Chepkoech Maurine, Malila Bessie, Mwangama Joyce
Department of Electrical Engineering, University of Cape Town, Rhondebosch, Cape Town, 7700, South Africa.
Division of Biomedical Engineering, University of Cape Town, Anzio Road, Cape Town, 7925, South Africa.
J Robot Surg. 2025 Aug 28;19(1):525. doi: 10.1007/s11701-025-02703-9.
Telementoring in surgical training enables expert surgeons to provide real-time remote guidance to trainees. This technique is increasingly adopted to address surgical training gaps in low- and middle-income countries (LMICs), i.e., nations with a gross national income per capita of $13,845 or less. However, existing systems are constrained by conventional communication systems, which experience high latency, limited bandwidth, and poor video resolution. These challenges hinder the integration of immersive and interactive technologies such as virtual reality (VR), augmented reality (AR), and haptic feedback, which would enhance learning outcomes, especially in resource-constrained environments. AR overlays digital images onto the real-world environment, whereas VR immerses users in a fully computer-generated environment, enabling trainees to interact with surgical components as if they are in the real world. In addition, the advent of the fifth generation of mobile networks (5G), which delivers ultra-low latency, high bandwidth, and support for network slicing, offers a promising foundation for scaling high-fidelity telementoring systems. Moreover, the integration of artificial intelligence (AI), i.e., equipping computer systems with the ability to perform tasks that would typically require human intelligence, can enable real-time performance analytics and skill assessment of the trainees. In regions lacking reliable network backbone infrastructure, such as fiber, hybrid approaches that combine low-cost 5G deployments with satellite communication can be leveraged to achieve reliable end-to-end connectivity. Therefore, this systematic literature review evaluates current surgical telementoring systems, their enabling technologies, and associated challenges, with emphasis on LMIC contexts, where such systems will have the greatest benefits. Through a structured Population, Intervention, Comparison, and Outcome (PICO)-based synthesis, we address five key research questions that span key aspects such as current telementoring systems and technologies, functional and technical requirements, educational outcome effectiveness, and the gaps addressed by modern technology and connection solutions, i.e., 5G, AI, VR, and AR. In addition, we identify recurrent challenges and propose a design framework that can be adopted in low-resource settings. Finally, we outline future development directions, including AI-driven evaluation models, scalable system architectures, and policy frameworks to guide the development of secure, cost-effective, and equitable telementoring platforms to advance global surgical education.
外科培训中的远程指导使专家外科医生能够为学员提供实时远程指导。这种技术越来越多地被用于解决低收入和中等收入国家(LMIC)的外科培训差距,即人均国民总收入为13,845美元或更低的国家。然而,现有的系统受到传统通信系统的限制,这些系统存在高延迟、有限带宽和低视频分辨率的问题。这些挑战阻碍了虚拟现实(VR)、增强现实(AR)和触觉反馈等沉浸式和交互式技术的整合,而这些技术将提高学习效果,特别是在资源有限的环境中。AR将数字图像叠加到现实世界环境中,而VR则将用户沉浸在完全由计算机生成的环境中,使学员能够像在现实世界中一样与手术组件进行交互。此外,第五代移动网络(5G)的出现提供了超低延迟、高带宽和对网络切片的支持,为扩展高保真远程指导系统提供了一个有前景的基础。此外,人工智能(AI)的整合,即让计算机系统具备执行通常需要人类智能的任务的能力,可以实现对学员的实时性能分析和技能评估。在缺乏可靠网络骨干基础设施(如光纤)的地区,可以利用将低成本5G部署与卫星通信相结合的混合方法来实现可靠的端到端连接。因此,本系统文献综述评估了当前的外科远程指导系统、其支持技术和相关挑战,重点关注LMIC背景,在这些背景下此类系统将带来最大益处。通过基于结构化的人群、干预、对照和结局(PICO)的综合分析,我们解决了五个关键研究问题,这些问题涵盖了当前远程指导系统和技术、功能和技术要求、教育成果有效性以及现代技术和连接解决方案(即5G、AI、VR和AR)所解决的差距等关键方面。此外,我们识别了反复出现的挑战,并提出了一个可在资源匮乏环境中采用的设计框架。最后,我们概述了未来的发展方向,包括人工智能驱动的评估模型、可扩展的系统架构以及政策框架,以指导安全、经济高效且公平的远程指导平台的开发,从而推动全球外科教育的发展。