Muscle synergies as a predictive framework for the EMG patterns of new hand postures.

Muscle synergies as a predictive framework for the EMG patterns of new hand postures.
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肌肉协同作用是新手姿势的EMG模式的预测框架。

DOI:
10.1088/1741-2560/6/3/036004
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发表时间:
2009-06
影响因子:
4
通讯作者:
Weir RF
Weir RF
中科院分区:
工程技术2区
文献类型:
--
作者:
Ajiboye AB;Weir RF

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同步肌肉协同效应被认为是肌肉协调中降维的一个框架。许多研究表明,协同效应为各种任务形成了一个描述性框架。我们研究了肌肉协同框架是否能准确预测与未经训练的静态手势相关的肌电模式,本质上,如果它们形成了一个预测框架。受试者静态模仿美国手语字母表中的33种姿势时,记录了手和前臂的肌肉活动。使用非负矩阵分解从训练姿势的子集中提取协同效应,并用于预测其余姿势的肌电模式。在受试者群体中,只有11个姿势就可以形成一个八维协同框架,允许至少90%预测所有33个姿势的肌电模式,包括试验到试验的变化。尽管在训练组中使用了不同的姿势,而且使用了不同数量的姿势,但协同效应仍然相当强劲。估计的协同作用被分为针对特定主题的协同作用和针对全体人口的协同作用。群体协同效应比特定对象的协同效应更稀疏,通常由单一肌肉主导。在多个肌肉的共同激活中,特定受试者的协同作用更加平衡。因此,我们认为全局肌肉协调可能是强健的特定对象肌肉协同的高阶控制和个性化肌肉的低阶控制的组合,并且这种控制范式可能在基于EMG的技术的控制中有用,例如假肢和功能性电刺激系统。
Synchronous muscle synergies have been suggested as a framework for dimensionality reduction in muscle coordination. Many studies have shown that synergies form a descriptive framework for a wide variety of tasks. We examined if a muscle synergy framework could accurately predict the EMG patterns associated with untrained static hand postures, in essence, if they formed a predictive framework. Hand and forearm muscle activities were recorded while subjects statically mimed 33 postures of the American Sign Language alphabet. Synergies were extracted from a subset of training postures using non-negative matrix factorization and used to predict the EMG patterns of the remaining postures. Across the subject population, as few as 11 postures could form an eight-dimensional synergy framework that allowed for at least 90% prediction of the EMG patterns of all 33 postures, including trial-to-trial variations. Synergies were quite robust despite using different postures in the training set, and also despite using a varied number of postures. Estimated synergies were categorized into those which were subject-specific and those which were general to the population. Population synergies were sparser than the subject-specific synergies, typically being dominated by a single muscle. Subject-specific synergies were more balanced in the coactivation of multiple muscles. We suggest as a result that global muscle coordination may be a combination of higher order control of robust subject-specific muscle synergies and lower order control of individuated muscles, and that this control paradigm may be useful in the control of EMG-based technologies, such as artificial limbs and functional electrical stimulation systems.
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