CN116453656B - Psychological health assessment early warning system and psychological health assessment early warning method - Google Patents
Psychological health assessment early warning system and psychological health assessment early warning method Download PDFInfo
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Abstract
The invention discloses a psychological health assessment early warning system and a psychological health assessment early warning method, which relate to the technical field of psychological assessment, wherein the method comprises the following steps: and (3) carrying out psychological health assessment test on the target user by adopting an assessment problem to obtain a plurality of test results, collecting physiological parameters of the target user in the test process, carrying out tension degree analysis to obtain a plurality of tension degree analysis results, respectively judging whether the tension degree analysis results are larger than a preset tension degree threshold, carrying out early warning if the ratio of the unqualified tension degree analysis results is larger than a preset proportion threshold, or otherwise determining an assessment mode according to the qualified tension degree analysis results, inputting the assessment mode into a corresponding psychological health assessment model to obtain a psychological health assessment result, and carrying out early warning when the psychological health assessment result is unqualified. The invention solves the technical problem of low accuracy of the evaluation result due to single psychological health evaluation method in the prior art, and achieves the technical effect of improving the accuracy of the psychological health evaluation result.
Description
Technical Field
The invention relates to the technical field of psychological assessment, in particular to a psychological health assessment early warning system and method.
Background
With the development of society and the improvement of living standard, the public increasingly pays attention to psychological health problems. The current psychological assessment demands are quite large, but the development and application of psychological assessment are hindered by various limitations in the aspects of theoretical basis, implementation mode and the like, a plurality of classical scales are often tested on a testee during psychological assessment so as to comprehensively assess the psychological development condition of an individual, the capacity of the testee is obtained through accumulation of simple scores without considering factors such as question difficulty, distinction degree and the like, the formulation of measurement statistical indexes depends on sampling variation, sampling deviation, sampling sample size and the like, and the accuracy and the assessment efficiency of the measurement scale are easily influenced due to various limitations.
From the evaluation result, the current mental health evaluation also has the technical problem that the accuracy of the evaluation result is not high because the mental health evaluation method is single.
Disclosure of Invention
The application provides a psychological health assessment early warning system and a psychological health assessment early warning method, which are used for solving the technical problem that the accuracy of assessment results is low due to the fact that the psychological health assessment method is single.
In a first aspect of the present application, there is provided a mental health assessment and early warning method, the method comprising: acquiring a plurality of evaluation questions for performing mental health evaluation on a user; testing the target user by adopting the plurality of evaluation problems to obtain a plurality of test results; respectively acquiring physiological parameters of the target user according to a physiological parameter index set in the process of testing the plurality of evaluation problems to obtain a plurality of physiological parameter sets; respectively inputting the multiple physiological parameter sets into a tension degree analysis model to obtain multiple tension degree analysis results, respectively judging whether the multiple physiological parameter sets are larger than a preset tension degree threshold value, and obtaining a plurality of unqualified tension degree analysis results and a plurality of qualified tension degree analysis results which are larger than the preset tension degree threshold value; judging whether the duty ratio of the plurality of unqualified tension degree analysis results is larger than a preset proportion threshold, if so, carrying out early warning, or if not, determining an evaluation mode according to a plurality of effective evaluation problems corresponding to the plurality of qualified tension degree analysis results; inputting the plurality of qualified tension degree analysis results into a psychological health assessment model corresponding to the assessment mode, obtaining a psychological health assessment result, and carrying out early warning when the psychological health assessment result is unqualified.
In a second aspect of the present application, there is provided a mental health assessment and early warning system, the system comprising: the evaluation problem acquisition module is used for acquiring a plurality of evaluation problems for performing mental health evaluation on the user; the test result obtaining module is used for testing the target user by adopting the plurality of evaluation problems to obtain a plurality of test results; the physiological parameter set obtaining module is used for collecting physiological parameters of the target user according to the physiological parameter index set in the process of testing the plurality of evaluation problems to obtain a plurality of physiological parameter sets; the tension degree analysis result obtaining module is used for respectively inputting the multiple physiological parameter sets into a tension degree analysis model to obtain multiple tension degree analysis results, respectively judging whether the multiple physiological parameter sets are larger than a preset tension degree threshold value or not, and obtaining a plurality of unqualified tension degree analysis results and a plurality of qualified tension degree analysis results which are larger than the preset tension degree threshold value; the evaluation mode determining module is used for judging whether the duty ratio of the plurality of unqualified tension degree analysis results is larger than a preset proportion threshold value, if so, early warning is carried out, or if not, an evaluation mode is determined according to a plurality of effective evaluation problems corresponding to the plurality of qualified tension degree analysis results; the psychological health assessment result obtaining module is used for inputting a plurality of effective test results of the plurality of effective assessment problems into the psychological health assessment model corresponding to the assessment mode by combining the plurality of qualified tension degree analysis results, obtaining a psychological health assessment result, and carrying out early warning when the psychological health assessment result is unqualified.
