Anxiety trait quantification method based on multi-dimensional internal perception features

Abstract

The invention relates to the technical field of electronic informatization of biological indexes, in particular to an anxiety trait quantification method based on multi-dimensional internal perceptionfeatures. The anxiety trait quantification method comprises the following steps: obtaining multi-dimensional data of tested ethology, electroencephalogram physiology and nuclear magnetic resonance image; preprocessing ethological heartbeat perception sensitivity, heartbeat consciousness potential, brain structure and task state data; and constructing a multi-dimensional deep learning network andestablishing an automatic quantization system. The multi-dimensional features of ecology, electroencephalogram physiology and nuclear magnetic resonance image under an internal perception normal formare combined, feature learning is carried out through deep network learning by means of automatic learning and nonlinear hierarchical system advantages, feature value extraction modeling is carried out, individualized anxiety trait level scoring results are obtained, a tool is provided for quantitatively and objectively evaluating the anxiety trait level, the anxiety level is accurately quantified, the anxiety disorder can be effectively recognized in the ultra-early stage, the biological objective diagnosis effect is huge, and diagnosis and treatment of the anxiety disorder can be assisted.

Description

technical field [0001] The invention relates to the technical field of electronic informationization of biological indicators, in particular to a method for quantifying anxiety traits based on multi-dimensional inner perception features. Background technique [0002] Anxiety disorder (AD) has the highest prevalence among mental disorders, reaching 5.0% in December and 7.6% in lifetime. Anxiety disorders are not only the most common and affect many people, but also have a considerable degree of functional impairment, directly affecting the patient's work ability and social function. [0003] People with high anxiety traits have an increased risk of developing anxiety disorders, and multiple studies have shown that the prognosis of comorbid anxiety with mental disorders is worse. Existing technologies rely on the answers to subjective questions to judge whether a person has anxiety. This judgment method is highly subjective, and it is impossible to accurately and objectively ...

AI Technical Summary

Problems solved by technology

[0003] People with high anxiety traits have an increased risk of developing anxiety disorders, and multiple studies have shown that the prognosis of anxiety with psychiatric disorders is worse

Existing technologies rely on the a

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