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...
- 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 |
dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 http://purl.org/coar/resource_type/c_2df8fbb1 |
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/ |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.rights.local.spa.fl_str_mv |
Acceso abierto |
rights_invalid_str_mv |
Acceso abierto http://purl.org/coar/access_right/c_abf2 |
dc.format.eng.fl_str_mv |
application/pdf |
dc.publisher.spa.fl_str_mv |
Hindawi Publishing Corp. |
institution |
Universidad EAFIT |
bitstream.url.fl_str_mv |
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bitstream.checksumAlgorithm.fl_str_mv |
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repository.name.fl_str_mv |
Repositorio Institucional Universidad EAFIT |
repository.mail.fl_str_mv |
repositorio@eafit.edu.co |
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1814110373079416832 |
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.coSS4gT0JSQVMgWUEgUFVCTElDQURBUwoKUGFyYSBvYnJhcyB5YSBwdWJsaWNhZGFzIHNlIHJlcXVpZXJlLCBwYXJhIGVsIGFyY2hpdm8geSBkaXZ1bGdhY2nDs24gZW4gZWwgUmVwb3NpdG9yaW8gSW5zdGl0dWNpb25hbCBkZSBsYSBVbml2ZXJzaWRhZCBFQUZJVCwgcXVlIGVsIGF1dG9yIGNvbm96Y2EgeSB2YWxpZGUgbGFzIGNvbmRpY2lvbmVzIGVuIHF1ZSBoYSBzdXNjcml0byBsb3MgYWN1ZXJkb3MgZGUgY2VzacOzbiBvIGxpY2VuY2lhIGRlIGRlcmVjaG9zIGRlIGF1dG9yIGNvbiBsYShzKSBlZGl0b3JpYWwoZXMpIGVuIGxhcyBxdWUgaGEgcHVibGljYWRvIGxhIG9icmEuCgpFc3RhIHZlcmlmaWNhY2nDs24gc2UgcHVlZGUgcmVhbGl6YXIgY29uc3VsdGFuZG8gbGFzIGJhc2VzIGRlIGRhdG9zIFNIRVJQQSAvIFJPTUVPIHkgRFVMQ0lORUEsIHBhcmEgY29ub2NlciBsYSBwb2zDrXRpY2Egc29icmUgZGVyZWNob3MgZGUgYXV0b3IgZGUgbGEgcmVzcGVjdGl2YSBlZGl0b3JpYWwuIEVuIGNhc28gZGUgcXVlIGxhIGVkaXRvcmlhbCBubyBzZSBlbmN1ZW50cmUgZW4gZXN0YXMgYmFzZXMgZGUgZGF0b3MsIGVsIGF1dG9yIGRlYmUgY29uc3VsdGFyIGRpcmVjdGFtZW50ZSBjb24gZWwgcmVzcG9uc2FibGUgZGUgbGEgZmlybWEgZGUgbGEgbGljZW5jaWEgcG9yIHBhcnRlIGRlIGxhIGVkaXRvcmlhbC4KCkNvbnN1bHRhciBQb2zDrXRpY2EgZGVsIFJlcG9zaXRvcmlvIEluc3RpdHVjaW9uYWwuCgpJSS4gT0JSQVMgSU7DiURJVEFTCgpFbCBhdXRvciBjb25zZXJ2YSB0b2RvcyBsb3MgZGVyZWNob3MsIGNvbiBsbyBjdWFsIHB1ZWRlIHB1YmxpY2FybGEgcG9zdGVyaW9ybWVudGUuIFNlIHJlY29taWVuZGEgY29ub2Nlci9yZXZpc2FyIGxhIHBvbMOtdGljYSBkZSBkb25kZSBzZSBwcmV2w6kgcHVibGljYXIsIGRhZG8gcXVlIGFsZ3Vub3MgcHVibGljYWRvcmVzIHPDs2xvIGFjZXB0YW4gdHJhYmFqb3Mgbm8gZGlmdW5kaWRvcyBjb24gYW50ZXJpb3JpZGFkLiBQdWVkZSBjb25zdWx0YXIgbGEgYmFzZSBkZSBkYXRvcyBTSEVSUEEvUk9NRU8qIG8gRFVMQ0lORUEqKiwgcGFyYSBjb25vY2VyIGxhIHBvbMOtdGljYSBzb2JyZSBkZXJlY2hvcyBkZSBhdXRvciBkZSBsYSByZXNwZWN0aXZhIGVkaXRvcmlhbC4KCkFVVE9SSVpBQ0nDk04gREUgUFVCTElDQUNJw5NOIEVOIEZPUk1BIEFOQUzDk0dJQ0EgTyBESUdJVEFMIERFIExBIE9CUkEuCgpBdXRvcml6byBlbiBmb3JtYSBncmF0dWl0YSB5IHBvciB0aWVtcG8gaW5kZWZpbmlkbyBhIGxhIFVuaXZlcnNpZGFkIEVBRklUIHBhcmEgcmVhbGl6YXIgbGFzIHNpZ3VpZW50ZXMgYWN0aXZpZGFkZXM6CgotIFB1YmxpY2FyIGVuIGZvcm1hIGVsZWN0csOzbmljYSBvIGRpdnVsZ2FyIHBvciBtZWRpbyBlbGVjdHLDs25pY28gZWwgdGV4dG8gZGVsIHRyYWJham8gY29uIGVsIGZpbiBkZSBzZXIgY29uc3VsdGFkbyBwb3IgZWwgcMO6YmxpY28gZW4gaHR0cDovL3d3dy5lYWZpdC5lZHUuY28vYmlibGlvdGVjYQotIFB1YmxpY2FyIGVuIGZvcm1hIGVsZWN0csOzbmljYSwgZGl2dWxnYXIgcG9yIG1lZGlvIGVsZWN0csOzbmljbyB5IHByZXNlcnZhciBlbCB0ZXh0byBkZWwgdHJhYmFqbyBjb24gZWwgZmluIGRlIHNlciBjb25zdWx0YWRvIHBvciBlbCBww7pibGljbyBlbiBodHRwOi8vcmVwb3NpdG9yeS5lYWZpdC5lZHUuY28KClRvZG8gcGVyc29uYSBxdWUgY29uc3VsdGUgZWwgbWF0ZXJpYWwgYmllbiBzZWEgZGUgZm9ybWEgYW5hbMOzZ2ljYSBvIGRpZ2l0YWwsIHBvZHLDoSByZWFsaXphciBjaXRhcyBjb25mb3JtZSBhIGxvIHBlcm1pdGlkbyBwb3IgbGEgbGV5IGNpdGFuZG8gZW4gdG9kbyBjYXNvIGxhcyBmdWVudGVzLiBFc3RhIGF1dG9yaXphY2nDs24gbm8gaW1wbGljYSByZW51bmNpYSBhIGxhIGZhY3VsdGFkIHF1ZSB0ZW5nbyBkZSBwdWJsaWNhciB0b3RhbCBvIHBhcmNpYWxtZW50ZSBsYSBvYnJhLgoKRGVjbGFybyBxdWUgc295IGVsIGF1dG9yIHkgdGl0dWxhciBkZSBsb3MgZGVyZWNob3MgZGUgYXV0b3Igc29icmUgbGEgb2JyYSwgeSBxdWUgbGEgbWlzbWEgZXMgb3JpZ2luYWwsIHBvciBsbyB0YW50byBsYSBVbml2ZXJzaWRhZCBFQUZJVCBubyBzZXLDoSByZXNwb25zYWJsZSBkZSBuaW5ndW5hIHJlY2xhbWFjacOzbiBxdWUgcHVkaWVyYSBzdXJnaXIgcG9yIHBhcnRlIGRlIHRlcmNlcm9zIHF1ZSBpbnZvcXVlbiBhdXRvcsOtYSBkZSBsYSBvYnJhIHF1ZSBwcmVzZW50by4KClNpIHRpZW5lIGFsZ3VuYSBkdWRhIHNvYnJlIGxhIGxpY2VuY2lhLCBwb3IgZmF2b3IsIGNvbnRhY3RlIGNvbiBlbCBhZG1pbmlzdHJhZG9yIGRlbCBzaXN0ZW1hLgoKRGVjbGFybyBxdWUgY29ub3pjbyBsYSBwb2zDrXRpY2EgZGVsIFJlcG9zaXRvcmlvIEluc3RpdHVjaW9uYWwgeSBjb25jZWRvIGxhIGF1dG9yaXphY2nDs24uCgpfX19fX19fX19fX19fX18KKCopIFNoZXJwYS4gRGlzcG9uaWJsZSBlbjogaHR0cDovL3d3dy5zaGVycGEuYWMudWsvcm9tZW8vP2xhPWVzCigqKikgRHVsY2luZWEuIERpc3BvbmlibGUgZW46IGh0dHA6Ly93d3cuYWNjZXNvYWJpZXJ0by5uZXQvZHVsY2luZWEK |