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A method and system for analyzing the chaotic characteristics of EEG

An analysis method and chaotic technology, applied in the field of EEG chaotic characteristic analysis, can solve the problem of not being able to identify the similarities and differences between vibrations well

Active Publication Date: 2018-05-01
BEIJING UNIV OF TECH
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  • Description
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  • Application Information

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Problems solved by technology

[0004] Aiming at the defect that the existing technology cannot well identify the similarity and difference between vibrations, and the analysis of EEG has certain limitations, the present invention provides an analysis method and system for the chaotic characteristics of EEG

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  • A method and system for analyzing the chaotic characteristics of EEG
  • A method and system for analyzing the chaotic characteristics of EEG
  • A method and system for analyzing the chaotic characteristics of EEG

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Embodiment Construction

[0065] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

[0066] Such as figure 1 As shown, it is a schematic flowchart of a method for analyzing chaotic characteristics of EEG according to an embodiment of the present invention. The method includes the following steps:

[0067] S1: Filter the EEG signal, and decompose the filtered EEG signal into several sub-band signals.

[0068] Specifically, filtering the brain electrical signal refers to performing band-pass filtering on the brain electrical ...

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Abstract

The present invention provides a method for analyzing the chaotic characteristics of EEG, comprising: filtering the EEG signal, and decomposing the filtered EEG signal into several sub-frequency band signals; extracting the extreme points of each sub-frequency band signal and the The time point corresponding to the extremum point, and according to the extremum point and the time point, generate a monotone amplitude sequence and a monotone period sequence; the monotone amplitude sequence and the monotone period sequence are formed into a vector sequence, and the vector sequence Perform artifact removal; divide the vector sequence into several subintervals from the two dimensions of monotone amplitude and monotone period, obtain the probability that each vector is distributed in each subinterval, and obtain the EEG signal according to the probability the vibration entropy of the EEG signal; analyzing the degree of chaos of the EEG signal according to the vibration entropy of the EEG signal. The invention can effectively reflect the distribution characteristics of the vibration characteristics of the waveform of the electroencephalogram signal.

Description

Technical field [0001] The invention relates to the technical field of brain electrical signal processing, and in particular to a method and system for analyzing the chaotic characteristics of brain electrical signals. Background technique [0002] EEG signals have time-varying nonlinear characteristics. Time-domain nonlinear analysis is an important aspect of EEG signal processing, including correlation dimension, Lyapunov exponent, wavelet entropy, approximate entropy, multi-scale entropy, etc., which are relatively common at present Methods. [0003] Amplitude and period are two important variables to express the waveform vibration, but because of the irregular changes in the amplitude and period of the EEG waveform, the start and end points of the vibration are not clear, so it is difficult to determine the amplitude and period of a single vibration of the EEG signal Therefore, the existing non-linear processing methods of EEG generally only analyze the signal sampling point s...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00
CPCG06F2218/02G06F2218/08G06F2218/12
Inventor 钟宁郭家梁周海燕杨孝敬马小萌李淮周
Owner BEIJING UNIV OF TECH
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