Global and local identifiability analysis of a nonlinear biphasic constitutive model in confined compression

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Author(s)Peloquin, John M.
Author(s)Elliott, Dawn M.
Date Accessioned2024-11-26T20:58:34Z
Date Available2024-11-26T20:58:34Z
Publication Date2024-11-13
DescriptionThis article was originally published in Journal of the Royal Society Interface. The version of record is available at: https://doi.org/10.1098/rsif.2024.0415. © 2024 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
AbstractApplication of biomechanical models relies on model parameters estimated from experimental data. Parameter non-identifiability, when the same model output can be produced by many sets of parameter values, introduces severe errors yet has received relatively little attention in biomechanics and is subtle enough to remain unnoticed in the absence of deliberate verification. The present work develops a global identifiability analysis method in which cluster analysis and singular value decomposition are applied to vectors of parameter–output variable correlation coefficients. This method provides a visual representation of which specific experimental design elements are beneficial or harmful in terms of parameter identifiability, supporting the correction of deficiencies in the test protocol prior to testing physical specimens. The method was applied to a representative nonlinear biphasic model for cartilaginous tissue, demonstrating that confined compression data does not provide identifiability for the biphasic model parameters. This result was confirmed by two independent analyses: local analysis of the Hessian of a sum-of-squares error cost function and observation of the behaviour of two optimization algorithms. Therefore, confined compression data are insufficient for the calibration of general-purpose biphasic models. Identifiability analysis by these or other methods is strongly recommended when planning future experiments.
SponsorResearch reported in this publication was supported by (a) NIAMS of the National Institutes of Health award nos. R01 AR050052 and R01 AR054620 and (b) NIGMS of the National Institutes of Health award no. P20 GM139760.
CitationPeloquin John M. and Elliott Dawn M. 2024 Global and local identifiability analysis of a nonlinear biphasic constitutive model in confined compression. J. R. Soc. Interface. 2120240415. http://doi.org/10.1098/rsif.2024.0415
ISSN1742-5662
URLhttps://udspace.udel.edu/handle/19716/35626
Languageen_US
PublisherJournal of the Royal Society Interface
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
Keywordsidentifiability analysis
Keywordsparameter estimation
Keywordssoft tissue mechanics
Keywordscartilage
Keywordsconfined compression
TitleGlobal and local identifiability analysis of a nonlinear biphasic constitutive model in confined compression
TypeArticle
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