Intelligent dynamic mental health assessment method

Abstract

The invention relates to the field of chip fixtures, in particular to an intelligent dynamic psychological health assessment method, which provides comprehensive and accurate psychological health assessment for individuals by monitoring and analyzing physiological, psychological and behavioral characteristics of the individuals in real time. The method has real-time performance, comprehensiveness, accuracy and individuation, the mental health state of an individual can be monitored in real time, and psychological problems can be found and intervened in time; data in multiple aspects of physiology, psychology, behaviors and the like are combined, and the psychological health condition of an individual is comprehensively evaluated; machine learning and artificial intelligence algorithms are adopted, so that the accuracy and reliability of an evaluation result are improved; personalized intervention suggestions and rehabilitation training are provided according to individual requirements and evaluation results.

Description

Technical Field

[0001] The invention relates to the field of dynamic data and mental health assessment technology, and in particular to an intelligent dynamic mental health assessment method. Background Art

[0002] Mental health refers to all aspects of the mind and the process of activities being in a good or normal state, being able to maintain good communication or cooperation with others in social, production, and life, and being able to deal with various situations in life well. The ideal state of mental health is to maintain a good character, normal intelligence, correct cognition, appropriate emotions, reasonable will, positive attitude, appropriate behavior, and good adaptation. At present, people's mental health is a top priority. At present, under high-intensity and high-pressure work, nurses often suffer from mental health. Mental health is an increasingly concerned global issue that affects people's daily life and work performance. In order to improve people's mental health level and detect and intervene in psychological problems early, the current mental health assessment method can only perform simple assessments but cannot provide targeted help. It is impossible to provide individuals with comprehensive and accurate mental health assessments based on multiple aspects of the individual. Therefore, it is necessary to propose an intelligent dynamic mental health assessment method. Summary of the invention

[0003] In view of the problems in the prior art, the present invention provides a method for intelligent dynamic mental health assessment.

[0004] The technical solution adopted by the present invention to solve its technical problems is: a method for intelligent dynamic mental health assessment, including a mental health assessment system, the mental health assessment system including a data acquisition module, a data analysis and processing module and a dynamic assessment and intervention module, the data acquisition module including a physiological data module, a psychological data module and a behavioral data module; the data analysis and processing module including a time series analysis module of physiological indicators, a statistical analysis module of psychological indicators and a classification and clustering analysis module of behavioral data; the dynamic assessment and intervention module including a psychological education module and a rehabilitation training module.

[0005] The data acquisition module uses a variety of sensors and devices for data collection, including smart watches, smart phones, physiological sensors, etc. The physiological data module collects individual physiological indicators such as body temperature, heart rate, blood pressure, and blood oxygen saturation through sensors; the psychological data module collects individual psychological states such as emotions, cognition, and stress through psychological tests and questionnaires; the behavioral data module collects individual geographic location, movement trajectory, living habits and other behavioral information through mobile phone GPS, motion sensors and other devices. At the same time, the collected data is transmitted to the server through a wireless network, and encryption technology is used to ensure the security of data transmission. On the server side, data is stored in a dedicated database to ensure the integrity and traceability of the data, and distributed storage technology is used to improve the reliability and scalability of data storage.

[0006] The data analysis and processing module pre-processes the collected data, including data cleaning, denoising, feature extraction and other operations, and then uses machine learning and artificial intelligence algorithms to analyze the data and extract the individual's mental health characteristics. The physiological indicator timing analysis module uses time series analysis methods to study the changing patterns and trends of physiological indicators; the psychological indicator statistical analysis module uses descriptive statistics and correlation analysis to explore the relationship between psychological indicators; the behavioral data classification and clustering analysis module uses classification and clustering algorithms to identify individual behavioral patterns and abnormal behaviors.

[0007] The dynamic assessment and intervention module dynamically establishes an individual's dynamic mental health assessment model based on the results of data processing and analysis. The model can monitor the individual's mental health status in real time and provide personalized intervention suggestions based on the assessment results. The psychological education module provides mental health knowledge education and psychological skills training online or offline; provides professional psychological counseling services, including online chat, telephone consultation, etc.; the rehabilitation training module recommends rehabilitation training suitable for individuals, such as yoga, meditation, etc.

[0008] The data analysis and processing module includes a variety of data processing and analysis algorithms, including time series analysis, statistical analysis and machine learning algorithms. The time series analysis is used to explore the dynamic change patterns of physiological data, the statistical analysis is used to reveal the relationship between psychological indicators, and the machine learning algorithm is used to build a dynamic evaluation model and a behavior recognition model. By continuously optimizing the algorithm, the accuracy and real-time performance of the evaluation are improved.

[0009] The dynamic assessment and intervention module uses a dynamic assessment model to conduct real-time assessment of the individual's mental health status based on real-time data and historical data. The assessment results are used to generate personalized intervention suggestions, which are pushed to the individual through smart terminal devices. The intervention strategies include psychological education, psychological counseling, rehabilitation training and other forms, which are adjusted according to the individual's needs and assessment results.

