TWM605592U - Action emotional care system based on cognitive behavioral technology and emotional analysis - Google Patents

Abstract

This creation is about a kind of behavioral emotional care system based on cognitive behavioral technology and emotional analysis. It is mainly based on the built-in smart mood sharing module, life bit recording module, interactive evaluation module, and personalized emotion in the mobile device. Analysis module, online consultation appointment module, social website module, and all modules are connected to the server, and the server is connected to the vocabulary database required for sentiment analysis; by this, the machine can be used Learning and emotional analysis technology to develop interactive personalized emotional care functions to help users do a good job in personal daily self-emotion management and care, to achieve the action-oriented and personalized application assistance of emotional management information, and it is more effective in its overall implementation. Those who increase practical functional characteristics.

Description

Action emotional care system based on cognitive behavioral technology and emotional analysis

This creation department is about a kind of behavioral emotional care system based on cognitive behavioral technology and emotional analysis, in particular, it refers to the use of machine learning and emotional analysis technology to develop interactive personal emotional care functions to help users do their daily self. Emotion management and care efficiency, to achieve the mobile and personal application assistance of emotional management information, and in its overall implementation, it is an innovative designer of the behavioral emotional care system based on cognitive behavioral technology and emotional analysis with more practical features.

According to statistics from the World Health Organization, the risk of mental illness is rising all over the world, among which the most common anxiety and depression are plagued by about 120 million people worldwide. With the rapid development of modern society, the pressure from society, work, and schoolwork is increasing. It's like a disease of civilization. The latest information shows that the number one killer of mankind in the 21st century is mental health. In particular, the recent spread of the novel coronavirus disease [COVID-19] has caused physical and psychological stress on people or caused many people to be in a state of emotional tension due to factors such as epidemic prevention social distance or isolation. Without proper care and management, it may cause psychological problems. Health issues.

In particular, mental health problems are becoming more and more serious among young people. The rate and severity are also increasing. Although people are paying more and more attention to mental health issues, less than a quarter of young people seek professional treatment.

The rapid development of information technology, especially the rapid development of the innovative functions of smart phones, the use of mobile mental health care system can provide users with the effect of self-care anytime and anywhere, the popularity and use of smart phones is increasing, through mobile health care [mHealth] Promote the effectiveness of mental health care. The advantages of mobile health care include continuous availability, more extensive information search, fair mental health resource sharing, instant service support, anonymous privacy protection, tailor-made personalized content, lower cost and efficient transmission The service capacity of the company can effectively enhance personalized health care. Therefore, the establishment of a mobile emotional care system is expected to improve personal emotional management capabilities and improve the mental health and well-being of users.

The reason is that, in view of this, the creators uphold the professional capabilities of machine learning and natural language processing emotion analysis technology, as well as the rich design development and practical production experience in the related industry for many years, and research and improve the existing structure and deficiencies to provide a cognitive Behavioral technology and emotional analysis based action emotional care system, in order to achieve the purpose of better practical value.

The main purpose of this creation is to provide a behavioral emotional care system based on cognitive behavioral technology and emotional analysis. It mainly uses machine learning and emotional analysis technology to develop interactive and personalized emotional care functions to help users do their own daily routines. Self-emotion management and care efficiency, to achieve the mobile and personal application of emotional management information Assist, and increase practicality and intelligent service characteristics in its overall implementation.

The main purpose and effect of this creative cognitive behavioral technology and emotional analysis-based action emotional care system are achieved by the following specific technical means:

It mainly includes mobile devices and servers; among them:

The mobile device has a built-in smart mood sharing module, life recording module, interactive evaluation module, personalized mood analysis module, online consultation appointment module, social website module, and each module Are connected to the server;

The intelligent mood sharing module uses sentiment analysis technology and natural language processing unit to capture the emotional vocabulary in the mood story shared by the user through the mood sharing interface, and further uses sentiment analysis technology and Bayesian reasoning to extract the emotional vocabulary, and then The previously trained vocabulary stored in the database is compared and analyzed for positive and negative emotional tendency indicators, which can record the user's emotional history and recommend appropriate health education information to the user;

