Evidence map›Paper›PMID 31741116›Full record

ArticleBiomechanics and modeling in mechanobiology2020

Predictive prosthetic socket design: part 2-generating person-specific candidate designs using multi-objective genetic algorithms.

J W Steer, P A Grudniewski, M Browne, P R Worsley, A J Sobey, A S Dickinson

Open access · hybridAbstract read
In one paragraph

Article in Biomechanics and modeling in mechanobiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
2.1field-weighted citation impact, top 13% 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, 1 synthesis or guideline pooled it, 48 citations in OpenAlex.

  1. Pooled it
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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

6 authors at 1 institution in 1 country.

J W SteerFaculty of Engineering and Physical Sciences, University of Southampton, Southampton, UK.ORCID http://orcid.org/0000-0002-6288-1347
P A GrudniewskiFaculty of Engineering and Physical Sciences, University of Southampton, Southampton, UK.ORCID http://orcid.org/0000-0003-0635-3125
M BrowneFaculty of Engineering and Physical Sciences, University of Southampton, Southampton, UK.ORCID http://orcid.org/0000-0001-5184-050X
P R WorsleyFaculty of Environmental and Life Sciences, University of Southampton, Southampton, UK.ORCID http://orcid.org/0000-0003-0145-5042
A J SobeyFaculty of Engineering and Physical Sciences, University of Southampton, Southampton, UK.ORCID http://orcid.org/0000-0001-6880-8338
A S DickinsonFaculty of Engineering and Physical Sciences, University of Southampton, Southampton, UK. alex.dickinson@soton.ac.uk.ORCID http://orcid.org/0000-0002-9647-1944
University of Southampton · GB

Funding

EPSRC EP/M000303/1EPSRC EP/M508147/1Royal Academy of Engineering RF/130
6 · The paper itself

Abstract

In post-amputation rehabilitation, a common goal is to return to ambulation using a prosthetic limb, suspended by a customised socket. Prosthetic socket design aims to optimise load transfer between the residual limb and mechanical limb, by customisation to the user. This is a time-consuming process, and with the increase in people requiring these prosthetics, it is vital that these personalised devices can be produced rapidly while maintaining excellent fit, to maximise function and comfort. Prosthetic sockets are designed by capturing the residual limb's shape and applying a series of geometrical modifications, called rectifications. Expert knowledge is required to achieve a comfortable fit in this iterative process. A variety of rectifications can be made, grouped into established strategies [e.g. in transtibial sockets: patellar tendon bearing (PTB) and total surface bearing (TSB)], creating a complex design space. To date, adoption of advanced engineering solutions to support fitting has been limited. One method is numerical optimisation, which allows the designer a number of likely candidate solutions to start the design process. Numerical optimisation is commonly used in many industries but not prevalent in the design of prosthetic sockets. This paper therefore presents candidate shape optimisation methods which might benefit the prosthetist and the limb user, by blending the state of the art from prosthetic mechanical design, surrogate modelling and evolutionary computation. The result of the analysis is a series of prosthetic socket designs that preferentially load and unload the pressure tolerant and intolerant regions of the residual limb. This spectrum is bounded by the general forms of the PTB and TSB designs, with a series of variations in between that represent a compromise between these accepted approaches. This results in a difference in pressure of up to 31 kPa over the fibula head and 14 kPa over the residuum tip. The presented methods would allow a trained prosthetist to rapidly assess these likely candidates and then to make final detailed modifications and fine-tuning. Importantly, insights gained about the design should be seen as a compliment, not a replacement, for the prosthetist's skill and experience. We propose instead that this method might reduce the time spent on the early stages of socket design and allow prosthetists to focus on the most skilled and creative tasks of fine-tuning the design, in face-to-face consultation with their client.

Indexed as

AlgorithmsProsthesis DesignArtificial LimbsAutomationHumansPressureAmputationFEAOptimisationResidual limb

Identifiers

PMID31741116
PMCPMC7423857
OpenAlexW2983582968

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.