Estimating mechanical properties of soft objects using surface measurements from AR headsets
Authors: 
Max Dang Vu, Gonzalo Daniel Maso Talou, Huidong Bai, Mark Billinghurst, Poul Michael FøNss Nielsen, Martyn Peter Nash, Thiranja Prasad Babarenda GamageAuthors Info & Claims
Article No.: 60, Pages 1 - 2
Abstract
Physics-driven predictions of soft tissue mechanics are vital for various medical interventions. Insights on the mechanical properties of soft tissues are essential for obtaining personalised predictions from these models. This study aims to provide a workflow to identify the material parameters of soft homogeneous materials under gravity loading using 3D surface geometrical measurements acquired from a wearable augmented reality (AR) headset’s depth camera. Preliminary results show that the parameter estimation procedure can successfully recover the ground truth material parameter C1 of a cantilever beam using synthetic surface data. This workflow could be used for real-time navigational guidance during soft tissue treatment procedures.
References
[1]
T.P. Babarenda Gamage, D.T.K. Malcolm, G.D. Maso Talou, A. Mîra, A. Doyle, P.M.F. Nielsen, and M.P. Nash. 2019. An automated computational biomechanics workflow for improving breast cancer diagnosis and treatment. Interface Focus 9, 4 (2019). https://doi.org/10.1098/rsfs.2019.0034
[2]
T.P. Babarenda Gamage, V. Rajagopal, M. Ehrgott, M.P. Nash, and P.M.F. Nielsen. 2011. Identification of mechanical properties of heterogeneous soft bodies using gravity loading. International Journal for Numerical Methods in Biomedical Engineering 27, 4 (2011), 391–407. https://doi.org/10.1002/cnm.1429
[3]
J.C. Dibene and E. Dunn. 2022. HoloLens 2 Sensor Streaming. http://arxiv.org/abs/2211.02648
[4]
S.L. Perkins, M.A. Lin, S. Srinivasan, A.J. Wheeler, B.A. Hargreaves, and B.L. Daniel. 2017. A Mixed-Reality System for Breast Surgical Planning. In 2017 IEEE International Symposium on Mixed and Augmented Reality (ISMAR-Adjunct). 269–274. https://doi.org/10.1109/ISMAR-Adjunct.2017.92
[5]
romaset. 2018. Doctor in a surgical room with virtual reality glasses on the background of the real operation. Stock Photo — stock.adobe.com. https://stock.adobe.com/nz/images/doctor-in-a-surgical-room-with-virtual-reality-glasses-on-the-background-of-the-real-operation/243078687. [Accessed 21-08-2023].
[6]
D. Ungureanu, F. Bogo, S. Galliani, P. Sama, X. Duan, C. Meekhof, J. Stühmer, T.J. Cashman, B. Tekin, J.L. Schönberger, P. Olszta, and M. Pollefeys. 2020. HoloLens 2 Research Mode as a Tool for Computer Vision Research. https://doi.org/10.48550/arXiv.2008.11239
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Published In
October 2023
542 pages
ISBN:9798400703287
DOI:10.1145/3611659
Copyright © 2023 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
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Association for Computing Machinery
New York, NY, United States
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Published: 09 October 2023
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- Refereed limited
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- Ministry for Business, Innovation and Employment New Zealand
- New Zealand Breast Cancer Foundation
- University of Auckland Foundation
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VRST 2023: 29th ACM Symposium on Virtual Reality Software and Technology
October 9 - 11, 2023
Christchurch, New Zealand
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Overall Acceptance Rate 66 of 254 submissions, 26%
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