Tristimania diagnosis system and method based on attention and emotion information fusion

Abstract

The invention provides a tristimania diagnosis system and method based on attention and emotion information fusion. The system comprises an emotion stimulating module, an image collecting module, a data transmission module, a data pre-processing module, a data processing module, a feature extraction module and an identification feedback module, wherein the emotion stimulating module is used for setting a plurality of emotion stimulating tasks and providing the emotion stimulating tasks to a subject; the image collecting module is used for collecting eye images and face images of the subject in the emotion stimulating task performing process; the data transmission module is used for obtaining and sending the eye images and the face images; the data pre-processing module is used for pre-processing the eye images and the face images; the data processing module is used for calculating the attention point position and the pupil diameter of the subject; the feature extraction module is used for extracting attention type features and emotion type features; and the identification feedback module is used for performing tristimania diagnosis and identification on the subject. The system and the method have the advantage that the tristimania can be comprehensively, systematically and quantificationally identified by using the attention point center distance features, the attention deviation score features, the emotion zone width and the face expression features.

Description

technical field [0001] The invention relates to the technical fields of image processing, biological feature extraction, and pattern recognition, in particular to a system and method for diagnosing depression based on fusion of attention and emotion information. Background technique [0002] At present, the most extensive diagnostic criteria for depression is the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV), and the diagnosis of depression is limited to clinical symptoms, and its diagnosis is mainly based on the experience of psychiatrists and related depression. depression scale, but the scoring results of the depression scale cannot accurately reflect the patient's psychological state, and the patient may have subjective concealment, and the diagnosis result is often affected by the doctor's own subjective factors and actual clinical experience. On the one hand, there is a lack of quantitative diagnostic indicators and a reliable and...

AI Technical Summary

Problems solved by technology

[0002] Currently, the most extensive diagnostic criteria for depression is the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV), and the diagnosis of depression is limited to clinical symptoms, and its diagnosis is mainly based on the experience of psychiatrists and related depression. Depression Scale, but the scoring results of the Depression Scale cannot accurately reflect the psychological state of the patient, the patient may have subjective concealment, and the diagnosis result is often affected by the doctor's own subjective factors and actual clinical experience, and in the diagnosis of depression On the one hand, there is a lack of quantitative diagnostic indicators and a reliable and efficient diagnostic system. The problems of low diagnostic efficiency, high misdiagnosis rate, and high resource consumption have not been resolved.

Images