An expertise-oriented Training framework for robotics-Assisted surgery

Mahya Shahbazi, S. Farokh Atashzar, H. Ali Talebi, Rajni V. Patel

Research output: Contribution to journalConference article

Abstract

This paper proposes an expertise-oriented Training platform for robotics-Assisted minimally invasive surgery. The framework builds on previous work of The authors and makes use of dual-user Teleoperation scenario, allowing The presence of an expert in The Training loop. A Fuzzy-Logic (FL) methodology is proposed, which specifies The level/mode of The Training required for The Trainee according To his/her level of proficiency over The Task. A major advantage of The proposed FL approach is That, having The expert in The loop, it can specify The Trainee's proficiency level relative To That of The expert in real-time. Moreover, based on The relative skills assessment, The proposed FL approach decides if or To what extent The Trainee should receive a haptic guidance force based on Virtual Fixtures or The environment force from The interaction between The surgical instrument and Tissue at The slave side. In addition To The level/mode of The haptics-enabled Training required for The Trainee, The proposed FL framework specifies The authority level of The Trainees over The operation in real-time, according To Their proficiency levels over The Task. Stability of The overall closed-loop Teleoperated system is also investigated using The small-gain Theorem, resulting in a sufficient condition To guarantee stability in The presence of constant communication delays. Finally, experimental results are given To evaluate The design and feasibility of The proposed framework.

Original languageEnglish (US)
Article number6907728
Pages (from-to)5902-5907
Number of pages6
JournalProceedings - IEEE International Conference on Robotics and Automation
DOIs
StatePublished - Sep 22 2014
Event2014 IEEE International Conference on Robotics and Automation, ICRA 2014 - Hong Kong, China
Duration: May 31 2014Jun 7 2014

Keywords

  • Dual-User System
  • Fuzzy Logic
  • Relative Skills Assessment
  • Surgical Training
  • Teleoperation

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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