Object Identification in Remotely-Assisted Robotic Surgery Using Fuzzy Inference System

Introduction

Teleoperated robotic systems have attracted the attention of many people during the last two decades due to their numerous medical and non-medical uses. The emergence of robots in medicine has opened new opportunities for advancement, not just in terms of surgeon precision and comfort, but also in terms of patient benefits. In terms of health applications, two major groups may be distinguished: remote - controlled surgery and teleoperated recovery robotic systems, both of which have shown significant potential in terms of improving healthcare delivery. Teleoperated surgery has been extensively researched and marketed in this line. The sensory-motor capabilities of humans have been significantly enhanced by telerobotic systems. The capacity of humans to attain increased sensorimotor abilities, allowing them to connect with things and places from a distance (Mehrdad et al., 2021). Authors in the domains of image analysis, machine learning, and automation have moved to geometric technologies for collecting and analysing images as a result of recent developments in technology in terms of memory and processing capability. In automation and immersive virtual reality research, information technology is employed to give efficient solutions in clinical imaging, practical surveillance, automation, and computer aided manufacturing (Thilahar & Thilahar, 2019).

Traditional robot assisted systems are made up of a master module and a slave module. The human operator will control the master unit, and the slave system will follow the master robot's actions for interaction with the environment. During surgery, the operative region is frequently the patient's body portion on which the procedure is being conducted. The operator will get sensory information from the operating area in feedback loop. The sensory information repeated by the leader robot for the operator allows her/him to complete the operation. In reality, the most serious worry with human-robot collaboration is safety (Haddadin & Hirzinger, 2010; Haddadin et al., 2009).

The key motivations for telerobotic surgery were the necessity to provide remote medical surgery. Remotely placed hospitals usually have limited resources and skilled physicians on a worldwide scale. This successful study demonstrates the feasibility and possibility of using telerobotic devices for telesurgery in rural and underserved locations. The fundamental issue in this scenario was a large delay. Despite these enlightening tests, current standard practice demands that the patient and the surgeon be at the same hospital. Robots solved the majority of the tasks that could not previously be completed due to security concerns (Bauer et al., 2008; Hägele et al., 2002). Researchers addressed the difficulty of safe human-robot interaction in 2017 while designing architecture for operating a teleoperated industrial manipulator used in surgical applications (Capolei et al., 2017). The investigation's goal was to insert and position a long and light surgical instrument, the laparoscope, properly and safely through a small incision in the patient's skin, which serves as the fulcrum point for tool motions. This eventually brought into question the idea of human interaction, as well as the design of a system that was reactive and safe enough while dealing with several constraints in such a sensitive and unpredictable situation. This challenging issue needs a well-organized architectural design capable of managing several events in real time. Telesurgery offers the ability to enable the “global exchange of medical expertise without the need for specialists to visit.” Another reason surgical telerobots are appealing is their ability to aid surgeons in their training. In addition to that it was found that the human collaboration might result in a significant decrease in workplace accidents as well as the optimization of production processes in a variety of economic industries (Bauer et al., 2008; Kaplan et al., 2016).