Mental health evaluation system based on Internet

Abstract

The invention relates to a mental health evaluation system based on an Internet. The system comprises the following steps: establishing and training a RBF neural network evaluation model based on the factor score of a mental test scale in a known sample stored in a cloud database by use of a RBF neural network algorithm; and acquiring the factor score of the mental test scale of a new individual, and obtaining a mental health state evaluation result of the new individual according to the RBF neural network evaluation model. The RBE neural network estimation model has good accuracy and adaptability to the evaluation of the mental health state, is small in error and good in fitting; the mental health result and therapeutic schedule obtained by use of the mental health evaluation system of the application are more precise and reliable.

Description

technical field [0001] The invention relates to the technical field of mental health state evaluation, in particular to an Internet-based mental health evaluation system. Background technique [0002] With the development of social economy and the improvement of human living standards, people's demand for health is also constantly increasing. The concept of health has surpassed the era of "disease-free" and entered the era of physical and mental health and high-quality life. Mental health, It is an inseparable important aspect of modern people's health. Mental health mainly refers to normal spirit, normal activities, and good psychological quality. Modern people's material life is relatively comfortable, but they are under great mental and psychological pressure. Mental health problems are increasingly becoming the health problems of modern people. Therefore, how to quickly, accurately and comprehensively assess an individual's physical and mental health needs to be studied ...

AI Technical Summary

Problems solved by technology

However, mental health assessment and psychological problem identification are inherently pattern recognition or non-linear classification problems

The psychological state of each independent individual is a multi-dimensional information system, whose basic characteristics are multi-variable, multi-level, and strong coupling. There are complex nonlinear interactions among various factors within the system. Therefore, it is difficult to describe it with traditional mathematical methods.

Radial basis (RBF) neural network is an artificial neural network that uses local receptive fields to perform function mapping based on the knowledge of biological local adjustment and overlapping receptive regions. Its basic idea is: use radial basis function As the "base" of the hidden unit, the hidden layer constitutes the hidden layer space to transform the input vector, and transforms the low-dimensional pattern input data into the high-dimensional space, so that the problem of linear inseparability in the low-dimensional space can be solved in the high-dimensional space The inner line can be divided, Chinese Journal of Clinical Psychology, Volume 19, Issue 6, 2011, a document by Xi Xiaolan et al. (Neural Network-based Mental Health Assessment Model for College Students) reported the application of artificial neural network technology to the psychological assessment of college students Modeling, and established RBF neural network and BP neural network models respectively, to evaluate the mental health status of college students, and analyzed that RBF neural network has better accuracy and adaptability than BP neural network modeling, but the literature does not The combination of RBF neural network and Internet cloud technology is not disclosed, the factor scores of the psychological test scale in known samples are not disclosed based on cloud storage, and the specific evaluation method of neural network for mental health is not disclosed. The focus of this document is It lies in the establishment and comparison of two neural network models

Patent document CN104835103 discloses a mobile network health evaluation method based on neural network and fuzzy comprehensive evaluation. It discloses that the method includes steps such as establishing an evaluation system, establishing and training a BP neural network model, and testing the BP network model for health evaluation. However, This evaluation method is applied to mobile network health evaluation, and it is not a health evaluation method that combines neural network and Internet cloud technology. Patent US2005 / 0236004A1 discloses a monitoring method for human health status, in which a nonlinear input vector The module contains a neural network, but it is also not a combination of neural network and Internet cloud technology for the assessment of mental health

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