In the life-by-bit recording module, the user records important personal emotional index data through the life-by-bit recording module, and through the calendar function interface, the user can record and query his personal emotional history record;

The interactive evaluation module uses a scale that can measure the depressive tendency of the testee, and is aimed at the online test of the user to easily measure the personal mental health status;

The personalized emotion analysis module records the user’s daily emotional history and generates chart analysis, which can provide users with emotional health care and psychologists for diagnosis and treatment. test;

The online consultation and appointment module provides users with information about related consulting institutions and clinics, and can make appointments and consultations online;

The community website module, which provides users with emotional management health education information, for querying health education information, and sharing and expressing emotions through community sharing and discussion;

The server is respectively linked with a database and a natural language processing (NLP) unit, and the database stores the vocabulary required for sentiment analysis.

This is a preferred embodiment of an action emotional care system based on creative cognitive behavioral technology and emotional analysis, wherein the intelligent mood sharing module first uses Python programming language to write text analysis, and segment the emotional stories shared by users. Sentences are segmented and emotional vocabulary is extracted, and then vocabulary training is performed through the Naive Bayes classifier and stored in the database.

The present invention is a preferred embodiment of a behavioral emotional care system based on cognitive behavioral technology and emotional analysis, wherein the interactive evaluation module uses the anxiety self-assessment scale [The Patient Health Questionnaire-9, PHQ-9]. The health questionnaire is a scale designed based on the DSM-IV diagnosis, which measures the subject’s depression tendency with a level of reliability and validity.

1: mobile device

11: Smart Mood Sharing Module

12: Life recording module

13: Interactive assessment module

14: Personalized sentiment analysis module

15: Online consultation appointment module

16: Community website module

2: server

21: Database

22: Natural language processing unit

Figure 1: Schematic diagram of the system architecture of this creation

In order to have a more complete and clear disclosure of the technical content, the purpose of creation and the effect achieved in this creation, we will explain them in detail below, and please refer to the figures and figure numbers disclosed together:

First of all, please refer to the system architecture diagram of this author in the first figure. This author mainly includes mobile devices (1) and servers (2); among them:

The mobile device (1) has built-in smart mood sharing module (11), life recording module (12), interactive evaluation module (13), personalized emotion analysis module (14), and online consultation Make reservation module (15), social website module (16), and make each module connect to the server (2);

The smart mood sharing module (11) uses Python programming language to write text analysis, segmentation, sentence segmentation and emotional vocabulary extraction for the mood stories shared by users, and then vocabulary training is carried out through the Naive Bayes classifier. It is stored in the database (21) to capture the emotion vocabulary in the mood story shared by the user through the emotion sharing interface through emotion analysis technology and natural language processing unit, and further use emotion analysis technology and Bayesian reasoning Extract emotional vocabulary, compare it with the previously trained vocabulary stored in the database (21), analyze positive and negative emotional tendency indicators, record the user's emotional history, and recommend appropriate health education messages for use By.

In the life bit recording module (12), the user records important personal emotional index data through the life bit recording module (12), and through the calendar function interface, the user can record and query his personal emotional history record.

The interactive assessment module (13) uses the anxiety self-assessment scale [The Patient Health Questionnaire-9, PHQ-9], which is a scale designed based on the DSM-IV diagnosis. Reliability and validity are used to measure the subject’s depression tendency, and online testing for users can easily measure personal mental health.

The personalized emotion analysis module (14) records the user's daily emotional history and generates chart analysis, which can provide users with emotional health care and psychologists for diagnosis and treatment.

The online consultation and appointment module (15) provides users with inquiries about relevant consulting agencies and clinics, and can make appointments and consultations online.

The community website module (16) provides users with emotional management health education information for inquiring about health education information, and sharing and expressing emotions through community sharing and discussion.

