Mental health state assessment system and method based on mobile equipment using behavior

Abstract

The invention provides a mental health state assessment system and method based on mobile equipment using behavior. The system comprises an information recording module, a behavior extracting module, an assessment model establishing module and an assessment module. The information recording module is used for recording and storing the using information of intelligent mobile equipment. The behavior extracting module is used for carrying out data preprocessing on recorded equipment using information, effective equipment using behavior for interaction between a user and equipment is extracted, and equipment using behavior features are mined. The assessment model establishing module is used for establishing a mental health state assessment model based on the relation between the intelligent mobile equipment using behavior features and mental health states obtained with a machine learning method. The assessment module is used for inputting the mined equipment using behavior features into the mental health state assessment model, and a mental health state assessment result is obtained.

Description

technical field [0001] The present invention relates to a mental health state evaluation technology, and more specifically, to a mental health state evaluation system and method based on the use behavior of an intelligent mobile device. The system and method use logs for mental health state evaluation. Background technique [0002] At present, in the world, mental health problems have become the primary cause of individual "disability", and its negative consequences account for 37% of all disease hazards. Combined with its "global", " According to the development trend of "chronic" and "prevalent", the existence of mental health problems will not only cause huge consumption and waste of social resources, increase the burden on the whole society, but also directly threaten the health of individuals. Quality of daily life and subjective well-being. [0003] Specific to the actual situation in our country, according to the survey and research results, the overall level of peop...

AI Technical Summary

Problems solved by technology

Although some of the subjective bias factors can be checked through some control methods (such as validity scales or experimental design), it is very cumbersome and inefficient to repeatedly implement similar controls in similar studies, and some invalid data (such as wrong answers) cannot be ruled out. , missing or blind answer)

[0007] In addition, the data collected by the "questionnaire" technique is limited in detail and size

First of all, due to the constraints of time and space and some social conditions, it is difficult to recruit a sufficient number of individuals to fill in the scale for each experiment, and it is also difficult to track and measure the same group of individuals

Secondly, in order to facilitate individuals to complete the survey, it is impossible to design a large number of items on the scale, so that more details of individual behavior samples cannot be collected

In addition, the distribution, collection and entry of scales have also brought adverse effects on large-scale data collection.

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