协同肌的合并和肌间一致性预测肌肉协调的复杂性

Xinxin Li, Yihao Du, Chunhua Yang, Wenjing Qi, P. Xie
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引用次数: 5

摘要

研究表明,神经系统通过模块化结构简化了对运动的控制,然而,这种模块化结构的复杂性是否与肌肉耦合有关还没有得到很好的证明。本研究的目的是检验协同肌肉和肌间连贯预测肌肉协调复杂性的作用。记录了8名健康受试者上肢8块肌肉的肌电图活动。他们用主臂进行两种不同的活动,特别是不知道下一个动作是什么,他们专注于指示性图像。我们首先通过非负矩阵分解确定运动模块的数量为5,并考虑到肌肉激活的可变性。接下来,我们通过相干方法计算肌肉之间的耦合关系,这是肌电信号对,包括协同和非协同肌肉。我们发现协同肌中存在强耦合肌;大多数同时观测到β带和γ带。识别耦合肌肉的协同作用可能会导致探索神经控制机制的新见解。
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Merging of synergistic muscles and intermuscular coherence predict muscle coordination complexity
Studies have shown that the nervous system through the modular structure simplifies control the movement, however, whether such a modular structure complexity associated with muscle coupling has not been proven well. The purpose of this study was to examine the effect of synergistic muscles and intermuscular coherence predicts muscle coordination complexity. Electormyographic (EMG) activity was recorded from eight upper limb muscles of eight healthy subjects. They performed two different activities with the dominant arm, especially were not known what is the next action, they focus on indicative images. We first determine the number of motion modules was 5 through nonnegative matrix factorization with the account for variability of muscle activation. Next, we calculate the coupling relationship between muscles through approach of coherence, which are the pairs of EMG signals, both synergistic and non-synergistic muscles. We found a strong coupling muscles exist in synergistic muscles; most were observed both beta band and gamma band. Identification coupling muscles of the synergistic may lead to new insight into explored the neural control mechanism.
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