The server (2) is respectively connected with a database (21) and a natural language processing [NLP] unit (22), and the database (21) stores the vocabulary required for sentiment analysis.

In this way, the author can be used for operation, and users can use the built-in smart mood sharing module (11), life recording module (12), and interactive evaluation module of the mobile device (1) (13), Personalized emotion analysis module (14), online consultation appointment module (15), social website module (16) are connected to the server (2), and the server (2) is connected with emotion Analyze the required vocabulary database. In addition, the online consultation appointment module (15) can provide users with inquiries about relevant consulting agencies and clinic information, and use the online consultation appointment module (15) to allow users to relate when necessary The clinic makes real-time appointments and consultations online, To achieve the mobile and personal application assistance of emotional management information.

Based on the above, the use and implementation instructions of this creation show that, compared with the existing technical means, this creation mainly uses machine learning and emotion analysis technology to develop interactive personal emotional care functions to help users To do a good job in personal daily self-emotion management and care efficiency, to achieve the mobile and personal application assistance of emotional management information, and to increase the practical function characteristics in its overall implementation.

The foregoing embodiments or drawings do not limit the structure of this creation, and any appropriate changes or modifications by those with ordinary knowledge in the technical field should be regarded as not departing from the scope of the patent of this creation.

In summary, this creative embodiment can indeed achieve the expected use effect, and the specific structure disclosed by it has not been seen in similar products, nor has it been disclosed before the application. It is sincerely in full compliance with the provisions and requirements of the Patent Law. , Yan submits an application for a new patent in accordance with the law, and asks for favors for examination and grants a patent.

1: mobile device

11: Smart Mood Sharing Module

12: Life recording module

13: Interactive assessment module

14: Personalized sentiment analysis module

15: Online consultation appointment module

16: Community website module

2: server

21: Database

22: Natural language processing unit

Claims (3)

A mobile emotional care system based on cognitive behavioral technology and emotional analysis, which mainly includes mobile devices and servers; among them: The mobile device has a built-in smart mood sharing module, life recording module, interactive evaluation module, personalized mood analysis module, online consultation appointment module, social website module, and each module Are connected to the server; The intelligent mood sharing module uses sentiment analysis technology and natural language processing unit to capture the emotional vocabulary in the mood story shared by the user through the mood sharing interface, and further uses sentiment analysis technology and Bayesian reasoning to extract the emotional vocabulary, and then The previously trained vocabulary stored in the database is compared and analyzed for positive and negative emotional tendency indicators, which can record the user's emotional history and recommend appropriate health education information to the user; In the life-by-bit recording module, the user records important personal emotional index data through the life-by-bit recording module, and through the calendar function interface, the user can record and query his personal emotional history record; The interactive evaluation module uses a scale that can measure the depressive tendency of the testee, and is aimed at the online test of the user to easily measure the personal mental health status; The personalized emotion analysis module records the user's daily emotional history and generates chart analysis, which can provide users with emotional health care and psychologists for diagnosis and treatment; The online consultation and appointment module provides users with information about related consulting institutions and clinics, and can make appointments and consultations online; The community website module, which provides users with emotional management health education information, for querying health education information, and sharing and expressing emotions through community sharing and discussion; The server is respectively linked with a database and a natural language processing (NLP) unit, and the database stores the vocabulary required for sentiment analysis. The behavioral emotional care system based on cognitive behavioral technology and emotional analysis as described in claim 1, wherein the smart mood sharing module first uses Python programming language to write text analysis, and segment the emotional stories shared by users. The emotional vocabulary is extracted, and then the vocabulary is trained through the Naive Bayes classifier and stored in the database. The behavioral emotional care system based on cognitive behavioral technology and emotional analysis as described in claim 1, wherein the interactive evaluation module uses the anxiety self-evaluation scale [The Patient Health Questionnaire-9, PHQ-9], and the health The questionnaire is a scale designed based on the diagnosis of DSM-IV, which measures the subject’s depression tendency with a level of reliability and validity.

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