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Foot Modeling and Smart Plantar Pressure Reconstruction from Three Sensors

In order to monitor pressure under feet, this study presents a biomechanical model of the human foot. The main elements of the foot that induce the plantar pressure distribution are described. Then the link between the forces applied at the ankle and the distribution of the plantar pressure is estab...

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Detalles Bibliográficos
Autores principales: Ghaida, Hussein Abou, Mottet, Serge, Goujon, Jean-Marc
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Bentham Open 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4231377/
https://www.ncbi.nlm.nih.gov/pubmed/25400713
http://dx.doi.org/10.2174/1874120701408010084
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author Ghaida, Hussein Abou
Mottet, Serge
Goujon, Jean-Marc
author_facet Ghaida, Hussein Abou
Mottet, Serge
Goujon, Jean-Marc
author_sort Ghaida, Hussein Abou
collection PubMed
description In order to monitor pressure under feet, this study presents a biomechanical model of the human foot. The main elements of the foot that induce the plantar pressure distribution are described. Then the link between the forces applied at the ankle and the distribution of the plantar pressure is established. Assumptions are made by defining the concepts of a 3D internal foot shape, which can be extracted from the plantar pressure measurements, and a uniform elastic medium, which describes the soft tissues behaviour. In a second part, we show that just 3 discrete pressure sensors per foot are enough to generate real time plantar pressure cartographies in the standing position or during walking. Finally, the generated cartographies are compared with pressure cartographies issued from the F-SCAN system. The results show 0.01 daN (2% of full scale) average error, in the standing position.
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spelling pubmed-42313772014-11-14 Foot Modeling and Smart Plantar Pressure Reconstruction from Three Sensors Ghaida, Hussein Abou Mottet, Serge Goujon, Jean-Marc Open Biomed Eng J Article In order to monitor pressure under feet, this study presents a biomechanical model of the human foot. The main elements of the foot that induce the plantar pressure distribution are described. Then the link between the forces applied at the ankle and the distribution of the plantar pressure is established. Assumptions are made by defining the concepts of a 3D internal foot shape, which can be extracted from the plantar pressure measurements, and a uniform elastic medium, which describes the soft tissues behaviour. In a second part, we show that just 3 discrete pressure sensors per foot are enough to generate real time plantar pressure cartographies in the standing position or during walking. Finally, the generated cartographies are compared with pressure cartographies issued from the F-SCAN system. The results show 0.01 daN (2% of full scale) average error, in the standing position. Bentham Open 2014-10-30 /pmc/articles/PMC4231377/ /pubmed/25400713 http://dx.doi.org/10.2174/1874120701408010084 Text en © Abou Ghaida et al.; Licensee Bentham Open. http://creativecommons.org/licenses/by-nc/3.0/ This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.
spellingShingle Article
Ghaida, Hussein Abou
Mottet, Serge
Goujon, Jean-Marc
Foot Modeling and Smart Plantar Pressure Reconstruction from Three Sensors
title Foot Modeling and Smart Plantar Pressure Reconstruction from Three Sensors
title_full Foot Modeling and Smart Plantar Pressure Reconstruction from Three Sensors
title_fullStr Foot Modeling and Smart Plantar Pressure Reconstruction from Three Sensors
title_full_unstemmed Foot Modeling and Smart Plantar Pressure Reconstruction from Three Sensors
title_short Foot Modeling and Smart Plantar Pressure Reconstruction from Three Sensors
title_sort foot modeling and smart plantar pressure reconstruction from three sensors
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4231377/
https://www.ncbi.nlm.nih.gov/pubmed/25400713
http://dx.doi.org/10.2174/1874120701408010084
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