Vertical force calibration of smart force platform using artificial neural networks

Detalhes bibliográficos
Autor(a) principal: Toso,Marcelo André
Data de Publicação: 2014
Outros Autores: Gomes,Herbert Martins
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista Brasileira de Engenharia Biomédica (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1517-31512014000400011
Resumo: INTRODUCTION: The human body may interact with the structures and these interactions are developed through the application of contact forces, for instance due to walking movement. A structure may undergo changes in the dynamic behaviour when subjected to loads and human bodies. The aim of this paper is to propose a methodology using Artificial Neural Networks (ANN) to calibrate a force platform in order to reduce uncertainties in the vertical Ground Reaction Force measurements and positioning of the applied force for the human gait. METHODS: Force platforms have been used to evaluate the pattern of applied human forces and to fit models for the interaction between pedestrians and structures. The designed force platform consists in two force plates placed side by side in the direction of walking. The reference voltages applied to the Wheatstone bridge were used for calibration as the input data to the ANN, while the output data were the estimated values of the standard weights applied to the force platform. RESULTS: It was presented a framework to enhance traditional calibration methods for force platforms (vertical component) using an ANN. The use of ANN shows significant improvements for the measured variables, leading to better results with lower uncertain values that are smaller than those using a simple traditional calibration. CONCLUSION: The results suggest that the calibration with the ANN method may be useful in obtaining more accurate vertical Ground Reaction Forces and positioning measurements in a force platform for human gait analysis.
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spelling Vertical force calibration of smart force platform using artificial neural networksBiomechanicsForce platformArtificial neural networksCalibrationINTRODUCTION: The human body may interact with the structures and these interactions are developed through the application of contact forces, for instance due to walking movement. A structure may undergo changes in the dynamic behaviour when subjected to loads and human bodies. The aim of this paper is to propose a methodology using Artificial Neural Networks (ANN) to calibrate a force platform in order to reduce uncertainties in the vertical Ground Reaction Force measurements and positioning of the applied force for the human gait. METHODS: Force platforms have been used to evaluate the pattern of applied human forces and to fit models for the interaction between pedestrians and structures. The designed force platform consists in two force plates placed side by side in the direction of walking. The reference voltages applied to the Wheatstone bridge were used for calibration as the input data to the ANN, while the output data were the estimated values of the standard weights applied to the force platform. RESULTS: It was presented a framework to enhance traditional calibration methods for force platforms (vertical component) using an ANN. The use of ANN shows significant improvements for the measured variables, leading to better results with lower uncertain values that are smaller than those using a simple traditional calibration. CONCLUSION: The results suggest that the calibration with the ANN method may be useful in obtaining more accurate vertical Ground Reaction Forces and positioning measurements in a force platform for human gait analysis.SBEB - Sociedade Brasileira de Engenharia Biomédica2014-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1517-31512014000400011Revista Brasileira de Engenharia Biomédica v.30 n.4 2014reponame:Revista Brasileira de Engenharia Biomédica (Online)instname:Sociedade Brasileira de Engenharia Biomédica (SBEB)instacron:SBEB10.1590/1517-3151.0569info:eu-repo/semantics/openAccessToso,Marcelo AndréGomes,Herbert Martinseng2015-01-15T00:00:00Zoai:scielo:S1517-31512014000400011Revistahttp://www.scielo.br/rbebONGhttps://old.scielo.br/oai/scielo-oai.php||rbeb@rbeb.org.br1984-77421517-3151opendoar:2015-01-15T00:00Revista Brasileira de Engenharia Biomédica (Online) - Sociedade Brasileira de Engenharia Biomédica (SBEB)false
dc.title.none.fl_str_mv Vertical force calibration of smart force platform using artificial neural networks
title Vertical force calibration of smart force platform using artificial neural networks
spellingShingle Vertical force calibration of smart force platform using artificial neural networks
Toso,Marcelo André
Biomechanics
Force platform
Artificial neural networks
Calibration
title_short Vertical force calibration of smart force platform using artificial neural networks
title_full Vertical force calibration of smart force platform using artificial neural networks
title_fullStr Vertical force calibration of smart force platform using artificial neural networks
title_full_unstemmed Vertical force calibration of smart force platform using artificial neural networks
title_sort Vertical force calibration of smart force platform using artificial neural networks
author Toso,Marcelo André
author_facet Toso,Marcelo André
Gomes,Herbert Martins
author_role author
author2 Gomes,Herbert Martins
author2_role author
dc.contributor.author.fl_str_mv Toso,Marcelo André
Gomes,Herbert Martins
dc.subject.por.fl_str_mv Biomechanics
Force platform
Artificial neural networks
Calibration
topic Biomechanics
Force platform
Artificial neural networks
Calibration
description INTRODUCTION: The human body may interact with the structures and these interactions are developed through the application of contact forces, for instance due to walking movement. A structure may undergo changes in the dynamic behaviour when subjected to loads and human bodies. The aim of this paper is to propose a methodology using Artificial Neural Networks (ANN) to calibrate a force platform in order to reduce uncertainties in the vertical Ground Reaction Force measurements and positioning of the applied force for the human gait. METHODS: Force platforms have been used to evaluate the pattern of applied human forces and to fit models for the interaction between pedestrians and structures. The designed force platform consists in two force plates placed side by side in the direction of walking. The reference voltages applied to the Wheatstone bridge were used for calibration as the input data to the ANN, while the output data were the estimated values of the standard weights applied to the force platform. RESULTS: It was presented a framework to enhance traditional calibration methods for force platforms (vertical component) using an ANN. The use of ANN shows significant improvements for the measured variables, leading to better results with lower uncertain values that are smaller than those using a simple traditional calibration. CONCLUSION: The results suggest that the calibration with the ANN method may be useful in obtaining more accurate vertical Ground Reaction Forces and positioning measurements in a force platform for human gait analysis.
publishDate 2014
dc.date.none.fl_str_mv 2014-12-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1517-31512014000400011
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1517-3151.0569
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv SBEB - Sociedade Brasileira de Engenharia Biomédica
publisher.none.fl_str_mv SBEB - Sociedade Brasileira de Engenharia Biomédica
dc.source.none.fl_str_mv Revista Brasileira de Engenharia Biomédica v.30 n.4 2014
reponame:Revista Brasileira de Engenharia Biomédica (Online)
instname:Sociedade Brasileira de Engenharia Biomédica (SBEB)
instacron:SBEB
instname_str Sociedade Brasileira de Engenharia Biomédica (SBEB)
instacron_str SBEB
institution SBEB
reponame_str Revista Brasileira de Engenharia Biomédica (Online)
collection Revista Brasileira de Engenharia Biomédica (Online)
repository.name.fl_str_mv Revista Brasileira de Engenharia Biomédica (Online) - Sociedade Brasileira de Engenharia Biomédica (SBEB)
repository.mail.fl_str_mv ||rbeb@rbeb.org.br
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