Cortical muscle function network construction method based on R-vine Copula

A technology of functional network and construction method, applied in the field of cortical muscle functional network construction based on R-vineCopula, to achieve the effect of strengthening high-dimensional problems and improving processing ability

Inactive Publication Date: 2021-09-28
睿旭康苏州智能技术有限责任公司
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  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Compared with the traditional Copula, Vine Copula makes high-dimensional multivariate problems more intuitive. Existing research focuses on the selection of binary fu...

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  • Cortical muscle function network construction method based on R-vine Copula
  • Cortical muscle function network construction method based on R-vine Copula
  • Cortical muscle function network construction method based on R-vine Copula

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Embodiment Construction

[0051] This embodiment is carried out on the premise of the technical solution of the present invention, and a detailed implementation manner and specific operation process are given. Embodiments of the present invention are described in detail below in conjunction with accompanying drawings:

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

[0053] Step 1. In the overall experimental data collection process, a total of 12 healthy subjects (6 males and 6 females; age: 21-26 years old; height: 164-187cm; weight: 45-85kg) were selected as experimental subjects. Such as figure 2 Simultaneously record EEG signals and sEMG signals from multiple subjects. It is required to walk forward and backward in a straight line on a level ground according to the metronome command speed (60bmp and 120bmp), and complete two 2-minute walks up and down with 8 steps stairs task. In this paper, two sets of instruments, wirelessEEG amplifier NeuSen.W64, Neuracle ...

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Abstract

The invention discloses a cortical muscle function network construction method based on R-vine Copula. According to the method, firstly, electroencephalogram signals and surface electromyogram signals from multiple subjects are synchronously recorded, and specific tasks are required to be executed according to metronome instructions; and other artifacts are separated from the collected electroencephalogram and electromyogram data by adopting independent component analysis, and de-noising is conducted by adopting a wavelet threshold. and secondly, a new cortical muscle function method for quantitatively analyzing the complex causal relationship between cortical muscle signals is constructed. According to the method, R-vine Copula is used for carrying out electroencephalogram and electromyogram nonlinear coupling analysis and brain muscle function network modeling, and a large number of experiments prove that the method can effectively describe cortical muscle connectivity in a specific walking state, and the constructed cortical muscle function network is meaningful.

Description

technical field [0001] The invention belongs to the field of signal processing, and relates to an R-vine Copula-based cortical muscle function network construction method. Background technique [0002] For the rehabilitation of lower limbs after stroke, the recovery of walking function is extremely important. Walking is a complex task that requires the coordination and flexible movement of several muscles, depending on the complex control of the central nervous system in response to changing environmental challenges. The complex control between the cerebral cortex and muscles is mainly reflected in the degree of connection between the EEG signal, the surface electromyographic signal sEMG and the EEG-sEMG signal. The characteristics of EEG-sEMG signals and the coupling of EEG-sEMG signals can reflect the principle of brain function control and functional connection with muscles. The research results that have been obtained so far show that walking training can adjust the fu...

Claims

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Application Information

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IPC IPC(8): A61B5/372A61B5/397A61B5/00G06K9/00
CPCA61B5/372A61B5/397A61B5/7203A61B5/7264G06F2218/06G06F2218/10
Inventor 汪婷席旭刚樊竹尧文燕赵云波
Owner 睿旭康苏州智能技术有限责任公司
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