Pontin, M. and Damian, D.D. orcid.org/0000-0002-0595-0182 (2020) A physical soft tissue growth simulator for implantable robotic devices. IEEE Transactions on Medical Robotics and Bionics, 2 (4). pp. 553-556. ISSN 2576-3202
Abstract
In the development of surgical technologies, one of the challenges in their initial validation has been the creation of accurate bench-top tissue phantoms. Tissue phantoms made of elastomeric material have fixed mechanical properties and are not able to increase in size, so they cannot mimic growth process or change in mechanical properties of their real counterparts. In this work we present a novel real-time soft tissue simulator aimed at testing the in vivo dynamic behavior of robotic implants. The simulator is capable of reproducing mechanical properties of the biological tissue, e.g. viscoelasticity, as well as its metabolism, being able to grow up to 260 mm. A control strategy based on impedance control enables the simulation of changing mechanical properties in real-time, in order to recreate conditions such as fibrosis or tissue scarring. We finally show the platform in use with a soft implant. The electric actuation in conjunction with the 500 Hz control loop frequency guarantees fast and accurate response. We believe our platform has the potential to reduce the need for in vivo preclinical studies and shorten the path to clinical experimentation.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, 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 components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Keywords: | Internal robots; Physical soft tissue simulator; Robotic implant; Tissue growth simulator |
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) |
Funding Information: | Funder Grant number Engineering and Physical Science Research Council EP/S021035/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 29 Sep 2020 06:44 |
Last Modified: | 28 Jan 2022 17:08 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers |
Refereed: | Yes |
Identification Number: | 10.1109/TMRB.2020.3028739 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:165918 |