Martin, JW, Barducci, L, Scaglioni, B orcid.org/0000-0003-4891-8411 et al. (6 more authors) (2022) Robotic Autonomy for Magnetic Endoscope Biopsy. IEEE Transactions on Medical Robotics and Bionics, 4 (3). pp. 599-607. ISSN 2576-3202
Abstract
Magnetically actuated endoscopes are currently transitioning in to clinical use for procedures such as colonoscopy, presenting numerous benefits over their conventional counterparts. Intelligent and easy-to-use control strategies are an essential part of their clinical effectiveness due to the un-intuitive nature of magnetic field interaction. However, work on developing intelligent control for these devices has mainly been focused on general purpose endoscope navigation. In this work, we investigate the use of autonomous robotic control for magnetic colonoscope intervention via biopsy, another major component of clinical viability. We have developed control strategies with varying levels of robotic autonomy, including semi-autonomous routines for identifying and performing targeted biopsy, as well as random quadrant biopsy. We present and compare the performance of these approaches to magnetic endoscope biopsy against the use of a standard flexible endoscope on bench-top using a colonoscopy training simulator and silicone colon model. The semi-autonomous routines for targeted and random quadrant biopsy were shown to reduce user workload with comparable times to using a standard flexible endoscope.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Keywords: | Medical robotics, endoscopes, autonomous systems, robot control, medical device |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Robotics, Autonomous Systems & Sensing (Leeds) |
Funding Information: | Funder Grant number National Institute of Health - NIH (PHS) 2R01EB018992-05 EU - European Union 818045 EU - European Union 952118 EPSRC (Engineering and Physical Sciences Research Council) EP/V047914/1 Cancer Research UK Supplier No: 138573 C64904/A27744 |
Depositing User: | Symplectic Publications |
Date Deposited: | 08 Jul 2022 10:25 |
Last Modified: | 25 Nov 2024 17:32 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers |
Identification Number: | 10.1109/TMRB.2022.3187028 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:188623 |