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Predictive prosthetic socket design: Part 1—population-based evaluation of transtibial prosthetic sockets by FEA-driven surrogate modelling

Predictive prosthetic socket design: Part 1—population-based evaluation of transtibial prosthetic sockets by FEA-driven surrogate modelling
Predictive prosthetic socket design: Part 1—population-based evaluation of transtibial prosthetic sockets by FEA-driven surrogate modelling
It has been proposed that Finite Element Analysis can complement clinical decision making for the appropriate design and manufacture of prosthetic sockets for amputees. However, clinical translation has not been achieved, in part due to lengthy solver times and the complexity involved in model development. In this study, a parametric model informed by variation in i) population-driven residuum shape morphology, ii) soft tissue compliance and iii) prosthetic socket design was created. A Kriging surrogate model was fitted to the response of the analyses across the design space enabling prediction for new residual limb morphologies and socket designs. It was predicted that morphological variability and prosthetic socket design had a substantial effect on socket-limb interfacial pressure and shear conditions as well as sub-dermal soft tissue strains. These relationships were investigated with a higher resolution of anatomical, surgical and design variability than previously reported, with a reduction in computational expense of six orders of magnitude. This enabled real-time predictions (1.6ms) with error vs the analytical solutions (<4 kPa in pressure at residuum tip, and <3% in soft tissue strain). As such, this framework represents a substantial step towards implementation of Finite Element Analysis in the prosthetics clinic.
1617-7959
1331-1346
Steer, Joshua
b958f526-9782-4e36-9c49-ad48e8f650ed
Worsley, Peter
6d33aee3-ef43-468d-aef6-86d190de6756
Browne, Martin
6578cc37-7bd6-43b9-ae5c-77ccb7726397
Dickinson, Alexander
10151972-c1b5-4f7d-bc12-6482b5870cad
Steer, Joshua
b958f526-9782-4e36-9c49-ad48e8f650ed
Worsley, Peter
6d33aee3-ef43-468d-aef6-86d190de6756
Browne, Martin
6578cc37-7bd6-43b9-ae5c-77ccb7726397
Dickinson, Alexander
10151972-c1b5-4f7d-bc12-6482b5870cad

Steer, Joshua, Worsley, Peter, Browne, Martin and Dickinson, Alexander (2019) Predictive prosthetic socket design: Part 1—population-based evaluation of transtibial prosthetic sockets by FEA-driven surrogate modelling. Biomechanics and Modeling in Mechanobiology, 19 (4), 1331-1346. (doi:10.1007/s10237-019-01195-5).

Record type: Article

Abstract

It has been proposed that Finite Element Analysis can complement clinical decision making for the appropriate design and manufacture of prosthetic sockets for amputees. However, clinical translation has not been achieved, in part due to lengthy solver times and the complexity involved in model development. In this study, a parametric model informed by variation in i) population-driven residuum shape morphology, ii) soft tissue compliance and iii) prosthetic socket design was created. A Kriging surrogate model was fitted to the response of the analyses across the design space enabling prediction for new residual limb morphologies and socket designs. It was predicted that morphological variability and prosthetic socket design had a substantial effect on socket-limb interfacial pressure and shear conditions as well as sub-dermal soft tissue strains. These relationships were investigated with a higher resolution of anatomical, surgical and design variability than previously reported, with a reduction in computational expense of six orders of magnitude. This enabled real-time predictions (1.6ms) with error vs the analytical solutions (<4 kPa in pressure at residuum tip, and <3% in soft tissue strain). As such, this framework represents a substantial step towards implementation of Finite Element Analysis in the prosthetics clinic.

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Steer 2019 BMMB TT Socket Surrogate Modelling - Version of Record
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More information

Submitted date: 15 March 2019
Accepted/In Press date: 21 June 2019
e-pub ahead of print date: 29 June 2019
Published date: August 2019

Identifiers

Local EPrints ID: 431942
URI: http://eprints.soton.ac.uk/id/eprint/431942
ISSN: 1617-7959
PURE UUID: f6178d13-f17b-4ab0-925c-4c52c9f345e1
ORCID for Joshua Steer: ORCID iD orcid.org/0000-0002-6288-1347
ORCID for Peter Worsley: ORCID iD orcid.org/0000-0003-0145-5042
ORCID for Martin Browne: ORCID iD orcid.org/0000-0001-5184-050X
ORCID for Alexander Dickinson: ORCID iD orcid.org/0000-0002-9647-1944

Catalogue record

Date deposited: 21 Jun 2019 16:30
Last modified: 26 Nov 2021 06:10

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