Prediction of three-dimensional crutch walking patterns using a torque-driven model

Computational prediction of 3D crutch-assisted walking patterns is a challenging problem that could be applied to study different biomechanical aspects of crutch walking in virtual subjects, to assist physiotherapists to choose the optimal crutch walking pattern for a specific subject, and to help i...

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Detalles Bibliográficos
Autores: Febrer Nafría, Miriam|||0000-0002-1189-835X, Pallarès López, Roger, Fregly, Benjamin Jon, Font Llagunes, Josep Maria|||0000-0002-7192-2980
Tipo de recurso: artículo
Fecha de publicación:2020
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/330203
Acceso en línea:https://hdl.handle.net/2117/330203
https://dx.doi.org/10.1007/s11044-020-09751-z
Access Level:acceso abierto
Palabra clave:Biomedical engineering
Biomechanics
Medical instruments and apparatus
Physical therapists
Crutch walking
Optimal control
Human motion prediction
Direct collocation
Enginyeria biomèdica
Biomecànica
Medicina--Aparells i instruments
Fisioterapeutes
Àrees temàtiques de la UPC::Enginyeria biomèdica
Àrees temàtiques de la UPC::Enginyeria biomèdica::Biomecànica
Àrees temàtiques de la UPC::Ciències de la salut::Fisioteràpia::Tècniques fisioterapèutiques
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network_acronym_str ES
network_name_str España
repository_id_str
spelling Prediction of three-dimensional crutch walking patterns using a torque-driven modelFebrer Nafría, Miriam|||0000-0002-1189-835XPallarès López, RogerFregly, Benjamin JonFont Llagunes, Josep Maria|||0000-0002-7192-2980Biomedical engineeringBiomechanicsMedical instruments and apparatusPhysical therapistsCrutch walkingOptimal controlHuman motion predictionDirect collocationEnginyeria biomèdicaBiomecànicaMedicina--Aparells i instrumentsFisioterapeutesÀrees temàtiques de la UPC::Enginyeria biomèdicaÀrees temàtiques de la UPC::Enginyeria biomèdica::BiomecànicaÀrees temàtiques de la UPC::Ciències de la salut::Fisioteràpia::Tècniques fisioterapèutiquesComputational prediction of 3D crutch-assisted walking patterns is a challenging problem that could be applied to study different biomechanical aspects of crutch walking in virtual subjects, to assist physiotherapists to choose the optimal crutch walking pattern for a specific subject, and to help in the design and control of exoskeletons, when crutches are needed for balance. The aim of this work is to generate a method to predict three-dimensional crutch-assisted walking motions following different patterns without tracking any experimental data. To reach this goal, we collected gait data from a healthy subject performing a four-point non-alternating crutch walking pattern, and developed a 3D torque-driven full-body model of the subject including the crutches and foot- and crutch-ground contact models. First, we developed a predictive (i.e., no tracking of experimental data) optimal control problem formulation to predict crutch walking cycles following the same pattern as the experimental data collected, using different cost functions. To reduce errors with respect to reference data, a cost function combining minimization terms of angular momentum, mechanical power, joint jerk and torque change was chosen. Then, the problem formulation was adapted to handle different foot- and crutch-ground conditions to make it capable of predicting three new crutch walking patterns, one of them at different speeds. A key aspect of our algorithm is that having ground reactions as additional controls allows one to define phases inside the cycle without the need of formulating a multiple-phase problem, thus facilitating the definition of different crutch walking patterns.20212021-01-0120202020-10-14journal articlehttp://purl.org/coar/resource_type/c_6501AMhttp://purl.org/coar/version/c_ab4af688f83e57aainfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/330203https://dx.doi.org/10.1007/s11044-020-09751-zreponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivs 3.0 Spainhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/3302032026-05-27T15:37:01Z
dc.title.none.fl_str_mv Prediction of three-dimensional crutch walking patterns using a torque-driven model
title Prediction of three-dimensional crutch walking patterns using a torque-driven model
spellingShingle Prediction of three-dimensional crutch walking patterns using a torque-driven model
Febrer Nafría, Miriam|||0000-0002-1189-835X
Biomedical engineering
