The University of Southampton
University of Southampton Institutional Repository
Warning ePrints Soton is experiencing an issue with some file downloads not being available. We are working hard to fix this. Please bear with us.

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

Predictive prosthetic socket design: part 2— generating person-specific candidate designs using multi-objective genetic algorithms
Predictive prosthetic socket design: part 2— generating person-specific candidate designs using multi-objective genetic algorithms
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 whilst 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.
1617-7959
1347-1360
Steer, Joshua
b958f526-9782-4e36-9c49-ad48e8f650ed
Grudniewski, Przemyslaw
31ca5517-c2c8-49dd-9536-6af3aefd8d33
Browne, Martin
6578cc37-7bd6-43b9-ae5c-77ccb7726397
Worsley, Peter
6d33aee3-ef43-468d-aef6-86d190de6756
Sobey, Adam
e850606f-aa79-4c99-8682-2cfffda3cd28
Dickinson, Alexander
10151972-c1b5-4f7d-bc12-6482b5870cad
Steer, Joshua
b958f526-9782-4e36-9c49-ad48e8f650ed
Grudniewski, Przemyslaw
31ca5517-c2c8-49dd-9536-6af3aefd8d33
Browne, Martin
6578cc37-7bd6-43b9-ae5c-77ccb7726397
Worsley, Peter
6d33aee3-ef43-468d-aef6-86d190de6756
Sobey, Adam
e850606f-aa79-4c99-8682-2cfffda3cd28
Dickinson, Alexander
10151972-c1b5-4f7d-bc12-6482b5870cad

Steer, Joshua, Grudniewski, Przemyslaw, Browne, Martin, Worsley, Peter, Sobey, Adam and Dickinson, Alexander (2019) Predictive prosthetic socket design: part 2— generating person-specific candidate designs using multi-objective genetic algorithms. Biomechanics and Modeling in Mechanobiology, 19, 1347-1360. (doi:10.1007/s10237-019-01258-7).

Record type: Article

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 whilst 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.

Text
Submission 2019 05 28 - Author's Original
Available under License Creative Commons Attribution.
Download (1MB)
Text
Accepted Manuscript 2019 11 06 - Accepted Manuscript
Available under License Creative Commons Attribution.
Download (1MB)
Text
Steer2019_Article_PredictiveProstheticSocketDesi - Version of Record
Available under License Creative Commons Attribution.
Download (4MB)

More information

Submitted date: 28 May 2019
Accepted/In Press date: 6 November 2019
e-pub ahead of print date: 18 November 2019
Published date: 18 November 2019

Identifiers

Local EPrints ID: 436043
URI: http://eprints.soton.ac.uk/id/eprint/436043
ISSN: 1617-7959
PURE UUID: 0af20629-ea30-4388-b25e-8b93b60a1f6d
ORCID for Joshua Steer: ORCID iD orcid.org/0000-0002-6288-1347
ORCID for Przemyslaw Grudniewski: ORCID iD orcid.org/0000-0003-0635-3125
ORCID for Martin Browne: ORCID iD orcid.org/0000-0001-5184-050X
ORCID for Peter Worsley: ORCID iD orcid.org/0000-0003-0145-5042
ORCID for Adam Sobey: ORCID iD orcid.org/0000-0001-6880-8338
ORCID for Alexander Dickinson: ORCID iD orcid.org/0000-0002-9647-1944

Catalogue record

Date deposited: 26 Nov 2019 17:30
Last modified: 26 Nov 2021 03:18

Export record

Altmetrics

Contributors

Author: Joshua Steer ORCID iD
Author: Przemyslaw Grudniewski ORCID iD
Author: Martin Browne ORCID iD
Author: Peter Worsley ORCID iD
Author: Adam Sobey ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×