Abeywardena, S., Yuan, Q., Tzemanaki, A. et al. (4 more authors) (2019) Estimation of tool-tissue forces in robot-assisted minimally invasive surgery using neural networks. Frontiers in Robotics and AI, 6. 56. ISSN 2296-9144
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.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 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: https://creativecommons.org/licenses/by/4.0/ |
Keywords: | force estimation; haptic feedback; minimally invasive surgery; neural networks; sensor-less sensing |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 12 Oct 2023 09:20 |
Last Modified: | 12 Oct 2023 09:20 |
Published Version: | http://dx.doi.org/10.3389/frobt.2019.00056 |
Status: | Published |
Publisher: | Frontiers Media |
Refereed: | Yes |
Identification Number: | 10.3389/frobt.2019.00056 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:204111 |