Development of a Robotic Surgery Training System

Author:

Trute Robin Julia,Zapico Carlos Suárez,Christou Andreas,Layeghi Daniel,Craig Stewart,Erden Mustafa Suphi

Abstract

Robotic Surgery is getting widely spread and applied to more and more clinical cases due to its advantages compared to open surgery, for both the patients and surgeons. However, Robotic Surgery requires a different set of skills and learning compared to open and also laparoscopic surgery. Tele-operation for a robotic system with hand controllers, the delay in the hand commands to be translated into robotic movements, slowness of the robotic movements, remote 2D or 3D vision of the actual operation, and lack of haptic feedback are some of the challenges that Robotic Surgery poses. Surgeons need to go through an intensive training for Robotic Surgery, and the learning and skill development continues throughout their early professional years. Despite the importance of training for Robotic Surgery, there are not yet dedicated, low-cost, and widespread training platforms; rather, surgeons mostly train with the same Robotic Surgery system they use in surgery; hence institutions need to invest on a separate surgical setup for training purposes. This is expensive for the institutions, it provides very limited access to the surgeons for training, and very limited, if any, access to researchers for experimentation. To address these, we have developed in our laboratory a low-cost, and experimental Robotic Surgery Trainer. This setup replicates the challenges that a Robotic Surgery system poses and further provides widespread access through internet connected control of the actual physical system. The overall system is composed of equipment that a standard engineering laboratory can afford. In this paper, we introduce the Robotic Surgery Training System and explain its development, parts, and functionality.

Funder

Engineering and Physical Sciences Research Council

Publisher

Frontiers Media SA

Subject

Artificial Intelligence,Computer Science Applications

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Mitigate Inertia for Wrist and Forearm Towards Safe Interaction in 5-DOF Cable-Driven Robot Arm;2023 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM);2023-06-28

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