Cargando…

Automatic Setting Procedure for Exoskeleton-Assisted Overground Gait: Proof of Concept on Stroke Population

Stroke-related locomotor impairments are often associated with abnormal timing and intensity of recruitment of the affected and non-affected lower limb muscles. Restoring the proper lower limbs muscles activation is a key factor to facilitate recovery of gait capacity and performance, and to reduce...

Descripción completa

Detalles Bibliográficos
Autores principales: Gandolla, Marta, Guanziroli, Eleonora, D'Angelo, Andrea, Cannaviello, Giovanni, Molteni, Franco, Pedrocchi, Alessandra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5868134/
https://www.ncbi.nlm.nih.gov/pubmed/29615890
http://dx.doi.org/10.3389/fnbot.2018.00010
_version_ 1783309096091385856
author Gandolla, Marta
Guanziroli, Eleonora
D'Angelo, Andrea
Cannaviello, Giovanni
Molteni, Franco
Pedrocchi, Alessandra
author_facet Gandolla, Marta
Guanziroli, Eleonora
D'Angelo, Andrea
Cannaviello, Giovanni
Molteni, Franco
Pedrocchi, Alessandra
author_sort Gandolla, Marta
collection PubMed
description Stroke-related locomotor impairments are often associated with abnormal timing and intensity of recruitment of the affected and non-affected lower limb muscles. Restoring the proper lower limbs muscles activation is a key factor to facilitate recovery of gait capacity and performance, and to reduce maladaptive plasticity. Ekso is a wearable powered exoskeleton robot able to support over-ground gait training. The user controls the exoskeleton by triggering each single step during the gait cycle. The fine-tuning of the exoskeleton control system is crucial—it is set according to the residual functional abilities of the patient, and it needs to ensure lower limbs powered gait to be the most physiological as possible. This work focuses on the definition of an automatic calibration procedure able to detect the best Ekso setting for each patient. EMG activity has been recorded from Tibialis Anterior, Soleus, Rectus Femoris, and Semitendinosus muscles in a group of 7 healthy controls and 13 neurological patients. EMG signals have been processed so to obtain muscles activation patterns. The mean muscular activation pattern derived from the controls cohort has been set as reference. The developed automatic calibration procedure requires the patient to perform overground walking trials supported by the exoskeleton while changing parameters setting. The Gait Metric index is calculated for each trial, where the closer the performance is to the normative muscular activation pattern, in terms of both relative amplitude and timing, the higher the Gait Metric index is. The trial with the best Gait Metric index corresponds to the best parameters set. It has to be noted that the automatic computational calibration procedure is based on the same number of overground walking trials, and the same experimental set-up as in the current manual calibration procedure. The proposed approach allows supporting the rehabilitation team in the setting procedure. It has been demonstrated to be robust, and to be in agreement with the current gold standard (i.e., manual calibration performed by an expert engineer). The use of a graphical user interface is a promising tool for the effective use of an automatic procedure in a clinical context.
format Online
Article
Text
id pubmed-5868134
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-58681342018-04-03 Automatic Setting Procedure for Exoskeleton-Assisted Overground Gait: Proof of Concept on Stroke Population Gandolla, Marta Guanziroli, Eleonora D'Angelo, Andrea Cannaviello, Giovanni Molteni, Franco Pedrocchi, Alessandra Front Neurorobot Neuroscience Stroke-related locomotor impairments are often associated with abnormal timing and intensity of recruitment of the affected and non-affected lower limb muscles. Restoring the proper lower limbs muscles activation is a key factor to facilitate recovery of gait capacity and performance, and to reduce maladaptive plasticity. Ekso is a wearable powered exoskeleton robot able to support over-ground gait training. The user controls the exoskeleton by triggering each single step during the gait cycle. The fine-tuning of the exoskeleton control system is crucial—it is set according to the residual functional abilities of the patient, and it needs to ensure lower limbs powered gait to be the most physiological as possible. This work focuses on the definition of an automatic calibration procedure able to detect the best Ekso setting for each patient. EMG activity has been recorded from Tibialis Anterior, Soleus, Rectus Femoris, and Semitendinosus muscles in a group of 7 healthy controls and 13 neurological patients. EMG signals have been processed so to obtain muscles activation patterns. The mean muscular activation pattern derived from the controls cohort has been set as reference. The developed automatic calibration procedure requires the patient to perform overground walking trials supported by the exoskeleton while changing parameters setting. The Gait Metric index is calculated for each trial, where the closer the performance is to the normative muscular activation pattern, in terms of both relative amplitude and timing, the higher the Gait Metric index is. The trial with the best Gait Metric index corresponds to the best parameters set. It has to be noted that the automatic computational calibration procedure is based on the same number of overground walking trials, and the same experimental set-up as in the current manual calibration procedure. The proposed approach allows supporting the rehabilitation team in the setting procedure. It has been demonstrated to be robust, and to be in agreement with the current gold standard (i.e., manual calibration performed by an expert engineer). The use of a graphical user interface is a promising tool for the effective use of an automatic procedure in a clinical context. Frontiers Media S.A. 2018-03-19 /pmc/articles/PMC5868134/ /pubmed/29615890 http://dx.doi.org/10.3389/fnbot.2018.00010 Text en Copyright © 2018 Gandolla, Guanziroli, D'Angelo, Cannaviello, Molteni and Pedrocchi. 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) and the copyright owner 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
Gandolla, Marta
Guanziroli, Eleonora
D'Angelo, Andrea
Cannaviello, Giovanni
Molteni, Franco
Pedrocchi, Alessandra
Automatic Setting Procedure for Exoskeleton-Assisted Overground Gait: Proof of Concept on Stroke Population
title Automatic Setting Procedure for Exoskeleton-Assisted Overground Gait: Proof of Concept on Stroke Population
title_full Automatic Setting Procedure for Exoskeleton-Assisted Overground Gait: Proof of Concept on Stroke Population
title_fullStr Automatic Setting Procedure for Exoskeleton-Assisted Overground Gait: Proof of Concept on Stroke Population
title_full_unstemmed Automatic Setting Procedure for Exoskeleton-Assisted Overground Gait: Proof of Concept on Stroke Population
title_short Automatic Setting Procedure for Exoskeleton-Assisted Overground Gait: Proof of Concept on Stroke Population
title_sort automatic setting procedure for exoskeleton-assisted overground gait: proof of concept on stroke population
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5868134/
https://www.ncbi.nlm.nih.gov/pubmed/29615890
http://dx.doi.org/10.3389/fnbot.2018.00010
work_keys_str_mv AT gandollamarta automaticsettingprocedureforexoskeletonassistedovergroundgaitproofofconceptonstrokepopulation
AT guanzirolieleonora automaticsettingprocedureforexoskeletonassistedovergroundgaitproofofconceptonstrokepopulation
AT dangeloandrea automaticsettingprocedureforexoskeletonassistedovergroundgaitproofofconceptonstrokepopulation
AT cannaviellogiovanni automaticsettingprocedureforexoskeletonassistedovergroundgaitproofofconceptonstrokepopulation
AT moltenifranco automaticsettingprocedureforexoskeletonassistedovergroundgaitproofofconceptonstrokepopulation
AT pedrocchialessandra automaticsettingprocedureforexoskeletonassistedovergroundgaitproofofconceptonstrokepopulation