Biomechanics
Medical instruments and apparatus
Physical therapists
Crutch walking
Optimal control
Human motion prediction
Direct collocation
Enginyeria biomèdica
Biomecànica
Medicina--Aparells i instruments
Fisioterapeutes
Àrees temàtiques de la UPC::Enginyeria biomèdica
Àrees temàtiques de la UPC::Enginyeria biomèdica::Biomecànica
Àrees temàtiques de la UPC::Ciències de la salut::Fisioteràpia::Tècniques fisioterapèutiques
title_short Prediction of three-dimensional crutch walking patterns using a torque-driven model
title_full Prediction of three-dimensional crutch walking patterns using a torque-driven model
title_fullStr Prediction of three-dimensional crutch walking patterns using a torque-driven model
title_full_unstemmed Prediction of three-dimensional crutch walking patterns using a torque-driven model
title_sort Prediction of three-dimensional crutch walking patterns using a torque-driven model
dc.creator.none.fl_str_mv Febrer Nafría, Miriam|||0000-0002-1189-835X
Pallarès López, Roger
Fregly, Benjamin Jon
Font Llagunes, Josep Maria|||0000-0002-7192-2980
author Febrer Nafría, Miriam|||0000-0002-1189-835X
author_facet Febrer Nafría, Miriam|||0000-0002-1189-835X
Pallarès López, Roger
Fregly, Benjamin Jon
Font Llagunes, Josep Maria|||0000-0002-7192-2980
author_role author
author2 Pallarès López, Roger
Fregly, Benjamin Jon
Font Llagunes, Josep Maria|||0000-0002-7192-2980
author2_role author
author
author
dc.subject.none.fl_str_mv Biomedical engineering
Biomechanics
Medical instruments and apparatus
Physical therapists
Crutch walking
Optimal control
Human motion prediction
Direct collocation
Enginyeria biomèdica
Biomecànica
Medicina--Aparells i instruments
Fisioterapeutes
Àrees temàtiques de la UPC::Enginyeria biomèdica
Àrees temàtiques de la UPC::Enginyeria biomèdica::Biomecànica
Àrees temàtiques de la UPC::Ciències de la salut::Fisioteràpia::Tècniques fisioterapèutiques
topic Biomedical engineering
Biomechanics
Medical instruments and apparatus
Physical therapists
Crutch walking
Optimal control
Human motion prediction
Direct collocation
Enginyeria biomèdica
Biomecànica
Medicina--Aparells i instruments
Fisioterapeutes
Àrees temàtiques de la UPC::Enginyeria biomèdica
Àrees temàtiques de la UPC::Enginyeria biomèdica::Biomecànica
Àrees temàtiques de la UPC::Ciències de la salut::Fisioteràpia::Tècniques fisioterapèutiques
description Computational prediction of 3D crutch-assisted walking patterns is a challenging problem that could be applied to study different biomechanical aspects of crutch walking in virtual subjects, to assist physiotherapists to choose the optimal crutch walking pattern for a specific subject, and to help in the design and control of exoskeletons, when crutches are needed for balance. The aim of this work is to generate a method to predict three-dimensional crutch-assisted walking motions following different patterns without tracking any experimental data. To reach this goal, we collected gait data from a healthy subject performing a four-point non-alternating crutch walking pattern, and developed a 3D torque-driven full-body model of the subject including the crutches and foot- and crutch-ground contact models. First, we developed a predictive (i.e., no tracking of experimental data) optimal control problem formulation to predict crutch walking cycles following the same pattern as the experimental data collected, using different cost functions. To reduce errors with respect to reference data, a cost function combining minimization terms of angular momentum, mechanical power, joint jerk and torque change was chosen. Then, the problem formulation was adapted to handle different foot- and crutch-ground conditions to make it capable of predicting three new crutch walking patterns, one of them at different speeds. A key aspect of our algorithm is that having ground reactions as additional controls allows one to define phases inside the cycle without the need of formulating a multiple-phase problem, thus facilitating the definition of different crutch walking patterns.
publishDate 2020
dc.date.none.fl_str_mv 2020
2020-10-14
2021
2021-01-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
AM
http://purl.org/coar/version/c_ab4af688f83e57aa
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/330203
https://dx.doi.org/10.1007/s11044-020-09751-z
url https://hdl.handle.net/2117/330203
https://dx.doi.org/10.1007/s11044-020-09751-z
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,301603

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