Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modeling

[Background] Research efforts in neurorehabilitation technologies have been directed towards creating robotic exoskeletons to restore motor function in impaired individuals. However, despite advances in mechatronics and bioelectrical signal processing, current robotic exoskeletons have had only mode...

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Autores: Durandau, Guillaume, Farina, Dario, Asín-Prieto, Guillermo, Dimbwadyo-Terrer, Iris, Lerma-Lara, Sergio, Pons Rovira, José Luis, Moreno, Juan Camilo, Sartori, Massimo
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2019
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/186445
Acceso en línea:http://hdl.handle.net/10261/186445
Access Level:acceso abierto
Palabra clave:Electromyography
EMG-driven modeling
Neuromechanical modeling
Neuromuscular injury
Robotic exoskeleton
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spelling Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modelingDurandau, GuillaumeFarina, DarioAsín-Prieto, GuillermoDimbwadyo-Terrer, IrisLerma-Lara, SergioPons Rovira, José LuisMoreno, Juan CamiloSartori, MassimoElectromyographyEMG-driven modelingNeuromechanical modelingNeuromuscular injuryRobotic exoskeleton[Background] Research efforts in neurorehabilitation technologies have been directed towards creating robotic exoskeletons to restore motor function in impaired individuals. However, despite advances in mechatronics and bioelectrical signal processing, current robotic exoskeletons have had only modest clinical impact. A major limitation is the inability to enable exoskeleton voluntary control in neurologically impaired individuals. This hinders the possibility of optimally inducing the activity-driven neuroplastic changes that are required for recovery.[Methods] We have developed a patient-specific computational model of the human musculoskeletal system controlled via neural surrogates, i.e., electromyography-derived neural activations to muscles. The electromyography-driven musculoskeletal model was synthesized into a human-machine interface (HMI) that enabled poststroke and incomplete spinal cord injury patients to voluntarily control multiple joints in a multifunctional robotic exoskeleton in real time.[Results] We demonstrated patients’ control accuracy across a wide range of lower-extremity motor tasks. Remarkably, an increased level of exoskeleton assistance always resulted in a reduction in both amplitude and variability in muscle activations as well as in the mechanical moments required to perform a motor task. Since small discrepancies in onset time between human limb movement and that of the parallel exoskeleton would potentially increase human neuromuscular effort, these results demonstrate that the developed HMI precisely synchronizes the device actuation with residual voluntary muscle contraction capacity in neurologically impaired patients.[Conclusions] Continuous voluntary control of robotic exoskeletons (i.e. event-free and task-independent) has never been demonstrated before in populations with paretic and spastic-like muscle activity, such as those investigated in this study. Our proposed methodology may open new avenues for harnessing residual neuromuscular function in neurologically impaired individuals via symbiotic wearable robots.The study was partly supported by ERC Starting Grant INTERACT (803035) and the FP7 BIOMOT Project (611695).Peer reviewedBioMed CentralEuropean Research CouncilEuropean CommissionConsejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]2019201920192019info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10261/186445reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/EC/H2020/803035info:eu-repo/grantAgreement/EC/FP7/611695https://doi.org/10.1186/s12984-019-0559-zSíinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/1864452026-05-22T06:33:51Z
dc.title.none.fl_str_mv Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modeling
title Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modeling
spellingShingle Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modeling
Durandau, Guillaume
Electromyography
EMG-driven modeling
Neuromechanical modeling
Neuromuscular injury
Robotic exoskeleton
title_short Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modeling
title_full Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modeling
title_fullStr Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modeling
title_full_unstemmed Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modeling
title_sort Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modeling
dc.creator.none.fl_str_mv Durandau, Guillaume
Farina, Dario
Asín-Prieto, Guillermo
Dimbwadyo-Terrer, Iris
Lerma-Lara, Sergio
Pons Rovira, José Luis
Moreno, Juan Camilo
Sartori, Massimo
author Durandau, Guillaume
author_facet Durandau, Guillaume
Farina, Dario
Asín-Prieto, Guillermo
Dimbwadyo-Terrer, Iris
Lerma-Lara, Sergio
Pons Rovira, José Luis
Moreno, Juan Camilo
Sartori, Massimo
author_role author
author2 Farina, Dario
Asín-Prieto, Guillermo
Dimbwadyo-Terrer, Iris
Lerma-Lara, Sergio
Pons Rovira, José Luis
Moreno, Juan Camilo
Sartori, Massimo
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv European Research Council
European Commission
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Electromyography
EMG-driven modeling
Neuromechanical modeling
Neuromuscular injury
Robotic exoskeleton
topic Electromyography
EMG-driven modeling
Neuromechanical modeling
Neuromuscular injury
Robotic exoskeleton
description [Background] Research efforts in neurorehabilitation technologies have been directed towards creating robotic exoskeletons to restore motor function in impaired individuals. However, despite advances in mechatronics and bioelectrical signal processing, current robotic exoskeletons have had only modest clinical impact. A major limitation is the inability to enable exoskeleton voluntary control in neurologically impaired individuals. This hinders the possibility of optimally inducing the activity-driven neuroplastic changes that are required for recovery.
publishDate 2019
dc.date.none.fl_str_mv 2019
2019
2019
2019
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/186445
url http://hdl.handle.net/10261/186445
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
#PLACEHOLDER_PARENT_METADATA_VALUE#
info:eu-repo/grantAgreement/EC/H2020/803035
info:eu-repo/grantAgreement/EC/FP7/611695
https://doi.org/10.1186/s12984-019-0559-z
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv BioMed Central
publisher.none.fl_str_mv BioMed Central
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,808905

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