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Dynamic brain network node consistent-behavior analysis method based on electroencephalogram signals

A technology for EEG signal and behavior analysis, applied in medical science, sensors, diagnostic recording/measurement, etc., can solve problems such as no network attribute analysis, no hierarchical structure, etc.

Inactive Publication Date: 2019-10-18
TAIYUAN UNIV OF TECH
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Problems solved by technology

After 2000, Wang Xiaofan and Chen Guanrong studied the synchronous stability model of the complex network of continuous systems coupled with oscillators. This model mainly studies the influence of network structure on the consistent behavior of dynamic network nodes; Arenas et al. The behavior process reveals the structural characteristics of the network, but its method is only applicable to the community network with a hierarchical structure, in fact, many community networks do not have a hierarchical structure
However, these methods compare the time series or the differences between electrodes, and do not analyze the properties of the network as a whole.

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  • Dynamic brain network node consistent-behavior analysis method based on electroencephalogram signals
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  • Dynamic brain network node consistent-behavior analysis method based on electroencephalogram signals

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Embodiment Construction

[0066] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0067] The method for analyzing the consistent behavior of dynamic brain network nodes based on EEG signals is carried out according to the following steps:

[0068] 1. Preprocessing and reprocessing of EEG signals.

[0069] 1. The original signal diagram of the EEG signal is as follows: figure 1 shown, then switch the reference electrode (see figure 2 ): Convert the reference electrode to a whole-brain averaged reference electrode.

[0070] 2. Goggle remo...

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Abstract

The invention discloses a dynamic brain network node consistent-behavior analysis method based on electroencephalogram signals. According to the dynamic brain network node consistent-behavior analysismethod based on electroencephalogram signals, a brain function network based on electroencephalogram signals is constructed by performing preprocessing and reprocessing on electroencephalogram signals; a complex dynamic brain network consistency model is constructed on basis of electroencephalogram signals; and then, a complex dynamic brain network model consistent-behavior discriminant is constructed so as to judge consistency and stability of brain network node behaviors. The dynamic brain network node consistent-behavior analysis method based on electroencephalogram signals can be used toverify consistency of complex dynamic behaviors of brain network nodes.

Description

technical field [0001] The invention belongs to the technical field of electroencephalogram signal processing, in particular to a method for analyzing consistent behavior of dynamic brain network nodes based on electroencephalogram signals. Background technique [0002] Behavior consistency discrimination of complex network nodes is a very important research direction in the study of complex network dynamics. Due to the complexity of complex network structure characteristics, it has brought many influences on the behavior consistency of nodes in the network. This direction has been the focus of research in recent years. At present, the research on the behavior consistency of most nodes in complex networks mainly discusses the impact of the consistency behavior of the complex network topology composed of nodes, but the process of consistency behavior is seldom studied. In fact, the process of consistent behavior is very important, because consistent behavior is a gradual pro...

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Application Information

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IPC IPC(8): A61B5/0476
CPCA61B5/369
Inventor 李海芳阴桂梅邓红霞姚蓉相洁郭浩
Owner TAIYUAN UNIV OF TECH
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