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A Transparent Teleoperated Robotic Surgical System with Predictive Haptic Feedback and Force Modelling

In recent years, robotic minimally invasive surgery has transformed many types of surgical procedures and improved their outcomes. Implementing effective haptic feedback into a teleoperated robotic surgical system presents a significant challenge due to the trade-off between transparency and stabili...

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Autores principales: Batty, Taran, Ehrampoosh, Armin, Shirinzadeh, Bijan, Zhong, Yongmin, Smith, Julian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9780898/
https://www.ncbi.nlm.nih.gov/pubmed/36560138
http://dx.doi.org/10.3390/s22249770
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author Batty, Taran
Ehrampoosh, Armin
Shirinzadeh, Bijan
Zhong, Yongmin
Smith, Julian
author_facet Batty, Taran
Ehrampoosh, Armin
Shirinzadeh, Bijan
Zhong, Yongmin
Smith, Julian
author_sort Batty, Taran
collection PubMed
description In recent years, robotic minimally invasive surgery has transformed many types of surgical procedures and improved their outcomes. Implementing effective haptic feedback into a teleoperated robotic surgical system presents a significant challenge due to the trade-off between transparency and stability caused by system communication time delays. In this paper, these time delays are mitigated by implementing an environment estimation and force prediction methodology into an experimental robotic minimally invasive surgical system. At the slave, an exponentially weighted recursive least squares (EWRLS) algorithm estimates the respective parameters of the Kelvin–Voigt (KV) and Hunt–Crossley (HC) force models. The master then provides force feedback by interacting with a virtual environment via the estimated parameters. Palpation experiments were conducted with the slave in contact with polyurethane foam during human-in-the-loop teleoperation. The experimental results indicated that the prediction RMSE of error between predicted master force feedback and measured slave force was reduced to 0.076 N for the Hunt–Crossley virtual environment, compared to 0.356 N for the Kelvin–Voigt virtual environment and 0.560 N for the direct force feedback methodology. The results also demonstrated that the HC force model is well suited to provide accurate haptic feedback, particularly when there is a delay between the master and slave kinematics. Furthermore, a haptic feedback approach that incorporates environment estimation and force prediction improve transparency during teleoperation. In conclusion, the proposed bilateral master–slave robotic system has the potential to provide transparent and stable haptic feedback to the surgeon in surgical robotics procedures.
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spelling pubmed-97808982022-12-24 A Transparent Teleoperated Robotic Surgical System with Predictive Haptic Feedback and Force Modelling Batty, Taran Ehrampoosh, Armin Shirinzadeh, Bijan Zhong, Yongmin Smith, Julian Sensors (Basel) Article In recent years, robotic minimally invasive surgery has transformed many types of surgical procedures and improved their outcomes. Implementing effective haptic feedback into a teleoperated robotic surgical system presents a significant challenge due to the trade-off between transparency and stability caused by system communication time delays. In this paper, these time delays are mitigated by implementing an environment estimation and force prediction methodology into an experimental robotic minimally invasive surgical system. At the slave, an exponentially weighted recursive least squares (EWRLS) algorithm estimates the respective parameters of the Kelvin–Voigt (KV) and Hunt–Crossley (HC) force models. The master then provides force feedback by interacting with a virtual environment via the estimated parameters. Palpation experiments were conducted with the slave in contact with polyurethane foam during human-in-the-loop teleoperation. The experimental results indicated that the prediction RMSE of error between predicted master force feedback and measured slave force was reduced to 0.076 N for the Hunt–Crossley virtual environment, compared to 0.356 N for the Kelvin–Voigt virtual environment and 0.560 N for the direct force feedback methodology. The results also demonstrated that the HC force model is well suited to provide accurate haptic feedback, particularly when there is a delay between the master and slave kinematics. Furthermore, a haptic feedback approach that incorporates environment estimation and force prediction improve transparency during teleoperation. In conclusion, the proposed bilateral master–slave robotic system has the potential to provide transparent and stable haptic feedback to the surgeon in surgical robotics procedures. MDPI 2022-12-13 /pmc/articles/PMC9780898/ /pubmed/36560138 http://dx.doi.org/10.3390/s22249770 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Batty, Taran
Ehrampoosh, Armin
Shirinzadeh, Bijan
Zhong, Yongmin
Smith, Julian
A Transparent Teleoperated Robotic Surgical System with Predictive Haptic Feedback and Force Modelling
title A Transparent Teleoperated Robotic Surgical System with Predictive Haptic Feedback and Force Modelling
title_full A Transparent Teleoperated Robotic Surgical System with Predictive Haptic Feedback and Force Modelling
title_fullStr A Transparent Teleoperated Robotic Surgical System with Predictive Haptic Feedback and Force Modelling
title_full_unstemmed A Transparent Teleoperated Robotic Surgical System with Predictive Haptic Feedback and Force Modelling
title_short A Transparent Teleoperated Robotic Surgical System with Predictive Haptic Feedback and Force Modelling
title_sort transparent teleoperated robotic surgical system with predictive haptic feedback and force modelling
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9780898/
https://www.ncbi.nlm.nih.gov/pubmed/36560138
http://dx.doi.org/10.3390/s22249770
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