Evidence map›Paper›PMID 34960503›Full record

ArticleSensors (Basel, Switzerland)2021

The Use of Smartphone Photogrammetry to Digitise Transtibial Sockets: Optimisation of Method and Quantitative Evaluation of Suitability.

Sean Cullen, Ruth Mackay, Amir Mohagheghi, Xinli Du

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.2field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 22 citations in OpenAlex.

  1. Immersive Neurosurgical Anatomy Using Photogrammetry: Technical Note and Scoping Review.Journal of neurological surgery. Part B, Skull base · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Sean CullenDepartment of Mechanical and Aerospace Engineering, College of Engineering Design and Physical Sciences, Brunel University, Kingston Lane, Uxbridge UB8 3PH, UK.ORCID 0000-0002-9515-9000
Ruth MackayDepartment of Mechanical and Aerospace Engineering, College of Engineering Design and Physical Sciences, Brunel University, Kingston Lane, Uxbridge UB8 3PH, UK.ORCID 0000-0002-6456-6914
Amir MohagheghiSport, Health & Exercise Sciences, College of Health, Medicine and Life Sciences, Brunel University, Kingston Lane, Uxbridge UB8 3PH, UK.ORCID 0000-0003-4295-3718
Xinli DuDepartment of Mechanical and Aerospace Engineering, College of Engineering Design and Physical Sciences, Brunel University, Kingston Lane, Uxbridge UB8 3PH, UK.ORCID 0000-0003-2604-0804
Brunel University of London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The fit of a lower limb prosthetic socket is critical for user comfort and the quality of life of lower limb amputees. Sockets are conventionally produced using hand-crafted patient-based casting techniques. Modern digital techniques offer a host of advantages to the process and ultimately lead to improving the lives of amputees. However, commercially available scanning equipment required is often expensive and proprietary. Smartphone photogrammetry could offer a low cost alternative, but there is no widely accepted imaging technique for prosthetic socket digitisation. Therefore, this paper aims to determine an optimal imaging technique for whole socket photogrammetry and evaluate the resultant scan measurement accuracy. A 3D printed transtibial socket was produced to create digital and physical twins, as reference models. The printed socket was photographed from 360 positions and simplified genetic algorithms were used to design a series of experiments, whereby a collection of photos were processed using Autodesk ReCap. The most fit technique was used to assess accuracy. The accuracy of the socket wall volume, surface area and height were 61.63%, 99.61% and 99.90%, respectively, when compared to the digital reference model. The scanned model had a wall thickness ranging from 2.075 mm at the top to 7.758 mm towards the base of the socket, compared to a consistent thickness of 2.025 mm in the control model. The technique selected did not show sufficient accuracy for clinical application due to the degradation of accuracy nearer to the base of the socket interior. However, using an internal wall thickness estimation, scans may be of sufficient accuracy for clinical use; assuming a uniform wall thickness.

Indexed as

Artificial LimbsSmartphoneHumansPhotogrammetryProsthesis DesignQuality of LifeCAD-CAMdigital twingenetic algorithmslower limb prosthesismeasurement techniquesphotogrammetryscanningsocket

Identifiers

PMID34960503
PMCPMC8703273
OpenAlexW4200239051

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.