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Enabling personalization of a robotic surgery procedure via a surgery training simulator

Published online by Cambridge University Press:  27 July 2022

Mehmet İsmet Can Dede*
Affiliation:
Department of Mechanical Engineering, Izmir Institute of Technology, Izmir, Turkey
Tarık Büyüköztekin
Affiliation:
Department of Mechanical Engineering, Izmir Institute of Technology, Izmir, Turkey
Şahin Hanalioğlu
Affiliation:
Department of Neurosurgery, Hacettepe University Faculty of Medicine, Ankara, Turkey
İlkay Işıkay
Affiliation:
Department of Neurosurgery, Hacettepe University Faculty of Medicine, Ankara, Turkey
Mustafa Berker
Affiliation:
Department of Neurosurgery, Hacettepe University Faculty of Medicine, Ankara, Turkey
*
*Corresponding author. E-mail: candede@iyte.edu.tr

Abstract

Although robotic or robot-assisted surgery has been increasingly used by many surgical disciplines, its application in cranial or skull base surgery is still in its infancy. Master-slave teleoperation setting of these robotic systems enables these surgical procedures to be replicated in a virtual reality environment for surgeon training purposes. A variety of teleoperation modes were previously determined with respect to the motion capability of the surgeon’s hand that wears the ring as the surgeon handles a surgical tool inside the surgical workspace. In this surgery training simulator developed for a robot-assisted endoscopic skull base surgery, a new strategy is developed to identify the preferred motion axes of the surgeon. This simulator is designed specifically for tuning the teleoperation system for each surgeon via the identification. This tuning capability brings flexibility to adjust the system operation with respect to the motion characteristics of the surgeon.

Type
Research Article
Copyright
© The Author(s), 2022. Published by Cambridge University Press

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