[0010] In order to achieve real-time data collection, the sensor in the acquisition module adopts high-precision physiological sensors to ensure the accuracy and stability of the data. Sensors built into devices such as smart watches and smartphones are also used to collect motion data and location information. All sensors are strictly calibrated and tested to ensure the reliability and validity of the data.

[0011] A method for using an intelligent dynamic mental health assessment method comprises the following steps: Step 1: When it is necessary to use the mental health assessment system to conduct a mental health assessment on the patient, the user's physiological data, psychological data and behavioral data are collected through the sensors of the data acquisition module and the user's smart device; Step 2: Preprocess and extract features of the data collected by the user through the physiological index time series analysis module, the psychological index statistical analysis module and the behavioral data classification and cluster analysis module in the data analysis and processing module, analyze the data using machine learning algorithms, and establish a dynamic assessment model for the user's mental health in conjunction with time series analysis and statistical analysis methods, and measure the user's current psychological condition based on the assessment results; Step 3: At this time, through dynamic evaluation, the psychological education module in the intervention module provides mental health knowledge education and psychological skills training online or offline, and provides professional psychological counseling services, including online chat, telephone consultation, etc. Through the rehabilitation training module, it recommends individuals to carry out rehabilitation training suitable for themselves, thereby increasing the overall treatment efficiency.

[0012] Beneficial effects of the present invention: The method of intelligent dynamic mental health assessment described in the present invention provides a comprehensive and accurate mental health assessment for an individual by real-time monitoring and analyzing the individual's physiological, psychological and behavioral characteristics. The method combines modern scientific and technological means with artificial intelligence algorithms, and is real-time, comprehensive, accurate and personalized. The method can monitor the individual's mental health status in real time, and promptly discover and intervene in psychological problems; it combines data from multiple aspects such as physiology, psychology and behavior to comprehensively assess the individual's mental health status; it uses machine learning and artificial intelligence algorithms to improve the accuracy and reliability of the assessment results; and it provides personalized intervention suggestions and rehabilitation training based on the individual's needs and assessment results. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0014] Figure 1 A schematic diagram of the structure of a method for intelligent dynamic mental health assessment provided by the present invention; Figure 2A structural schematic diagram of a data acquisition module in a method for intelligent dynamic mental health assessment provided by the present invention; Figure 3 A schematic diagram of the flow structure of a data analysis and processing module in a method for intelligent dynamic mental health assessment provided by the present invention; Figure 4 A schematic diagram of the process structure of a dynamic assessment and intervention module in a method for intelligent dynamic mental health assessment provided by the present invention. DETAILED DESCRIPTION

[0015] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.

[0016] like Figure 1-Figure 4As shown, an intelligent dynamic mental health assessment method of the present invention includes a mental health assessment system, which includes a data acquisition module, a data analysis and processing module, and a dynamic assessment and intervention module. The data acquisition module includes a physiological data module, a psychological data module, and a behavioral data module; the data analysis and processing module includes a time series analysis module of physiological indicators, a statistical analysis module of psychological indicators, and a classification and clustering analysis module of behavioral data; the dynamic assessment and intervention module includes a psychological education module and a rehabilitation training module; the data acquisition module uses a variety of sensors and devices for data acquisition, including smart watches, smart phones, physiological sensors, etc., and the physiological data module collects individual physiological indicators such as body temperature, heart rate, blood pressure, and blood oxygen saturation through sensors; the psychological data module collects individual psychological states such as emotions, cognition, and stress through psychological tests, questionnaires, etc.; the behavioral data module collects individual geographic location, movement trajectory, living habits, and other behavioral information through mobile phone GPS, motion sensors, and other devices. At the same time, the collected data is transmitted to the server through a wireless network, and encryption technology is used to ensure the security of data transmission. On the server side, data is stored in a dedicated database to ensure data integrity and traceability, and distributed storage technology is used to improve the reliability and scalability of data storage. The data analysis and processing module pre-processes the collected data, including data cleaning, denoising, feature extraction and other operations, and then uses machine learning and artificial intelligence algorithms to analyze the data and extract individual mental health characteristics. The time series analysis module of physiological indicators uses time series analysis methods to study the changing patterns and trends of physiological indicators. The statistical analysis module of psychological indicators uses descriptive statistics and correlation analysis to explore the relationship between psychological indicators. The classification and clustering analysis module of behavioral data uses classification and clustering algorithms to identify individual behavior patterns and abnormal behaviors. The dynamic assessment and intervention module dynamically establishes an individual's mental health dynamic assessment model based on the results of data processing and analysis. The model can monitor the individual's mental health status in real time and provide personalized intervention suggestions based on the assessment results. The psychological education module provides mental health knowledge education and psychological skills training through online or offline methods; provides professional psychological counseling services, including online chat, telephone consultation, etc. The rehabilitation training module recommends individuals to conduct rehabilitation training suitable for themselves, such as yoga, meditation, etc.

