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健康人和脑卒中后步态中通过肌肉协同作用评估踝关节肌肉激活。

Assessment of ankle muscle activation by muscle synergies in healthy and post-stroke gait.

机构信息

College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, People's Republic of China.

出版信息

Physiol Meas. 2018 Apr 20;39(4):045003. doi: 10.1088/1361-6579/aab2ed.

Abstract

OBJECTIVE

Impaired ankle dorsal and plantar flexor function is a frequent sequela of stroke. A better assessment of ankle muscle activation would be highly significant for stroke rehabilitation. The challenge in implementing current electromyography (EMG)-based assessments is due to problems with the variability and individuality of ankle muscle EMG profiles during walking. We have been studying a new technique using the muscle synergy method to quantify the characteristics that underlie ankle muscle activation to address this issue.

APPROACH

We processed surface EMG signals from ankle muscles and gait parameters collected from 20 healthy and 22 post-stroke subjects during walking. A non-negative matrix factorization algorithm was used to extract muscle synergies.

MAIN RESULTS

Our results suggest a featured muscle synergy structure (R  =  0.84, 95% CI: 0.83-0.85) underlying ankle muscle activation in both healthy and post-stroke subjects. The structure of the featured muscle synergy was robust in the same subjects across different conditions in the healthy group (R  =  0.97, 95% CI: 0.96-0.98) and the post-stroke group (R  =  0.95, 95% CI: 0.88-0.97). Compared to the stroke group, the synergy patterns of healthy subjects showed better regularity and higher inter-subject similarity (P  =  0.001). In addition, the results of muscle synergies were indicative of locomotor performance.

SIGNIFICANCE

The innovative quantitative results of this study can help us to better understand ankle muscle activation and will be a reference for clinical assessments and intervention studies.

摘要

目的

踝关节背屈和跖屈肌功能障碍是中风后的常见后遗症。更好地评估踝关节肌肉的激活对于中风康复具有重要意义。在实施基于肌电图(EMG)的评估时,挑战在于行走过程中踝关节肌肉 EMG 谱的可变性和个体差异。我们一直在研究一种新的技术,使用肌肉协同方法来量化踝关节肌肉激活的特征,以解决这个问题。

方法

我们处理了 20 名健康受试者和 22 名中风后受试者在行走过程中来自踝关节肌肉的表面 EMG 信号和步态参数。使用非负矩阵分解算法提取肌肉协同。

主要结果

我们的结果表明,在健康和中风后受试者中,踝关节肌肉激活存在一种特征性的肌肉协同结构(R=0.84,95%置信区间:0.83-0.85)。在健康组(R=0.97,95%置信区间:0.96-0.98)和中风后组(R=0.95,95%置信区间:0.88-0.97)中,相同受试者在不同条件下的特征性肌肉协同结构具有稳健性。与中风组相比,健康受试者的协同模式具有更好的规律性和更高的个体间相似性(P=0.001)。此外,肌肉协同的结果表明运动表现。

意义

这项研究的创新性定量结果可以帮助我们更好地理解踝关节肌肉的激活,并为临床评估和干预研究提供参考。

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