In security e-health brain neurosurgery, one of the important processes is to move the electrocoagulation to the appropriate position in order to excavate the diseased tissue. 1 However, it has been problematic for surgeons to freely operate the electrocoagulation, as the workspace is very narrow in the brain. Due to the precision, vulnerability, and important function of brain tissues, it is essential to ensure the precision and safety of brain tissues surrounding the diseased part. The present study proposes the use of a robot-assisted tele-surgery system to accomplish the process. With the aim to achieve accuracy, an output-bounded and RBF neural network–based bilateral position control method was designed to guarantee the stability and accuracy of the operation process. For the purpose of accomplishing a minimal amount of bleeding and damage, an adaptive force control of the slave manipulator was proposed, allowing it to be appropriate to contact the susceptible vessels, nerves, and brain tissues. The stability was analyzed, and the numerical simulation results revealed the high performance of the proposed controls.

中文翻译：

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用于安全远程手术的输出有界和基于 RBFNN 的位置跟踪和自适应力控制

在安全电子健康脑神经外科中，重要的过程之一是将电凝移动到适当的位置以挖掘病变组织。1然而，由于大脑中的工作空间非常狭窄，外科医生无法自由地操作电凝术。由于脑组织的精密性、脆弱性和重要功能，确保病变部位周围脑组织的精密性和安全性至关重要。本研究建议使用机器人辅助远程手术系统来完成该过程。以达到精度为目标，设计了一种基于输出有界和RBF神经网络的双边位置控制方法，以保证操作过程的稳定性和准确性。为了实现最小的出血和损伤，提出了一种从机械手的自适应力控制，使其能够适当地接触易受影响的血管、神经和脑组织。