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Experimental Validation of Motor Primitive-Based Control for Leg Exoskeletons during Continuous Multi-Locomotion Tasks

An emerging approach to design locomotion assistive devices deals with reproducing desirable biological principles of human locomotion. In this paper, we present a bio-inspired controller for locomotion assistive devices based on the concept of motor primitives. The weighted combination of artificia...

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Autores principales: Ruiz Garate, Virginia, Parri, Andrea, Yan, Tingfang, Munih, Marko, Molino Lova, Raffaele, Vitiello, Nicola, Ronsse, Renaud
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5355439/
https://www.ncbi.nlm.nih.gov/pubmed/28367121
http://dx.doi.org/10.3389/fnbot.2017.00015
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author Ruiz Garate, Virginia
Parri, Andrea
Yan, Tingfang
Munih, Marko
Molino Lova, Raffaele
Vitiello, Nicola
Ronsse, Renaud
author_facet Ruiz Garate, Virginia
Parri, Andrea
Yan, Tingfang
Munih, Marko
Molino Lova, Raffaele
Vitiello, Nicola
Ronsse, Renaud
author_sort Ruiz Garate, Virginia
collection PubMed
description An emerging approach to design locomotion assistive devices deals with reproducing desirable biological principles of human locomotion. In this paper, we present a bio-inspired controller for locomotion assistive devices based on the concept of motor primitives. The weighted combination of artificial primitives results in a set of virtual muscle stimulations. These stimulations then activate a virtual musculoskeletal model producing reference assistive torque profiles for different locomotion tasks (i.e., walking, ascending stairs, and descending stairs). The paper reports the validation of the controller through a set of experiments conducted with healthy participants. The proposed controller was tested for the first time with a unilateral leg exoskeleton assisting hip, knee, and ankle joints by delivering a fraction of the computed reference torques. Importantly, subjects performed a track involving ground-level walking, ascending stairs, and descending stairs and several transitions between these tasks. These experiments highlighted the capability of the controller to provide relevant assistive torques and to effectively handle transitions between the tasks. Subjects displayed a natural interaction with the device. Moreover, they significantly decreased the time needed to complete the track when the assistance was provided, as compared to wearing the device with no assistance.
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spelling pubmed-53554392017-03-31 Experimental Validation of Motor Primitive-Based Control for Leg Exoskeletons during Continuous Multi-Locomotion Tasks Ruiz Garate, Virginia Parri, Andrea Yan, Tingfang Munih, Marko Molino Lova, Raffaele Vitiello, Nicola Ronsse, Renaud Front Neurorobot Neuroscience An emerging approach to design locomotion assistive devices deals with reproducing desirable biological principles of human locomotion. In this paper, we present a bio-inspired controller for locomotion assistive devices based on the concept of motor primitives. The weighted combination of artificial primitives results in a set of virtual muscle stimulations. These stimulations then activate a virtual musculoskeletal model producing reference assistive torque profiles for different locomotion tasks (i.e., walking, ascending stairs, and descending stairs). The paper reports the validation of the controller through a set of experiments conducted with healthy participants. The proposed controller was tested for the first time with a unilateral leg exoskeleton assisting hip, knee, and ankle joints by delivering a fraction of the computed reference torques. Importantly, subjects performed a track involving ground-level walking, ascending stairs, and descending stairs and several transitions between these tasks. These experiments highlighted the capability of the controller to provide relevant assistive torques and to effectively handle transitions between the tasks. Subjects displayed a natural interaction with the device. Moreover, they significantly decreased the time needed to complete the track when the assistance was provided, as compared to wearing the device with no assistance. Frontiers Media S.A. 2017-03-17 /pmc/articles/PMC5355439/ /pubmed/28367121 http://dx.doi.org/10.3389/fnbot.2017.00015 Text en Copyright © 2017 Ruiz Garate, Parri, Yan, Munih, Molino Lova, Vitiello and Ronsse. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Ruiz Garate, Virginia
Parri, Andrea
Yan, Tingfang
Munih, Marko
Molino Lova, Raffaele
Vitiello, Nicola
Ronsse, Renaud
Experimental Validation of Motor Primitive-Based Control for Leg Exoskeletons during Continuous Multi-Locomotion Tasks
title Experimental Validation of Motor Primitive-Based Control for Leg Exoskeletons during Continuous Multi-Locomotion Tasks
title_full Experimental Validation of Motor Primitive-Based Control for Leg Exoskeletons during Continuous Multi-Locomotion Tasks
title_fullStr Experimental Validation of Motor Primitive-Based Control for Leg Exoskeletons during Continuous Multi-Locomotion Tasks
title_full_unstemmed Experimental Validation of Motor Primitive-Based Control for Leg Exoskeletons during Continuous Multi-Locomotion Tasks
title_short Experimental Validation of Motor Primitive-Based Control for Leg Exoskeletons during Continuous Multi-Locomotion Tasks
title_sort experimental validation of motor primitive-based control for leg exoskeletons during continuous multi-locomotion tasks
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5355439/
https://www.ncbi.nlm.nih.gov/pubmed/28367121
http://dx.doi.org/10.3389/fnbot.2017.00015
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