Electrocerebral non-linear dual-measure feature extraction and fusion processing method

Abstract

The invention discloses an electrocerebral non-linear dual-measure feature extraction and fusion processing method, and relates to the field of electrocerebral signals. The method comprises the following steps: acquiring an electrocerebral signal; performing data preprocessing on the electrocerebral signal; extracting an LZC (Leucocyte Zinc Content) complexity feature from preprocessed data; extracting a sample entropy feature, and performing feature analysis on the LZC complexity feature and the sample entropy feature; establishing a classification model with an SVM (Support Vector Machine) classifier by jointly taking the LZC value of the electrocerebral signal and a sample entropy value which are remarkably different as a feature parameter in order to classify and identify people in different psychological states. By adopting the method for classifying and identifying the electrocerebral signals of people in different psychological states, higher classifying accuracy can be achieved, and an objective evaluation index can be provided for the partition of people in different psychological states.

Description

technical field [0001] The invention relates to the field of EEG signals, in particular to an EEG nonlinear double-measure feature extraction and fusion processing method. Background technique [0002] With the rapid development of society, people's living environment, lifestyle and habits, and working conditions have all changed. The increasingly fast pace of life makes people in modern cities feel more and more lonely and depressed. Facing such a social environment, Abnormal mental and psychological conditions have become an unavoidable health problem for the whole society. Due to the improvement of material life, people pay more and more attention to mental health, how to detect the abnormality of mental and psychological state early has become an urgent problem to be solved. [0003] At present, the evaluation of a person's mental and psychological state mainly relies on some psychological scales (self-evaluation scale or other evaluation scale). According to the score ...

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Problems solved by technology

[0003] At present, the evaluation of a person's mental and psychological state mainly relies on some psychological scales (self-evaluation scale or other evaluation scale). According to the score of the scale, the mental and psychological state of the person is evaluated, and there is a lack of specific physiological conditions. indicators for evaluation

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