Evaluation of EMG patterns in children during assisted walking in the exoskeleton.

IF 3.2 3区 医学 Q2 NEUROSCIENCES
Frontiers in Neuroscience Pub Date : 2024-10-24 eCollection Date: 2024-01-01 DOI:10.3389/fnins.2024.1461323
Margherita Villani, Priscilla Avaltroni, Giulia Scordo, Damiana Rubeca, Peter Kreynin, Ekaterina Bereziy, Denise Berger, Germana Cappellini, Francesca Sylos-Labini, Francesco Lacquaniti, Yury Ivanenko
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引用次数: 0

Abstract

While exoskeleton technology is becoming more and more common for gait rehabilitation in children with neurological disorders, evaluation of gait performance still faces challenges and concerns. The reasoning behind evaluating the spinal locomotor output is that, while exoskeleton's guidance forces create the desired walking kinematics, they also affect sensorimotor interactions, which may lead to an abnormal spatiotemporal integration of activity in particular spinal segments and the risk of abnormalities in gait recovery. Therefore, traditional indicators based on kinematic or kinetic characteristics for optimizing exoskeleton controllers for gait rehabilitation may be supplemented by performance measures associated with the neural control mechanisms. The purpose of this study on a sample of children was to determine the basic features of lower limb muscle activity and to implement a method for assessing the neuromechanics of spinal locomotor output during exoskeleton-assisted gait. To this end, we assessed the effects of a robotic exoskeleton (ExoAtlet Bambini) on gait performance, by recording electromyographic activity of leg muscles and analyzing the corresponding spinal motor pool output. A slower walking setting (about 0.2 m/s) was chosen on the exoskeleton. The results showed that, even with slower walking, the level of muscle activation was roughly comparable during exoskeleton-assisted gait and normal walking. This suggests that, despite full assistance for leg movements, the child's locomotor controllers can interpret step-related afferent information promoting essential activity in leg muscles. This is most likely explained by the active nature of stepping in the exoskeleton (the child was not fully relaxed, experienced full foot loading and needed to maintain the upper trunk posture). In terms of the general muscle activity patterns, we identified notable variations for the proximal leg muscles, coactivation of the lumbar and sacral motor pools, and weak propulsion from the distal extensors at push-off. These changes led to the lack of characteristic lumbosacral oscillations of the center of motoneuron activity, normally associated with the pendulum mechanism of bipedal walking. This work shows promise as a useful technique for analyzing exoskeleton performance to help children develop their natural gait pattern and to guide system optimization in the future for inclusion into clinical care.

评估儿童在外骨骼辅助行走时的肌电图模式。
虽然外骨骼技术在神经系统疾病儿童的步态康复中越来越常见,但步态表现评估仍面临挑战和问题。评估脊柱运动输出的理由是,外骨骼的引导力在创造理想的行走运动学的同时,也会影响传感运动的相互作用,这可能会导致特定脊柱节段活动的时空整合异常以及步态恢复异常的风险。因此,在优化步态康复外骨骼控制器时,基于运动学或动力学特征的传统指标可以通过与神经控制机制相关的性能测量来补充。本研究以儿童为样本,旨在确定下肢肌肉活动的基本特征,并采用一种方法来评估外骨骼辅助步态时脊柱运动输出的神经力学。为此,我们通过记录腿部肌肉的肌电活动并分析相应的脊柱运动池输出,评估了机器人外骨骼(ExoAtlet Bambini)对步态表现的影响。外骨骼选择了较慢的行走速度(约 0.2 米/秒)。结果显示,即使行走速度较慢,外骨骼辅助步态和正常行走时的肌肉激活水平大致相当。这表明,尽管腿部运动完全由外骨骼辅助,但儿童的运动控制器仍能解读与步速相关的传入信息,促进腿部肌肉的基本活动。这很可能是由于在外骨骼中迈步的主动性(儿童没有完全放松,经历了完全的足部负荷,并需要保持上躯干姿势)。在一般肌肉活动模式方面,我们发现腿部近端肌肉有明显变化,腰部和骶部运动池共同激活,远端伸肌在推起时的推进力较弱。这些变化导致腰骶部运动神经元活动中心缺乏特征性摆动,而这种摆动通常与双足行走的钟摆机制有关。这项研究表明,分析外骨骼性能是一项有用的技术,可帮助儿童发展自然步态,并指导系统优化,以便将来纳入临床护理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Frontiers in Neuroscience
Frontiers in Neuroscience NEUROSCIENCES-
CiteScore
6.20
自引率
4.70%
发文量
2070
审稿时长
14 weeks
期刊介绍: Neural Technology is devoted to the convergence between neurobiology and quantum-, nano- and micro-sciences. In our vision, this interdisciplinary approach should go beyond the technological development of sophisticated methods and should contribute in generating a genuine change in our discipline.
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