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A Force-Feedback Methodology for Teleoperated Suturing Task in Robotic-Assisted Minimally Invasive Surgery

With robotic-assisted minimally invasive surgery (RAMIS), patients and surgeons benefit from a reduced incision size and dexterous instruments. However, current robotic surgery platforms lack haptic feedback, which is an essential element of safe operation. Moreover, teleportation control challenges...

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Autores principales: Ehrampoosh, Armin, Shirinzadeh, Bijan, Pinskier, Joshua, Smith, Julian, Moshinsky, Randall, Zhong, Yongmin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9609411/
https://www.ncbi.nlm.nih.gov/pubmed/36298180
http://dx.doi.org/10.3390/s22207829
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author Ehrampoosh, Armin
Shirinzadeh, Bijan
Pinskier, Joshua
Smith, Julian
Moshinsky, Randall
Zhong, Yongmin
author_facet Ehrampoosh, Armin
Shirinzadeh, Bijan
Pinskier, Joshua
Smith, Julian
Moshinsky, Randall
Zhong, Yongmin
author_sort Ehrampoosh, Armin
collection PubMed
description With robotic-assisted minimally invasive surgery (RAMIS), patients and surgeons benefit from a reduced incision size and dexterous instruments. However, current robotic surgery platforms lack haptic feedback, which is an essential element of safe operation. Moreover, teleportation control challenges make complex surgical tasks like suturing more time-consuming than those that use manual tools. This paper presents a new force-sensing instrument that semi-automates the suturing task and facilitates teleoperated robotic manipulation. In order to generate the ideal needle insertion trajectory and pass the needle through its curvature, the end-effector mechanism has a rotating degree of freedom. Impedance control was used to provide sensory information about needle–tissue interaction forces to the operator using an indirect force estimation approach based on data-based models. The operator’s motion commands were then regulated using a hyperplanar virtual fixture (VF) designed to maintain the desired distance between the end-effector and tissue surface while avoiding unwanted contact. To construct the geometry of the VF, an optoelectronic sensor-based approach was developed. Based on the experimental investigation of the hyperplane VF methodology, improved needle–tissue interaction force, manipulation accuracy, and task completion times were demonstrated. Finally, experimental validation of the trained force estimation models and the perceived interaction forces by the user was conducted using online data, demonstrating the potential of the developed approach in improving task performance.
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spelling pubmed-96094112022-10-28 A Force-Feedback Methodology for Teleoperated Suturing Task in Robotic-Assisted Minimally Invasive Surgery Ehrampoosh, Armin Shirinzadeh, Bijan Pinskier, Joshua Smith, Julian Moshinsky, Randall Zhong, Yongmin Sensors (Basel) Article With robotic-assisted minimally invasive surgery (RAMIS), patients and surgeons benefit from a reduced incision size and dexterous instruments. However, current robotic surgery platforms lack haptic feedback, which is an essential element of safe operation. Moreover, teleportation control challenges make complex surgical tasks like suturing more time-consuming than those that use manual tools. This paper presents a new force-sensing instrument that semi-automates the suturing task and facilitates teleoperated robotic manipulation. In order to generate the ideal needle insertion trajectory and pass the needle through its curvature, the end-effector mechanism has a rotating degree of freedom. Impedance control was used to provide sensory information about needle–tissue interaction forces to the operator using an indirect force estimation approach based on data-based models. The operator’s motion commands were then regulated using a hyperplanar virtual fixture (VF) designed to maintain the desired distance between the end-effector and tissue surface while avoiding unwanted contact. To construct the geometry of the VF, an optoelectronic sensor-based approach was developed. Based on the experimental investigation of the hyperplane VF methodology, improved needle–tissue interaction force, manipulation accuracy, and task completion times were demonstrated. Finally, experimental validation of the trained force estimation models and the perceived interaction forces by the user was conducted using online data, demonstrating the potential of the developed approach in improving task performance. MDPI 2022-10-14 /pmc/articles/PMC9609411/ /pubmed/36298180 http://dx.doi.org/10.3390/s22207829 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
Ehrampoosh, Armin
Shirinzadeh, Bijan
Pinskier, Joshua
Smith, Julian
Moshinsky, Randall
Zhong, Yongmin
A Force-Feedback Methodology for Teleoperated Suturing Task in Robotic-Assisted Minimally Invasive Surgery
title A Force-Feedback Methodology for Teleoperated Suturing Task in Robotic-Assisted Minimally Invasive Surgery
title_full A Force-Feedback Methodology for Teleoperated Suturing Task in Robotic-Assisted Minimally Invasive Surgery
title_fullStr A Force-Feedback Methodology for Teleoperated Suturing Task in Robotic-Assisted Minimally Invasive Surgery
title_full_unstemmed A Force-Feedback Methodology for Teleoperated Suturing Task in Robotic-Assisted Minimally Invasive Surgery
title_short A Force-Feedback Methodology for Teleoperated Suturing Task in Robotic-Assisted Minimally Invasive Surgery
title_sort force-feedback methodology for teleoperated suturing task in robotic-assisted minimally invasive surgery
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9609411/
https://www.ncbi.nlm.nih.gov/pubmed/36298180
http://dx.doi.org/10.3390/s22207829
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