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The influence of flow model selection on finite element model parameter estimation using Bayesian inference

Recently, Bayesian estimation coupled with finite element modeling has been demonstrated as a viable tool for estimating vocal fold material properties from kinematic information obtained via high-speed video recordings. In this article, the sensitivity of the parameter estimations to the employed f...

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Detalles Bibliográficos
Autores principales: Hadwin, Paul J., Erath, Byron D., Peterson, Sean D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Acoustical Society of America 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8182970/
https://www.ncbi.nlm.nih.gov/pubmed/34136884
http://dx.doi.org/10.1121/10.0004260
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author Hadwin, Paul J.
Erath, Byron D.
Peterson, Sean D.
author_facet Hadwin, Paul J.
Erath, Byron D.
Peterson, Sean D.
author_sort Hadwin, Paul J.
collection PubMed
description Recently, Bayesian estimation coupled with finite element modeling has been demonstrated as a viable tool for estimating vocal fold material properties from kinematic information obtained via high-speed video recordings. In this article, the sensitivity of the parameter estimations to the employed fluid model is explored by considering Bernoulli and one-dimensional viscous fluid flow models. Simulation results indicate that prescribing an ad hoc separation location for the Bernoulli flow model can lead to large estimate biases, whereas including the separation location as an estimated parameter leads to results comparable to that of the viscous fluid flow model.
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spelling pubmed-81829702021-06-14 The influence of flow model selection on finite element model parameter estimation using Bayesian inference Hadwin, Paul J. Erath, Byron D. Peterson, Sean D. JASA Express Lett Speech Communication Recently, Bayesian estimation coupled with finite element modeling has been demonstrated as a viable tool for estimating vocal fold material properties from kinematic information obtained via high-speed video recordings. In this article, the sensitivity of the parameter estimations to the employed fluid model is explored by considering Bernoulli and one-dimensional viscous fluid flow models. Simulation results indicate that prescribing an ad hoc separation location for the Bernoulli flow model can lead to large estimate biases, whereas including the separation location as an estimated parameter leads to results comparable to that of the viscous fluid flow model. Acoustical Society of America 2021-04 2021-04-15 /pmc/articles/PMC8182970/ /pubmed/34136884 http://dx.doi.org/10.1121/10.0004260 Text en © 2021 Author(s). 0001-4966/2021/1(4)/045204/8 https://creativecommons.org/licenses/by/4.0/All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Speech Communication
Hadwin, Paul J.
Erath, Byron D.
Peterson, Sean D.
The influence of flow model selection on finite element model parameter estimation using Bayesian inference
title The influence of flow model selection on finite element model parameter estimation using Bayesian inference
title_full The influence of flow model selection on finite element model parameter estimation using Bayesian inference
title_fullStr The influence of flow model selection on finite element model parameter estimation using Bayesian inference
title_full_unstemmed The influence of flow model selection on finite element model parameter estimation using Bayesian inference
title_short The influence of flow model selection on finite element model parameter estimation using Bayesian inference
title_sort influence of flow model selection on finite element model parameter estimation using bayesian inference
topic Speech Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8182970/
https://www.ncbi.nlm.nih.gov/pubmed/34136884
http://dx.doi.org/10.1121/10.0004260
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