Inverse kinematics for upper limb compound movement estimation in exoskeleton-assisted rehabilitation

Robot-Assisted Rehabilitation (RAR) is relevant for treating patients affected by nervous system injuries (e.g., stroke and spinal cord injury) -- The accurate estimation of the joint angles of the patient limbs in RAR is critical to assess the patient improvement -- The economical prevalent method...

Full description

Autores:
Cortés, Camilo
De los Reyes-Guzmán, Ana
Scorza, Davide
Bertelsen, Álvaro
Carrasco, Eduardo
Gil-Agudo, Ángel
Ruíz-Salguero, Óscar
Flórez, Julián
Tipo de recurso:
Fecha de publicación:
2016
Institución:
Universidad EAFIT
Repositorio:
Repositorio EAFIT
Idioma:
eng
OAI Identifier:
oai:repository.eafit.edu.co:10784/9529
Acceso en línea:
http://hdl.handle.net/10784/9529
Palabra clave:
ROBÓTICA
REHABILITACIÓN MÉDICA
BIOMECÁNICA
EXTREMIDADES SUPERIORES
EXOESQUELETO
ELECTROMIOGRAFÍA
Robotics
Medical rehabilitation
Biomechanics
Extremities, upper
Exoskeleton
Electromyography
Robotics
Medical rehabilitation
Biomechanics
Extremities
upper
Exoskeleton
Electromyography
Cinemática inversa
Rights
License
Acceso abierto
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dc.title.eng.fl_str_mv Inverse kinematics for upper limb compound movement estimation in exoskeleton-assisted rehabilitation
title Inverse kinematics for upper limb compound movement estimation in exoskeleton-assisted rehabilitation
spellingShingle Inverse kinematics for upper limb compound movement estimation in exoskeleton-assisted rehabilitation
ROBÓTICA
REHABILITACIÓN MÉDICA
BIOMECÁNICA
EXTREMIDADES SUPERIORES
EXOESQUELETO
ELECTROMIOGRAFÍA
Robotics
Medical rehabilitation
Biomechanics
Extremities, upper
Exoskeleton
Electromyography
Robotics
Medical rehabilitation
Biomechanics
Extremities
upper
Exoskeleton
Electromyography
Cinemática inversa
title_short Inverse kinematics for upper limb compound movement estimation in exoskeleton-assisted rehabilitation
title_full Inverse kinematics for upper limb compound movement estimation in exoskeleton-assisted rehabilitation
title_fullStr Inverse kinematics for upper limb compound movement estimation in exoskeleton-assisted rehabilitation
title_full_unstemmed Inverse kinematics for upper limb compound movement estimation in exoskeleton-assisted rehabilitation
title_sort Inverse kinematics for upper limb compound movement estimation in exoskeleton-assisted rehabilitation
dc.creator.fl_str_mv Cortés, Camilo
De los Reyes-Guzmán, Ana
Scorza, Davide
Bertelsen, Álvaro
Carrasco, Eduardo
Gil-Agudo, Ángel
Ruíz-Salguero, Óscar
Flórez, Julián
dc.contributor.department.spa.fl_str_mv Universidad EAFIT. Departamento de Ingeniería Mecánica
dc.contributor.author.none.fl_str_mv Cortés, Camilo
De los Reyes-Guzmán, Ana
Scorza, Davide
Bertelsen, Álvaro
Carrasco, Eduardo
Gil-Agudo, Ángel
Ruíz-Salguero, Óscar
Flórez, Julián
dc.contributor.researchgroup.spa.fl_str_mv Laboratorio CAD/CAM/CAE
dc.subject.lemb.spa.fl_str_mv ROBÓTICA
REHABILITACIÓN MÉDICA
BIOMECÁNICA
EXTREMIDADES SUPERIORES
EXOESQUELETO
ELECTROMIOGRAFÍA
topic ROBÓTICA
REHABILITACIÓN MÉDICA
BIOMECÁNICA
EXTREMIDADES SUPERIORES
EXOESQUELETO
ELECTROMIOGRAFÍA
Robotics
Medical rehabilitation
Biomechanics
Extremities, upper
Exoskeleton
Electromyography
Robotics
Medical rehabilitation
Biomechanics
Extremities
upper
Exoskeleton
Electromyography
Cinemática inversa
dc.subject.keyword.spa.fl_str_mv Robotics
Medical rehabilitation
Biomechanics
Extremities, upper
Exoskeleton
Electromyography
dc.subject.keyword.eng.fl_str_mv Robotics
Medical rehabilitation
Biomechanics
Extremities
upper
Exoskeleton
Electromyography
dc.subject.keyword..keywor.fl_str_mv Cinemática inversa
description Robot-Assisted Rehabilitation (RAR) is relevant for treating patients affected by nervous system injuries (e.g., stroke and spinal cord injury) -- The accurate estimation of the joint angles of the patient limbs in RAR is critical to assess the patient improvement -- The economical prevalent method to estimate the patient posture in Exoskeleton-based RAR is to approximate the limb joint angles with the ones of the Exoskeleton -- This approximation is rough since their kinematic structures differ -- Motion capture systems (MOCAPs) can improve the estimations, at the expenses of a considerable overload of the therapy setup -- Alternatively, the Extended Inverse Kinematics Posture Estimation (EIKPE) computational method models the limb and Exoskeleton as differing parallel kinematic chains -- EIKPE has been tested with single DOFmovements of the wrist and elbow joints -- This paper presents the assessment of EIKPEwith elbow-shoulder compoundmovements (i.e., object prehension) -- Ground-truth for estimation assessment is obtained from an optical MOCAP (not intended for the treatment stage) -- The assessment shows EIKPE rendering a good numerical approximation of the actual posture during the compoundmovement execution, especially for the shoulder joint angles -- This work opens the horizon for clinical studies with patient groups, Exoskeleton models, and movements types --
