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Electroencephalogram feature extraction and selection method

A feature extraction and EEG technology, applied in medical science, sensors, diagnostic recording/measurement, etc., can solve problems such as power frequency interference, difficult EEG data signal analysis, complex EEG signal background noise, etc., to improve accuracy degree of effect

Inactive Publication Date: 2020-06-02
苏州小蓝医疗科技有限公司
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Problems solved by technology

The EEG signal is very weak, with strong randomness and non-stationarity, and the signal is nonlinear. The background noise of the collected EEG signal is relatively complex, including power frequency interference, contact noise between the electrode and the skin, and common ground between the electrode and the ground. The interference of analog signals, etc., and the EEG signals will also be affected by individual differences. Therefore, the analysis of EEG data signals has become a difficult problem.

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  • Electroencephalogram feature extraction and selection method
  • Electroencephalogram feature extraction and selection method
  • Electroencephalogram feature extraction and selection method

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Embodiment Construction

[0032] 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.

[0033] Such as Figure 1 to Figure 3 Shown, to meet a kind of EEG feature extraction and selection method of the present invention, comprise the following steps:

[0034] S1: Perform feature extraction on the EEG data to obtain initial feature values;

[0035] S2: Perform feature combination cluster analysis on the obtained initial eigenvalues ​​to screen out effective eigenvalues.

[0036] Preferably, the step S2 specifically includes:

[0037] S21: Use th...

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Abstract

The invention discloses an electroencephalogram feature extraction and selection method. The method comprises the following steps of preprocessing electroencephalogram data to remove noise to obtain an effective electroencephalogram signal; performing feature extraction on the preprocessed electroencephalogram signal, and extracting an electroencephalogram time-frequency domain information-based feature and an entropy theory and complexity-based feature to obtain an initial feature value of the electroencephalogram signal; performing feature combination cluster analysis on the obtained initialfeature value, and screening out effective feature values. The method provides a powerful technical support for realization and development of an electroencephalogram signal technology so as to improve the accuracy of electroencephalogram signal analysis.

Description

technical field [0001] The invention relates to the technical field of EEG data analysis, in particular to a method for extracting and selecting EEG features. Background technique [0002] EEG signal is a spontaneous potential activity generated by brain nerve activity and always exists in the central nervous system. It is an important physiological electrical signal. The EEG signal is very weak, with strong randomness and non-stationarity, and the signal is nonlinear. The background noise of the collected EEG signal is relatively complex, including power frequency interference, contact noise between the electrode and the skin, and common ground between the electrode and the ground. The interference of analog signals, etc., and the EEG signals will also be affected by individual differences. Therefore, the analysis of EEG data signals has become a difficult problem. [0003] Since the information contained in the EEG signal is usually recessive, it is difficult to find all ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/0476A61B5/00
CPCA61B5/7203A61B5/725A61B5/7225A61B5/726A61B5/369
Inventor 张跃春丁衍
Owner 苏州小蓝医疗科技有限公司
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