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Estimation of tool-tissue forces in robot-assisted minimally invasive surgery using neural networks

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

Authors

Sajeeva Abeywardena

Qiaodi Yuan

Antonia Tzemanaki

Efi Psomopoulou

Chris Melhuish Chris.Melhuish@uwe.ac.uk
Professor of Robotics & Autonomous Systems



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 utilizes 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.

Citation

Abeywardena, S., Yuan, Q., Tzemanaki, A., Psomopoulou, E., Droukas, L., Melhuish, C., & Dogramadzi, S. (2019). Estimation of tool-tissue forces in robot-assisted minimally invasive surgery using neural networks. Frontiers in Robotics and AI, 6, Article 56. https://doi.org/10.3389/frobt.2019.00056

Journal Article Type Article
Acceptance Date Jun 26, 2019
Online Publication Date Jul 16, 2019
Publication Date Jul 16, 2019
Deposit Date Jul 8, 2019
Publicly Available Date Oct 17, 2019
Journal Frontiers in Robotics and AI
Electronic ISSN 2296-9144
Publisher Frontiers Media
Peer Reviewed Peer Reviewed
Volume 6
Article Number 56
DOI https://doi.org/10.3389/frobt.2019.00056
Keywords robotic surgery, force sensing, sensor-less, sensor-less sensing, neural networks, minimally invasive surgery, haptic feedback, force estimation
Public URL https://uwe-repository.worktribe.com/output/1492306
Publisher URL https://www.frontiersin.org/articles/10.3389/frobt.2019.00056/abstract

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Estimation of Tool-Tissue Forces in Robot-Assisted Minimally Invasive Surgery Using Neural Networks (1.3 Mb)
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Licence
http://creativecommons.org/licenses/by/4.0/

Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/

Copyright Statement
Copyright © 2019 Abeywardena, Yuan, Tzemanaki, Psomopoulou, Droukas, Melhuish and Dogramadzi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or
reproduction is permitted which does not comply with these terms.





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