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Intermuscular coupling analysis method capable of combining nonnegative matrix decomposition with complex network

A non-negative matrix decomposition and complex network technology, applied in the field of signal processing, can solve problems such as the lack of in-depth exploration of the coupling relationship between multiple muscles

Active Publication Date: 2019-04-26
HANGZHOU DIANZI UNIV
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  • Application Information

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Problems solved by technology

The above studies only analyzed the coherence between two muscles, and did not explore the coupling relationship between multiple muscles in depth

Method used

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  • Intermuscular coupling analysis method capable of combining nonnegative matrix decomposition with complex network
  • Intermuscular coupling analysis method capable of combining nonnegative matrix decomposition with complex network
  • Intermuscular coupling analysis method capable of combining nonnegative matrix decomposition with complex network

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Embodiment Construction

[0051] Below in conjunction with accompanying drawing, the embodiment of the present invention is described in detail: present embodiment implements under the premise of technical scheme of the present invention, has provided detailed implementation mode and concrete operation process:

[0052] Such as figure 1 As shown, this implementation patent includes the following steps:

[0053] In step 1, the 7-channel surface electromyographic signal (EMG) was collected at different grip force outputs. The specific collection operation is as follows:

[0054] Six right-handed healthy subjects without any medical history were selected. In a quiet laboratory, the subjects sat upright on a wooden chair, and the grip dynamometer was placed on the palms of the subjects. Before the experiment started, we measured the MVC of each subject. We used the spring grip dynamometer to carry out grasping experiments with 5%, 20%, 40%, 60%, and 80% of the MVC force output. Constant force o...

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Abstract

The invention provides an intermuscular coupling analysis method capable of combining nonnegative matrix decomposition with a complex network. The method comprises the following steps: collecting seven-channel surface electromyogram signals when different grip strengths are output; firstly, adopting generalized partial directional coherence to calculate coherence among multiple channels; then, adopting a nonnegative matrix decomposition algorithm to decompose a coherence value; finally, adopting the complex network to establish muscle function networks under different conditions. The characteristic index of a graph theory is used for evaluating the transfer efficiency of a muscle function network information flow. A result displays that muscle activation degrees under different grip strengths have significant differences; intermuscular coupling is obvious on a waveband of 10-20 Hz; in addition, on the waveband of 10-20 Hz, the coupling degree of muscles is significantly changed along with different grip strength levels. According to the intermuscular coupling analysis method, multichannel intermuscular coupling analysis is carried out to embody the control pattern of a central nervous system for different output grip strengths, and a basis is provided for evaluating the diagnosis and rehabilitation effect of dyskinesia.

Description

technical field [0001] The invention belongs to the field of signal processing, and relates to a coupling method of EEG and EMG signals, in particular to an analysis method applied to intermuscular coupling states. Background technique [0002] Surface electromyography (sEMG) is the action potential generated by muscle contraction during muscle movement. It is superimposed on the surface of the skin and has a direct relationship with the movement of the limbs. Intermuscular Coupling (IMC) refers to the interaction or coherence and time synchronization between muscles. Muscle-to-muscle coupling can indirectly reveal information that is commonly input to muscles from the subcortex, which is beneficial for us to explore the coordinated control of muscles by the central nervous system. Human beings can complete different actions according to different needs. Among them, grasping is one of the most basic movements of the upper limbs of the human body. The process of grasping re...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/00A61B5/0488
CPCA61B5/7203A61B5/7235A61B5/389
Inventor 高云园黄威陈强佘青山席旭刚马玉良
Owner HANGZHOU DIANZI UNIV
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