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Electroencephalogram chaos characteristic analysis method and system

A chaotic and characteristic technology, applied in the recognition of patterns in signals, instruments, characters and patterns, etc., can solve the problem of not being able to identify similarities and differences between vibrations well

Active Publication Date: 2015-08-19
BEIJING UNIV OF TECH
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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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  • Electroencephalogram chaos characteristic analysis method and system
  • Electroencephalogram chaos characteristic analysis method and system
  • Electroencephalogram chaos characteristic analysis method and system

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Embodiment Construction

[0065] 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.

[0066] like figure 1 As shown, it is a schematic flow chart of an analysis method of an EEG chaotic characteristic provided by 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-frequency band signals.

[0068] Specifically, filtering the EEG signals refers to performing band-pass filtering on the EEG signals, for example, removing signals ...

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Abstract

The invention relates to an electroencephalogram chaos characteristic analysis method. The method includes the following steps that: electroencephalogram signals are filtered, and the filtered electroencephalogram signals are decomposed into a plurality of sub-band signals; extreme values points and time points corresponding to the extreme values points of the sub-band signals are extracted, and a monotonic amplitude sequence and a monotonic period sequence are generated according to the extreme values points and the time points; the monotonic amplitude sequence and the monotonic period sequence constitute a vector sequence, and artifact removal is performed on the vector sequence; the vector sequence is divided into a plurality of subintervals in the dimensionalities of monotonic amplitude and monotonic period, so that the probability of each vector distributing in each subinterval can be obtained, and the vibrational entropy of the electroencephalogram signals can be obtained according to the probability; and the chaos degree of the electroencephalogram signals is analyzed according to the vibrational entropy of the electroencephalogram signals. The electroencephalogram chaos characteristic analysis method of the invention can effectively reflect the distribution characteristics of the waveform vibration characteristics of the electroencephalogram signals.

Description

technical field [0001] The invention relates to the technical field of EEG signal processing, in particular to a method and system for analyzing EEG chaotic characteristics. Background technique [0002] EEG signals have time-varying nonlinear characteristics, and nonlinear analysis in time domain is an important aspect of EEG signal processing, including correlation dimension, Lyapunov index, wavelet entropy, approximate entropy, multi-scale entropy, etc. Methods. [0003] Amplitude and period are two important variables to express waveform vibration, but because of the irregular changes in amplitude and period of EEG waveform, the starting point and end point of vibration are not clear, so it is difficult to determine the amplitude and period of a single vibration of EEG signal , so the existing EEG nonlinear processing methods generally only analyze the sampling point sequence of the signal, and some methods of extracting amplitude and period analysis usually only focus ...

Claims

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Application Information

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Patent Type & Authority Applications(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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