Jones, D, Wang, H, Alazmani, A orcid.org/0000-0001-8983-173X et al. (1 more author) (2017) A soft multi-axial force sensor to assess tissue properties in RealTime. In: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems Proceedings. 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 24-28 Sep 2017, Vancouver, BC, Canada. IEEE , pp. 5738-5743. ISBN 978-1-5386-2682-5
Abstract
Objective: This work presents a method for the use of a soft multi-axis force sensor to determine tissue trauma in Minimally Invasive Surgery.
Despite recent developments, there is a lack of effective haptic sensing technology employed in instruments for Minimally Invasive Surgery (MIS). There is thus a clear clinical need to increase the provision of haptic feedback and to perform real-time analysis of haptic data to inform the surgical operator. This paper establishes a methodology for the capture of real-time data through use of an inexpensive prototype grasper. Fabricated using soft silicone and 3D printing, the sensor is able to precisely detect compressive and shear forces applied to the grasper face. The sensor is based upon a magnetic soft tactile sensor, using variations in the local magnetic field to determine force. The performance of the sensing element is assessed and a linear response was observed, with a max hysteresis error of 4.1% of the maximum range of the sensor. To assess the potential of the sensor for surgical sensing, a simulated grasping study was conducted using ex vivo porcine tissue. Two previously established metrics for prediction of tissue trauma were obtained and compared from recorded data. The normalized stress rate (kPa.mm⁻¹) of compression and the normalized stress relaxation (ΔσR) were analyzed across repeated grasps. The sensor was able to obtain measures in agreement with previous research, demonstrating future potential for this approach. In summary this work demonstrates that inexpensive soft sensing systems can be used to instrument surgical tools and thus assess properties such as tissue health. This could help reduce surgical error and thus benefit patients.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017 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: | Robot sensing systems; Surgery; Tools; Face; Force; Stress |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) > Institute of Engineering Systems and Design (iESD) (Leeds) The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) > Institute of Functional Surfaces (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 03 May 2018 12:53 |
Last Modified: | 11 Feb 2019 21:40 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/IROS.2017.8206464 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:130400 |