dc.contributor.author |
Parker, Matthew D |
en |
dc.contributor.author |
Babarenda Gamage, Thiranja |
en |
dc.contributor.author |
Haji Rassouliha, Amir |
en |
dc.contributor.author |
Taberner, Andrew |
en |
dc.contributor.author |
Nash, Martyn |
en |
dc.contributor.author |
Nielsen, Poul |
en |
dc.date.accessioned |
2020-01-12T22:55:01Z |
en |
dc.date.issued |
2019-08 |
en |
dc.identifier.citation |
Biomechanics and modeling in mechanobiology 18(4):1031-1045 Aug 2019 |
en |
dc.identifier.issn |
1617-7959 |
en |
dc.identifier.uri |
http://hdl.handle.net/2292/49611 |
en |
dc.description.abstract |
Many computer vision algorithms have been presented to track surface deformations, but few have provided a direct comparison of measurements with other stereoscopic approaches and physics-based models. We have previously developed a phase-based cross-correlation algorithm to track dense distributions of displacements over three-dimensional surfaces. In the present work, we compare this algorithm with one that uses an independent tracking system, derived from an array of fluorescent microspheres. A smooth bicubic Hermite mesh was fitted to deformations obtained from the phase-based cross-correlation data. This mesh was then used to estimate the microsphere locations, which were compared to stereo reconstructions of the microsphere positions. The method was applied to a 35 mm × 35 mm × 35 mm soft silicone gel cube under indentation, with three square bands of microspheres placed around the indenter tip. At an indentation depth of 4.5 mm, the root-mean-square (RMS) differences between the reconstructed positions of the microspheres and their identified positions for the inner, middle, and outer bands were 60 µm, 20 µm, and 19 µm, respectively. The usefulness of the strain-tracking data for physics-based finite element modelling of large deformation mechanics was then demonstrated by estimating a neo-Hookean stiffness parameter for the gel. At the optimal constitutive parameter estimate, the RMS difference between the measured microsphere positions and their finite element model-predicted locations was 143 µm. |
en |
dc.format.medium |
Print-Electronic |
en |
dc.language |
eng |
en |
dc.relation.ispartofseries |
Biomechanics and modeling in mechanobiology |
en |
dc.rights |
Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. |
en |
dc.rights.uri |
https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm |
en |
dc.rights.uri |
https://www.springer.com/gp/open-access/publication-policies/self-archiving-policy |
en |
dc.subject |
Microspheres |
en |
dc.subject |
Phantoms, Imaging |
en |
dc.subject |
Surface Properties |
en |
dc.subject |
Robotics |
en |
dc.subject |
Finite Element Analysis |
en |
dc.subject |
Models, Biological |
en |
dc.subject |
Image Processing, Computer-Assisted |
en |
dc.title |
Surface deformation tracking and modelling of soft materials. |
en |
dc.type |
Journal Article |
en |
dc.identifier.doi |
10.1007/s10237-019-01127-3 |
en |
pubs.issue |
4 |
en |
pubs.begin-page |
1031 |
en |
pubs.volume |
18 |
en |
dc.rights.holder |
Copyright: Springer-Verlag GmbH Germany, part of Springer Nature 2019 |
en |
pubs.end-page |
1045 |
en |
pubs.publication-status |
Published |
en |
dc.rights.accessrights |
http://purl.org/eprint/accessRights/RestrictedAccess |
en |
pubs.subtype |
Journal Article |
en |
pubs.elements-id |
763930 |
en |
pubs.org-id |
Bioengineering Institute |
en |
pubs.org-id |
ABI Associates |
en |
pubs.org-id |
Engineering |
en |
pubs.org-id |
Engineering Science |
en |
pubs.org-id |
Science |
en |
pubs.org-id |
Science Research |
en |
pubs.org-id |
Maurice Wilkins Centre (2010-2014) |
en |
dc.identifier.eissn |
1617-7940 |
en |
pubs.record-created-at-source-date |
2019-02-20 |
en |
pubs.dimensions-id |
30778884 |
en |