publishDate 2016
dc.date.available.none.fl_str_mv 2016-10-21T01:35:33Z
dc.date.issued.none.fl_str_mv 2016-05-16
dc.date.accessioned.none.fl_str_mv 2016-10-21T01:35:33Z
dc.type.eng.fl_str_mv info:eu-repo/semantics/article
article
info:eu-repo/semantics/publishedVersion
publishedVersion
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dc.type.local.spa.fl_str_mv Artículo
status_str publishedVersion
dc.identifier.issn.none.fl_str_mv 2314-6141
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/10784/9529
dc.identifier.doi.none.fl_str_mv 10.1155/2016/2581924
identifier_str_mv 2314-6141
10.1155/2016/2581924
url http://hdl.handle.net/10784/9529
dc.language.iso.eng.fl_str_mv eng
language eng
dc.relation.ispartof.spa.fl_str_mv BioMed Research International, Volume 2016, pp 1-14
dc.relation.uri.none.fl_str_mv https://www.hindawi.com/journals/bmri/2016/2581924/
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dc.rights.local.spa.fl_str_mv Acceso abierto
rights_invalid_str_mv Acceso abierto
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dc.format.eng.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Hindawi Publishing Corp.
institution Universidad EAFIT
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spelling 2016-10-21T01:35:33Z2016-05-162016-10-21T01:35:33Z2314-6141http://hdl.handle.net/10784/952910.1155/2016/2581924Robot-Assisted Rehabilitation (RAR) is relevant for treating patients affected by nervous system injuries (e.g., stroke and spinal cord injury) -- The accurate estimation of the joint angles of the patient limbs in RAR is critical to assess the patient improvement -- The economical prevalent method to estimate the patient posture in Exoskeleton-based RAR is to approximate the limb joint angles with the ones of the Exoskeleton -- This approximation is rough since their kinematic structures differ -- Motion capture systems (MOCAPs) can improve the estimations, at the expenses of a considerable overload of the therapy setup -- Alternatively, the Extended Inverse Kinematics Posture Estimation (EIKPE) computational method models the limb and Exoskeleton as differing parallel kinematic chains -- EIKPE has been tested with single DOFmovements of the wrist and elbow joints -- This paper presents the assessment of EIKPEwith elbow-shoulder compoundmovements (i.e., object prehension) -- Ground-truth for estimation assessment is obtained from an optical MOCAP (not intended for the treatment stage) -- The assessment shows EIKPE rendering a good numerical approximation of the actual posture during the compoundmovement execution, especially for the shoulder joint angles -- This work opens the horizon for clinical studies with patient groups, Exoskeleton models, and movements types --application/pdfengHindawi Publishing Corp.BioMed Research International, Volume 2016, pp 1-14https://www.hindawi.com/journals/bmri/2016/2581924/Acceso abiertohttp://purl.org/coar/access_right/c_abf2Inverse kinematics for upper limb compound movement estimation in exoskeleton-assisted rehabilitationinfo:eu-repo/semantics/articlearticleinfo:eu-repo/semantics/publishedVersionpublishedVersionArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1ROBÓTICAREHABILITACIÓN MÉDICABIOMECÁNICAEXTREMIDADES SUPERIORESEXOESQUELETOELECTROMIOGRAFÍARoboticsMedical rehabilitationBiomechanicsExtremities, upperExoskeletonElectromyographyRoboticsMedical rehabilitationBiomechanicsExtremitiesupperExoskeletonElectromyographyCinemática inversaUniversidad EAFIT. Departamento de Ingeniería MecánicaCortés, CamiloDe los Reyes-Guzmán, AnaScorza, DavideBertelsen, ÁlvaroCarrasco, EduardoGil-Agudo, ÁngelRuíz-Salguero, ÓscarFlórez, JuliánLaboratorio CAD/CAM/CAEBioMed Research InternationalBioMed Research International2016114LICENSElicense.txtlicense.txttext/plain; charset=utf-82556https://repository.eafit.edu.co/bitstreams/4b1ad8cf-04b7-4233-b0ae-0a1c65733e3b/download76025f86b095439b7ac65b367055d40cMD51ORIGINALInverse_Kinematics.pdfInverse_Kinematics.pdfapplication/pdf4202334https://repository.eafit.edu.co/bitstreams/e7df578a-0fdf-422d-a7c9-14368b0019b3/downloadc5589d0972d48119a9a26ab6461996daMD522581924.pdf2581924.pdfapplication/pdf4202334https://repository.eafit.edu.co/bitstreams/a12ec9a3-18e1-47a0-9a58-28f74d93ca8c/downloadc5589d0972d48119a9a26ab6461996daMD5310784/9529oai:repository.eafit.edu.co:10784/95292022-11-08 11:18:56.328open.accesshttps://repository.eafit.edu.coRepositorio Institucional Universidad EAFITrepositorio@eafit.edu.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