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

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          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 was created, informed by variation in (i) population-driven residuum shape morphology, (ii) soft tissue compliance and (iii) prosthetic socket design. 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 (1.6 ms) with error vs the analytical solutions of < 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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          Exploratory designs for computational experiments

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            The elastic and ultimate properties of compact bone tissue

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              Sockets for Limb Prostheses: A Review of Existing Technologies and Open Challenges

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                Author and article information

                Contributors
                joshua.steer@soton.ac.uk
                p.r.worsley@soton.ac.uk
                doctor@soton.ac.uk
                alex.dickinson@soton.ac.uk
                Journal
                Biomech Model Mechanobiol
                Biomech Model Mechanobiol
                Biomechanics and Modeling in Mechanobiology
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                1617-7959
                1617-7940
                29 June 2019
                29 June 2019
                2020
                : 19
                : 4
                : 1331-1346
                Affiliations
                [1 ]GRID grid.5491.9, ISNI 0000 0004 1936 9297, Bioengineering Science Research Group, Faculty of Engineering and Physical Sciences, , University of Southampton, ; Southampton, UK
                [2 ]GRID grid.5491.9, ISNI 0000 0004 1936 9297, Clinical Academic Facility, Faculty of Health Sciences, , University of Southampton, ; Southampton, UK
                Author information
                http://orcid.org/0000-0002-6288-1347
                http://orcid.org/0000-0003-0145-5042
                http://orcid.org/0000-0001-5184-050X
                http://orcid.org/0000-0002-9647-1944
                Article
                1195
                10.1007/s10237-019-01195-5
                7423807
                31256276
                d06710cf-668f-485c-bf02-96c1d6628423
                © The Author(s) 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                History
                : 24 October 2018
                : 23 June 2019
                Funding
                Funded by: Royal Academy of Engineering (UK)
                Award ID: RF/130
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000266, Engineering and Physical Sciences Research Council;
                Award ID: EP/M508147/1
                Award ID: EP/N02723X/1
                Award Recipient :
                Categories
                Original Paper
                Custom metadata
                © Springer-Verlag GmbH Germany, part of Springer Nature 2020

                Biophysics
                finite element analysis,amputation,statistical shape modelling,principal component analysis

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