Cargando…

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 modes...

Descripción completa

Detalles Bibliográficos
Autores principales: Durandau, Guillaume, Farina, Dario, Asín-Prieto, Guillermo, Dimbwadyo-Terrer, Iris, Lerma-Lara, Sergio, Pons, Jose L., Moreno, Juan C., Sartori, Massimo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6637518/
https://www.ncbi.nlm.nih.gov/pubmed/31315633
http://dx.doi.org/10.1186/s12984-019-0559-z
_version_ 1783436255961284608
author Durandau, Guillaume
Farina, Dario
Asín-Prieto, Guillermo
Dimbwadyo-Terrer, Iris
Lerma-Lara, Sergio
Pons, Jose L.
Moreno, Juan C.
Sartori, Massimo
author_facet Durandau, Guillaume
Farina, Dario
Asín-Prieto, Guillermo
Dimbwadyo-Terrer, Iris
Lerma-Lara, Sergio
Pons, Jose L.
Moreno, Juan C.
Sartori, Massimo
author_sort Durandau, Guillaume
collection PubMed
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. 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12984-019-0559-z) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-6637518
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-66375182019-07-25 Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modeling Durandau, Guillaume Farina, Dario Asín-Prieto, Guillermo Dimbwadyo-Terrer, Iris Lerma-Lara, Sergio Pons, Jose L. Moreno, Juan C. Sartori, Massimo J Neuroeng Rehabil Research 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12984-019-0559-z) contains supplementary material, which is available to authorized users. BioMed Central 2019-07-17 /pmc/articles/PMC6637518/ /pubmed/31315633 http://dx.doi.org/10.1186/s12984-019-0559-z Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Durandau, Guillaume
Farina, Dario
Asín-Prieto, Guillermo
Dimbwadyo-Terrer, Iris
Lerma-Lara, Sergio
Pons, Jose L.
Moreno, Juan C.
Sartori, Massimo
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
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_short 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
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6637518/
https://www.ncbi.nlm.nih.gov/pubmed/31315633
http://dx.doi.org/10.1186/s12984-019-0559-z
work_keys_str_mv AT durandauguillaume voluntarycontrolofwearableroboticexoskeletonsbypatientswithparesisvianeuromechanicalmodeling
AT farinadario voluntarycontrolofwearableroboticexoskeletonsbypatientswithparesisvianeuromechanicalmodeling
AT asinprietoguillermo voluntarycontrolofwearableroboticexoskeletonsbypatientswithparesisvianeuromechanicalmodeling
AT dimbwadyoterreriris voluntarycontrolofwearableroboticexoskeletonsbypatientswithparesisvianeuromechanicalmodeling
AT lermalarasergio voluntarycontrolofwearableroboticexoskeletonsbypatientswithparesisvianeuromechanicalmodeling
AT ponsjosel voluntarycontrolofwearableroboticexoskeletonsbypatientswithparesisvianeuromechanicalmodeling
AT morenojuanc voluntarycontrolofwearableroboticexoskeletonsbypatientswithparesisvianeuromechanicalmodeling
AT sartorimassimo voluntarycontrolofwearableroboticexoskeletonsbypatientswithparesisvianeuromechanicalmodeling