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

Published: 18 May 2021 Publication History

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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    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
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    Publication History

    Published: 18 May 2021
    Online AM: 07 May 2020
    Accepted: 01 April 2020
    Revised: 01 March 2020
    Received: 01 February 2020
    Published in TOMM Volume 17, Issue 2s

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    Author Tags

    1. Security tele-surgery
    2. RBFNN
    3. bilateral position control
    4. force control

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    Funding Sources

    • National Natural Science Foundation of China
    • China Postdoctoral Science Foundation

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