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[多尺度肌间耦合网络分析]

[Multiple-scale intermuscular coupling network analysis].

作者信息

Wu Yating, She Qingshan, Gao Yunyuan, Tan Tongcai, Fan Yingle

机构信息

School of Automation, Hangzhou Dianzi University, Hangzhou 310018, P.R.China.

Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou 310014, P.R.China.

出版信息

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2021 Aug 25;38(4):742-752. doi: 10.7507/1001-5515.202009023.

Abstract

In order to more accurately and effectively understand the intermuscular coupling of different temporal and spatial levels from the perspective of complex networks, a new multi-scale intermuscular coupling network analysis method was proposed in this paper. The multivariate variational modal decomposition (MVMD) and Copula mutual information (Copula MI) were combined to construct an intermuscular coupling network model based on MVMD-Copula MI, and the characteristics of intermuscular coupling of multiple muscles of upper limbs in different time-frequency scales during reaching exercise in healthy subjects were analyzed by using the network parameters such as node strength and clustering coefficient. The experimental results showed that there are obvious differences in the characteristics of intermuscular coupling in the six time-frequency scales. Specifically, the triceps brachii (TB) had relatively high coupling strength with the middle deltoid (MD) and posterior deltoid (PD), and the intermuscular function was closely connected. However, the biceps brachii (BB) was independent of other muscles. The intermuscular coupling network had scale differences. MVMD-Copula MI can quantitatively describe the relationship of multi-scale intermuscular coupling strength, which has good application prospects.

摘要

为了从复杂网络的角度更准确、有效地理解不同时空尺度下的肌间耦合,本文提出了一种新的多尺度肌间耦合网络分析方法。将多变量变分模态分解(MVMD)和Copula互信息(Copula MI)相结合,构建基于MVMD-Copula MI的肌间耦合网络模型,并利用节点强度和聚类系数等网络参数,分析健康受试者在伸手运动过程中不同时频尺度上上肢多块肌肉的肌间耦合特征。实验结果表明,在六个时频尺度上肌间耦合特征存在明显差异。具体而言,肱三头肌(TB)与三角肌中束(MD)和三角肌后束(PD)具有较高的耦合强度,肌肉间功能紧密相连。然而,肱二头肌(BB)与其他肌肉相互独立。肌间耦合网络存在尺度差异。MVMD-Copula MI能够定量描述多尺度肌间耦合强度关系,具有良好的应用前景。

相似文献

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[Multiple-scale intermuscular coupling network analysis].[多尺度肌间耦合网络分析]
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本文引用的文献

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Abnormal functional corticomuscular coupling after stroke.脑卒中后皮质运动功能耦合异常。
Neuroimage Clin. 2018 Apr 4;19:147-159. doi: 10.1016/j.nicl.2018.04.004. eCollection 2018.
8
Direction Modulation of Muscle Synergies in a Hand-Reaching Task.手伸任务中肌肉协同作用的方向调制。
IEEE Trans Neural Syst Rehabil Eng. 2017 Dec;25(12):2427-2440. doi: 10.1109/TNSRE.2017.2769659.

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