肌肉协同效应及其适应的不同理论

A. T. Abd, Rajat Emanuel Singh, K. Iqbal, G. White
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引用次数: 5

摘要

人类运动系统是一个复杂的神经-肌肉-感觉系统,需要进一步研究神经-肌肉命令和感觉-运动耦合来解码运动执行。一些研究人员认为,中枢神经系统(CNS)激活一小组称为肌肉协同作用的模块,以简化运动控制。此外,这些模块形成了运动的功能构建块,因为它们可以解释运动的神经生理学特征。我们可以通过使用线性分解算法,如主成分分析(PCA)和非负矩阵分解算法(NNMF),从实验室记录的肌电图信号(EMG)中识别和提取这些肌肉协同作用。在过去的三十年里,肌肉协同作用的假设受到了相当大的关注,因为我们试图理解并应用肌肉协同作用在临床环境和康复中的概念。在这篇文章中,我们首先探讨了肌肉协同作用的概念。然后,我们在中枢神经系统用于实现运动目标的协同作用中提出了不同的适应策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Perspective on Muscle Synergies and Different Theories Related to Their Adaptation
The human motor system is a complex neuro-musculo sensory system that needs further investigations of neuro-muscular commands and sensory-motor coupling to decode movement execution. Some researchers suggest that the central nervous system (CNS) activates a small set of modules termed muscle synergies to simplify motor control. Further, these modules form functional building blocks of movement as they can explain the neurophysiological characteristics of movements. We can identify and extract these muscle synergies from electromyographic signals (EMG) recorded in the laboratory by using linear decomposition algorithms, such as principal component analysis (PCA) and non-Negative Matrix Factorization Algorithm (NNMF). For the past three decades, the hypothesis of muscle synergies has received considerable attention as we attempt to understand and apply the concept of muscle synergies in clinical settings and rehabilitation. In this article, we first explore the concept of muscle synergies. We then present different strategies of adaptation in these synergies that the CNS employs to accomplish a movement goal.
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CiteScore
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