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Output-Bounded and RBFNN-Based Position Tracking and Adaptive Force Control for Security Tele-Surgery

Published:18 May 2021Publication History
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Abstract

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.

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  1. Output-Bounded and RBFNN-Based Position Tracking and Adaptive Force Control for Security Tele-Surgery

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    • Published in

      cover image ACM Transactions on Multimedia Computing, Communications, and Applications
      ACM Transactions on Multimedia Computing, Communications, and Applications  Volume 17, Issue 2s
      June 2021
      349 pages
      ISSN:1551-6857
      EISSN:1551-6865
      DOI:10.1145/3465440
      Issue’s Table of Contents

      Copyright © 2021 Association for Computing Machinery.

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 18 May 2021
      • Online AM: 7 May 2020
      • Accepted: 1 April 2020
      • Revised: 1 March 2020
      • Received: 1 February 2020
      Published in tomm Volume 17, Issue 2s

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