手术(RAMS)的急剧学习曲线和训练有素的外科医生的短缺,对广泛采用RAMS提出了重大挑战。因此,有必要为RAMS开发一个多功能的培训系统,为外科医生和病人带来实际好处。在本文中,我们根据ROS-Django网络结构,为微外科医生更精确和安全地执行复杂的微观外科手术任务,开发了一个基于互联网的微外科手术系统(TIMS),协助外科医生执行复杂的微外科外科手术(RAMS)学习曲线曲线曲线,通过ROS-Django框架通过互联网传输实时数据。此外,TRIMS综合了对“指导受训人员以指导为指南,使其不遵循所期望的路径,通过专家的GLEAR进行模拟研究。学习从演示到从实验室分析结果,还用G进行演示。</s>