Cargando…
Predictive Behavior of a Computational Foot/Ankle Model through Artificial Neural Networks
Computational models are useful tools to study the biomechanics of human joints. Their predictive performance is heavily dependent on bony anatomy and soft tissue properties. Imaging data provides anatomical requirements while approximate tissue properties are implemented from literature data, when...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5304311/ https://www.ncbi.nlm.nih.gov/pubmed/28250804 http://dx.doi.org/10.1155/2017/3602928 |
_version_ | 1782506863980445696 |
---|---|
author | Chande, Ruchi D. Hargraves, Rosalyn Hobson Ortiz-Robinson, Norma Wayne, Jennifer S. |
author_facet | Chande, Ruchi D. Hargraves, Rosalyn Hobson Ortiz-Robinson, Norma Wayne, Jennifer S. |
author_sort | Chande, Ruchi D. |
collection | PubMed |
description | Computational models are useful tools to study the biomechanics of human joints. Their predictive performance is heavily dependent on bony anatomy and soft tissue properties. Imaging data provides anatomical requirements while approximate tissue properties are implemented from literature data, when available. We sought to improve the predictive capability of a computational foot/ankle model by optimizing its ligament stiffness inputs using feedforward and radial basis function neural networks. While the former demonstrated better performance than the latter per mean square error, both networks provided reasonable stiffness predictions for implementation into the computational model. |
format | Online Article Text |
id | pubmed-5304311 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-53043112017-03-01 Predictive Behavior of a Computational Foot/Ankle Model through Artificial Neural Networks Chande, Ruchi D. Hargraves, Rosalyn Hobson Ortiz-Robinson, Norma Wayne, Jennifer S. Comput Math Methods Med Research Article Computational models are useful tools to study the biomechanics of human joints. Their predictive performance is heavily dependent on bony anatomy and soft tissue properties. Imaging data provides anatomical requirements while approximate tissue properties are implemented from literature data, when available. We sought to improve the predictive capability of a computational foot/ankle model by optimizing its ligament stiffness inputs using feedforward and radial basis function neural networks. While the former demonstrated better performance than the latter per mean square error, both networks provided reasonable stiffness predictions for implementation into the computational model. Hindawi Publishing Corporation 2017 2017-01-30 /pmc/articles/PMC5304311/ /pubmed/28250804 http://dx.doi.org/10.1155/2017/3602928 Text en Copyright © 2017 Ruchi D. Chande et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Chande, Ruchi D. Hargraves, Rosalyn Hobson Ortiz-Robinson, Norma Wayne, Jennifer S. Predictive Behavior of a Computational Foot/Ankle Model through Artificial Neural Networks |
title | Predictive Behavior of a Computational Foot/Ankle Model through Artificial Neural Networks |
title_full | Predictive Behavior of a Computational Foot/Ankle Model through Artificial Neural Networks |
title_fullStr | Predictive Behavior of a Computational Foot/Ankle Model through Artificial Neural Networks |
title_full_unstemmed | Predictive Behavior of a Computational Foot/Ankle Model through Artificial Neural Networks |
title_short | Predictive Behavior of a Computational Foot/Ankle Model through Artificial Neural Networks |
title_sort | predictive behavior of a computational foot/ankle model through artificial neural networks |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5304311/ https://www.ncbi.nlm.nih.gov/pubmed/28250804 http://dx.doi.org/10.1155/2017/3602928 |
work_keys_str_mv | AT chanderuchid predictivebehaviorofacomputationalfootanklemodelthroughartificialneuralnetworks AT hargravesrosalynhobson predictivebehaviorofacomputationalfootanklemodelthroughartificialneuralnetworks AT ortizrobinsonnorma predictivebehaviorofacomputationalfootanklemodelthroughartificialneuralnetworks AT waynejennifers predictivebehaviorofacomputationalfootanklemodelthroughartificialneuralnetworks |