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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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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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 |
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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 |
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