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Visual kinematic force estimation in robot-assisted surgery–application to knot tying

Edwards, PJ; Colleoni, E; Sridhar, A; Kelly, JD; Stoyanov, D; (2020) Visual kinematic force estimation in robot-assisted surgery–application to knot tying. Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization 10.1080/21681163.2020.1833368. (In press). Green open access

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Abstract

Robot-assisted surgery has potential advantages but lacks force feedback, which can lead to errors such as broken stitches or tissue damage. More experienced surgeons can judge the tool-tissue forces visually and an automated way of capturing this skill is desirable. Methods to measure force tend to involve complex measurement devices or visual tracking of tissue deformation. We investigate whether surgical forces can be estimated simply from the discrepancy between kinematic and visual measurement of the tool position. We show that combined visual and kinematic force estimation can be achieved without external measurements or modelling of tissue deformation. After initial alignment when no force is applied to the tool, visual and kinematic estimates of tool position diverge under force. We plot visual/kinematic displacement with force using vision and marker-based tracking. We demonstrate the ability to discern the forces involved in knot tying and visualize the displacement force using the publicly available JIGSAWS dataset as well as clinical examples of knot tying with the da Vinci surgical system. The ability to visualize or feel forces using this method may offer an advantage to those learning robotic surgery as well as adding to the information available to more experienced surgeons.

Type: Article
Title: Visual kinematic force estimation in robot-assisted surgery–application to knot tying
Open access status: An open access version is available from UCL Discovery
DOI: 10.1080/21681163.2020.1833368
Publisher version: http://dx.doi.org/10.1080/21681163.2020.1833368
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Force estimation, robotic surgery, visual tracking, kinematic tracking
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Surgery and Interventional Sci
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10118802
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