[0017] The data analysis and processing module has a variety of data processing and analysis algorithms, including time series analysis, statistical analysis and machine learning algorithms. Time series analysis is used to mine the dynamic change rules of physiological data, statistical analysis is used to reveal the relationship between psychological indicators, and machine learning algorithms are used to build dynamic evaluation models and behavior recognition models. By continuously optimizing the algorithm, the accuracy and real-time performance of the evaluation are improved; the dynamic evaluation and intervention module uses a dynamic evaluation model to conduct real-time evaluation of the individual's mental health status based on real-time data and historical data. The evaluation results are used to generate personalized intervention suggestions, which are pushed to individuals through smart terminal devices. Intervention strategies include psychological education, psychological counseling, rehabilitation training and other forms, which are adjusted according to individual needs and evaluation results; sensors in the acquisition module In order to achieve real-time data collection, this method uses high-precision physiological sensors to ensure the accuracy and stability of the data. Sensors built into devices such as smart watches and smart phones are also used to collect motion data and location information. All sensors are strictly calibrated and tested to ensure the reliability and validity of the data.

[0018] Specific use: When it is necessary to use the mental health assessment system to conduct a mental health assessment on the patient, the user's physiological data, psychological data and behavioral data are collected through the sensors of the data acquisition module in conjunction with the user's smart device; the data collected by the user are preprocessed and feature extracted through the time series analysis module of physiological indicators, the statistical analysis module of psychological indicators and the classification and clustering analysis module of behavioral data in the data analysis and processing module, and the data is analyzed using a machine learning algorithm. At the same time, a dynamic mental health assessment model for the user is established in conjunction with the time series analysis and statistical analysis methods, and the user's current psychological condition is measured based on the assessment results; at this time, the psychological education module in the dynamic assessment intervention module provides mental health knowledge education and psychological skills training online or offline, and provides professional psychological counseling services, including online chat, telephone consultation, etc. The rehabilitation training module recommends individuals to conduct rehabilitation training suitable for themselves to increase the overall treatment efficiency.

[0019] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for intelligent dynamic mental health assessment, characterized in that: It comprises a mental health assessment system, which comprises a data acquisition module, a data analysis and processing module and a dynamic assessment and intervention module. The data acquisition module comprises a physiological data module, a psychological data module and a behavioral data module; the data analysis and processing module comprises a time series analysis module of physiological indicators, a statistical analysis module of psychological indicators and a classification and clustering analysis module of behavioral data; the dynamic assessment and intervention module comprises a psychological education module and a rehabilitation training module.

2. The method of intelligent dynamic mental health assessment according to claim 1, characterized in that: The data acquisition module uses a variety of sensors and devices to collect data, including smart watches, smart phones, physiological sensors, etc.

3. The method of intelligent dynamic mental health assessment according to claim 1, characterized in that: The data analysis and processing module pre-processes the collected data, including data cleaning, denoising, feature extraction and other operations, and then uses machine learning and artificial intelligence algorithms to analyze the data and extract individual mental health characteristics.

4. The method of intelligent dynamic mental health assessment according to claim 1, characterized in that: The dynamic assessment and intervention module dynamically establishes an individual's mental health dynamic assessment model based on the results of data processing and analysis. The model can monitor the individual's mental health status in real time and provide personalized intervention suggestions based on the assessment results.

5. The method of intelligent dynamic mental health assessment according to claim 1, characterized in that: The data analysis and processing module includes a variety of data processing and analysis algorithms, including time series analysis, statistical analysis and machine learning algorithms.

6. The method of intelligent dynamic mental health assessment according to claim 1, characterized in that: The dynamic assessment and intervention module uses a dynamic assessment model to conduct real-time assessment of the individual's mental health status based on real-time data and historical data. The assessment results are used to generate personalized intervention suggestions, which are pushed to the individual through smart terminal devices. The intervention strategies include psychological education, psychological counseling, rehabilitation training and other forms, which are adjusted according to the individual's needs and assessment results.

7. The method of intelligent dynamic mental health assessment according to claim 1, characterized in that: In order to realize real-time data collection, the sensor in the acquisition module adopts high-precision physiological sensors to ensure the accuracy and stability of the data.

8. A method for using the intelligent dynamic mental health assessment method according to any one of claims 1 to 7, characterized in that: The following steps are involved: Step 1: When it is necessary to use the mental health assessment system to conduct a mental health assessment on the patient, the user's physiological data, psychological data and behavioral data are collected through the sensors of the data acquisition module and the user's smart device; Step 2: Preprocess and extract features of the data collected by the user through the physiological index time series analysis module, the psychological index statistical analysis module and the behavioral data classification and cluster analysis module in the data analysis and processing module, analyze the data using machine learning algorithms, and establish a dynamic assessment model for the user's mental health in conjunction with time series analysis and statistical analysis methods, and measure the user's current psychological condition based on the assessment results; Step 3: At this time, through dynamic evaluation, the psychological education module in the intervention module provides mental health knowledge education and psychological skills training online or offline, and provides professional psychological counseling services, including online chat, telephone consultation, etc. Through the rehabilitation training module, it recommends individuals to carry out rehabilitation training suitable for themselves, thereby increasing the overall treatment efficiency.

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