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DC Field | Value | Language |
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dc.contributor.author | Cullen, S | - |
dc.contributor.author | Mackay, R | - |
dc.contributor.author | Mohagheghi, A | - |
dc.contributor.author | Du, X | - |
dc.date.accessioned | 2023-12-19T16:48:39Z | - |
dc.date.available | 2023-12-19T16:48:39Z | - |
dc.date.issued | 2023-12-18 | - |
dc.identifier | ORCiD: Sean Cullen https://orcid.org/0000-0002-9515-9000 | - |
dc.identifier | ORCiD: Ruth Mackay https://orcid.org/0000-0002-6456-6914 | - |
dc.identifier | ORCiD: Amir Mohagheghi https://orcid.org/0000-0003-4295-3718 | - |
dc.identifier | ORCiD: Xinli Du https://orcid.org/0000-0003-2604-0804 | - |
dc.identifier.citation | Cullen S. et al. (2023) 'Low-Cost Smartphone Photogrammetry Accurately Digitises Positive Socket and Limb Casts', Prosthesis, 5 (4), pp. 1382 - 1392. doi: 10.3390/prosthesis5040095. | en_US |
dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/27888 | - |
dc.description | Data Availability Statement: The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy. | - |
dc.description.abstract | Digitising prosthetic sockets and moulds is critical for advanced fabrication techniques enabling reduced lead times, advanced computer modelling, and personalised design history. Current 3D scanners are expensive (>GBP 5000) and difficult to use, restricting their use by prosthetists. In this paper, we explore the use and accuracy of smartphone photogrammetry (<GBP 1000) as an accessible means of digitising rectified socket moulds. A reversed digital twin method was used for evaluating accuracy, in addition to simplified genetic algorithms to identify an optimal technique. The identified method achieved an accuracy of 99.65% and 99.13% for surface area and volume, respectively, with an interclass coefficient of 0.81. The method presented is simple, requiring less than ten minutes to capture using twenty-six photos. However, image processing time can take hours, depending on the software used. This method falls within clinical limits for accuracy, requires minimal training, and is non-destructive; thus, it can be integrated into existing workflows. This technique could bridge the gap between digital and physical workflows, helping to revolutionise the prosthetics fitting process and supporting the inclusion of additive manufactured sockets. | en_US |
dc.description.sponsorship | EPSRC through a studentship for Sean Cullen (EP/R512990/1) | en_US |
dc.format.extent | 1382 - 1392 | - |
dc.language | en | - |
dc.publisher | MDPI AG | en_US |
dc.rights | Copyright © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). | - |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0 | - |
dc.subject | prosthetics | en_US |
dc.subject | sockets | en_US |
dc.subject | scanning | en_US |
dc.subject | photogrammetry | en_US |
dc.subject | low cost | en_US |
dc.subject | digital twin | en_US |
dc.subject | genetic algorithms | en_US |
dc.title | Low-Cost Smartphone Photogrammetry Accurately Digitises Positive Socket and Limb Casts | en_US |
dc.type | Article | en_US |
dc.identifier.doi | https://doi.org/10.3390/prosthesis5040095 | - |
dc.relation.isPartOf | Prosthesis | - |
pubs.issue | 4 | - |
pubs.publication-status | Published online | - |
pubs.volume | 5 | - |
dc.identifier.eissn | 2673-1592 | - |
dc.rights.license | https://creativecommons.org/licenses/by/4.0/legalcode.en | - |
dc.rights.holder | The authors | - |
Appears in Collections: | Dept of Life Sciences Research Papers |
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FullText.pdf | Copyright © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). | 2.26 MB | Adobe PDF | View/Open |
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