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Robotic Exoskeleton Gait Training in Stroke: An Electromyography-Based Evaluation

Authors :
Eleonora Guanziroli
Valeria Longatelli
Marta Gandolla
Alessandra Pedrocchi
Franco Molteni
Source :
Frontiers in Neurorobotics, Vol 15 (2021), Frontiers in Neurorobotics
Publication Year :
2021
Publisher :
Frontiers Media S.A., 2021.

Abstract

The recovery of symmetric and efficient walking is one of the key goals of a rehabilitation program in patients with stroke. The use of overground exoskeletons alongside conventional gait training might help foster rhythmic muscle activation in the gait cycle toward a more efficient gait. About twenty-nine patients with subacute stroke have been recruited and underwent either conventional gait training or experimental training, including overground gait training using a wearable powered exoskeleton alongside conventional therapy. Before and after the rehabilitation treatment, we assessed: (i) gait functionality by means of clinical scales combined to obtain a Capacity Score, and (ii) gait neuromuscular lower limbs pattern using superficial EMG signals. Both groups improved their ability to walk in terms of functional gait, as detected by the Capacity Score. However, only the group treated with the robotic exoskeleton regained a controlled rhythmic neuromuscular pattern in the proximal lower limb muscles, as observed by the muscular activation analysis. Coherence analysis suggested that the control group (CG) improvement was mediated mainly by spinal cord control, while experimental group improvements were mediated by cortical-driven control. In subacute stroke patients, we hypothesize that exoskeleton multijoint powered fine control overground gait training, alongside conventional care, may lead to a more fine-tuned and efficient gait pattern.

Details

Language :
English
ISSN :
16625218
Volume :
15
Database :
OpenAIRE
Journal :
Frontiers in Neurorobotics
Accession number :
edsair.doi.dedup.....aca7ea75012bdc0206cbc8142a0fedb3
Full Text :
https://doi.org/10.3389/fnbot.2021.733738/full