Estimation of Tool-Tissue Forces in Robot-Assisted Minimally Invasive Surgery using Neural Networks

Sajeeva Abeywardena*, Qiaodi Yuan, Antonia Tzemanaki, Efi Psomopoulou, Leonidas Droukas, Chris Melhuish, Sanja Dogramadzi

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

11 Citations (Scopus)
232 Downloads (Pure)

Abstract

A new algorithm is proposed to estimate the tool-tissue force interaction in robot-assisted minimally invasive surgery which does not require the use of external force sensing. The proposed method utilises the current of the motors of the surgical instrument and neural network methods to estimate the force interaction. Offline and online testing is conducted to assess the feasibility of the developed algorithm. Results showed that the developed method has promise in allowing online estimation of tool-tissue force and could thus enable haptic feedback in robotic surgery to be provided.
Original languageEnglish
Article number56
Number of pages11
JournalFrontiers in Robotics and AI
Volume6
Early online date16 Jul 2019
DOIs
Publication statusE-pub ahead of print - 16 Jul 2019

Bibliographical note

Funding Information:
Funding. This work was supported by the European Union's Horizon 2020 research and innovation programme under grant agreement No. 732515.

Funding Information:
This work was supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 732515.

Publisher Copyright:
© Copyright © 2019 Abeywardena, Yuan, Tzemanaki, Psomopoulou, Droukas, Melhuish and Dogramadzi.

Keywords

  • sensor-less sensing
  • neural networks
  • minimally invasive surgery
  • haptic feedback
  • force estimation

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