Rahimi Goloujeh Mohammad, Allen Jessica L
Department of Mechanical and Aerospace Engineering, University of Florida, PO Box 116250, Gainesville, FL, 32611, USA.
J Neuroeng Rehabil. 2025 Jan 30;22(1):16. doi: 10.1186/s12984-025-01561-8.
Motor module (a.k.a. muscle synergy) analysis has frequently been used to provide insight into changes in muscle coordination associated with declines in walking performance, to evaluate the effect of different rehabilitation interventions, and more recently, to control exoskeletons and prosthetic devices. However, it remains unclear whether changes in muscle coordination revealed via motor module analysis stem from abnormal walking biomechanics or neural control. This distinction has important implications for the use of motor module analysis for rehabilitation interventions and device design. Thus, this study aims to elucidate the extent to which motor modules emerge from pathological walking biomechanics, i.e. abnormal walking biomechanics commonly observed in individuals with neurological disease and/or injury.
We conducted a series of computer simulations using OpenSim Moco to simulate pathological walking biomechanics by manipulating speed, asymmetry, and step width in a three-dimensional musculoskeletal model. We focused on these spatiotemporal metrics because they are commonly altered in individuals with Parkinson's disease, stroke survivors, etc. and have been associated with changes in motor module number and structure. We extracted motor modules using nonnegative matrix factorization from the muscle activations from each simulation. We then examined how alterations in walking biomechanics influenced the number and structure of extracted motor modules and compared the findings to previous experimental studies.
The motor modules identified from our simulations were similar to those identified from previously published experiments of non-pathological walking. Moreover, our findings indicate that the same motor modules can be used to generate a range of pathological-like waking biomechanics by modulating their recruitment over the gait cycle. These results contrast with experimental studies in which pathological-like walking biomechanics are accompanied by a reduction in motor module number and alterations in their structure.
This study highlights that pathological walking biomechanics do not necessarily require abnormal motor modules. In other words, changes in number and structure of motor modules can be a valuable indicator of alterations in neuromuscular control and may therefore be useful for guiding rehabilitation interventions and controlling exoskeletons and prosthetic devices in individuals with impaired walking function due to neurological disease or injury.
运动模块（又称肌肉协同）分析经常被用于深入了解与步行能力下降相关的肌肉协调变化，评估不同康复干预措施的效果，以及最近用于控制外骨骼和假肢装置。然而，通过运动模块分析揭示的肌肉协调变化是源于异常的步行生物力学还是神经控制，仍不清楚。这种区分对于将运动模块分析用于康复干预和装置设计具有重要意义。因此，本研究旨在阐明运动模块在多大程度上源于病理性步行生物力学，即神经疾病和/或损伤个体中常见的异常步行生物力学。
我们使用OpenSim Moco进行了一系列计算机模拟，通过在三维肌肉骨骼模型中操纵速度、不对称性和步幅来模拟病理性步行生物力学。我们关注这些时空指标，因为它们在帕金森病患者、中风幸存者等个体中通常会发生改变，并且与运动模块数量和结构的变化有关。我们使用非负矩阵分解从每个模拟的肌肉激活中提取运动模块。然后，我们研究了步行生物力学的改变如何影响提取的运动模块的数量和结构，并将结果与之前的实验研究进行比较。
我们模拟中识别出的运动模块与之前发表的非病理性步行实验中识别出的运动模块相似。此外，我们的研究结果表明，通过在步态周期中调节运动模块的募集，可以使用相同的运动模块来生成一系列类似病理性的步行生物力学。这些结果与实验研究形成对比，在实验研究中，类似病理性的步行生物力学伴随着运动模块数量的减少和结构的改变。
本研究强调病理性步行生物力学不一定需要异常的运动模块。换句话说，运动模块数量和结构的变化可能是神经肌肉控制改变的有价值指标，因此可能有助于指导康复干预以及控制因神经疾病或损伤而步行功能受损个体的外骨骼和假肢装置。
