Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daehak-ro 291, Yuseong-gu, Daejeon, 34141, Republic of Korea.
Max Nader Lab for Rehabilitation Technologies and Outcomes Research, Shirley Ryan AbilityLab, 355 E Erie St, Chicago, IL, 60611, USA.
J Neuroeng Rehabil. 2021 Apr 7;18(1):58. doi: 10.1186/s12984-021-00860-0.
Recent evidence suggests that disinhibition and/or hyperexcitation of the brainstem descending pathways and intraspinal motor network diffuse spastic synergistic activation patterns after stroke. This results in simplified or merged muscle sets (i.e., muscle modules or synergies) compared to non-impaired individuals and this leads to poor walking performance. However, the relations of how these neuromuscular deficits influence gait quality (e.g., symmetry or natural walking patterns) are still unclear. The objective of this exploratory study was to investigate the relations of modular neuromuscular framework and gait quality measures in chronic stroke individuals.
Sixteen chronic post-stroke individuals participated in this study. Full lower body three-dimensional kinematics and electromyography (EMG) were concurrently measured during overground walking at a comfortable speed. We first examined changes in gait quality measures across the number of muscle modules using linear regression model. Then, a stepwise multiple regression was used to investigate the optimal combination of the neuromuscular parameters that associates with gait quality measures.
We observed that subjects who had a lower number of muscle modules revealed reduced function (i.e., speed) and greater asymmetry in the kinematic parameters including limb length, footpath area, knee flexion/extension, and hip abduction/adduction (all p < 0.05). We also found that the combination of input variables from the modular neuromuscular control framework significantly associated with gait quality measures (average [Formula: see text]). Those variables included variability accounted for ([Formula: see text]) information from the muscle modules and area under the EMG envelope curves of the quadriceps (i.e., rectus femoris and vastus lateralis) and tibialis anterior muscles.
The results suggest that there exists a significant correlation between the neuromuscular control framework and the gait quality measures. This study helps to understand the underlying mechanism of disturbances in gait quality and provides insight for a more comprehensive outcome measure to assess gait impairment after stroke.
最近的证据表明，脑桥下行通路和脊髓内运动网络的抑制作用丧失和/或过度兴奋会导致中风后弥散性痉挛协同激活模式。这导致与非受损个体相比，肌肉集合（即肌肉模块或协同作用）简化或合并，从而导致行走能力较差。然而，这些神经肌肉缺陷如何影响步态质量（例如，对称性或自然行走模式）的关系尚不清楚。本探索性研究的目的是调查慢性中风患者的模块化神经肌肉框架与步态质量测量之间的关系。
16 名慢性中风后患者参与了本研究。在舒适速度下进行地面行走时，同时进行全身三维运动学和肌电图（EMG）的测量。我们首先使用线性回归模型检查步态质量测量值随肌肉模块数量的变化。然后，使用逐步多元回归来研究与步态质量测量值相关的神经肌肉参数的最佳组合。
我们观察到，肌肉模块数量较少的受试者的运动学参数（包括肢体长度、足迹面积、膝关节屈伸和髋关节外展/内收）的功能（即速度）降低，并且对称性增加（均 p < 0.05）。我们还发现，模块化神经肌肉控制框架的输入变量组合与步态质量测量值显著相关（平均值 [Formula: see text]）。这些变量包括肌肉模块的变异性占比 ([Formula: see text])信息以及股四头肌（即股直肌和股外侧肌）和胫骨前肌的 EMG 包络曲线下面积。
结果表明，神经肌肉控制框架与步态质量测量值之间存在显著相关性。这项研究有助于理解步态质量障碍的潜在机制，并为评估中风后步态障碍提供更全面的预后测量方法。