One or more technical schemes provided by the application have at least the following technical effects or advantages:
the application provides a psychological health assessment early warning method, which relates to the technical field of psychological health assessment, and aims at obtaining a plurality of test results by carrying out psychological health assessment test on a target user through assessment problems, and in the test process, collecting physiological parameters of the target user for tension degree analysis to obtain a plurality of tension degree analysis results, respectively judging whether the analysis results are larger than a preset tension degree threshold, if the proportion of unqualified tension degree analysis results is larger than a preset proportion threshold, carrying out early warning, or otherwise, determining an assessment mode according to qualified tension degree analysis results, inputting the assessment mode into a corresponding psychological health assessment model to obtain psychological health assessment results, and carrying out early warning when the psychological health assessment results are unqualified, thereby solving the technical problem that the accuracy of the assessment results is low due to single psychological health assessment method in the prior art, and realizing the technical effect of improving the accuracy of the psychological health assessment results.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a logic flow diagram of a mental health assessment and early warning method according to an embodiment of the present application;
fig. 2 is a schematic flow chart of a mental health assessment and early warning method according to an embodiment of the present application;
fig. 3 is a schematic flow chart of obtaining a plurality of tension analysis results in a mental health assessment and early warning method according to an embodiment of the present application;
fig. 4 is a schematic flow chart of determining an evaluation mode in a mental health evaluation early warning method according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of a mental health assessment and early warning system according to an embodiment of the present application.
Reference numerals illustrate: the system comprises an assessment problem acquisition module 11, a test result acquisition module 12, a physiological parameter set acquisition module 13, a stress analysis result acquisition module 14, an assessment mode determination module 15 and a mental health assessment result acquisition module 16.
Detailed Description
The application provides a psychological health assessment early warning method, which is used for solving the technical problem of low accuracy of assessment results caused by single psychological health assessment method in the prior art.
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. It will be apparent that the described embodiments are only some, but not all, embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
It is noted that the terms "comprises" and "comprising," and any variations thereof, in the description and claims of the present application and in the foregoing figures, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or server comprising a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or apparatus, but may include other steps or modules not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
As shown in fig. 1, the application provides a psychological health assessment and early warning method, which comprises the following steps:
s100: acquiring a plurality of evaluation questions for performing mental health evaluation on a user;
fig. 2 shows a flow chart of a mental health assessment early warning method provided by the embodiment of the application, specifically, mental health assessment is to assess aspects of cognition, emotion, behavior, tendency, potential, personality, living environment and the like of a person from a professional perspective so as to determine mental health conditions of the person.
The user refers to a crowd who may need to use the system to carry out psychological assessment test, and according to psychological health tendency and test appeal of the user, a plurality of corresponding assessment questions are extracted from a question bank, wherein the question bank comprises professional psychological test questions compiled by hospitals, psychological consultation centers and professional research institutions, and the plurality of assessment questions can be a plurality of questions or a plurality of psychological assessment questionnaires and serve as test questions for carrying out psychological tests on the user.
S200: testing the target user by adopting the plurality of evaluation problems to obtain a plurality of test results;
specifically, the target user refers to a user who currently uses the system to perform a psychological assessment test, and the psychological assessment test can be performed on the target user by using the plurality of assessment questions at a plurality of time points or in different scenes, and the psychological assessment test can be performed by the user himself or herself in a questionnaire assessment manner, or by professional psychological consultants to ask the target user, the test result of each time is recorded, and a plurality of test results obtained after a plurality of tests can be used as basic data for performing subsequent psychological health assessment.
S300: respectively acquiring physiological parameters of the target user according to a physiological parameter index set in the process of testing the plurality of evaluation problems to obtain a plurality of physiological parameter sets;
specifically, step S300 may be performed simultaneously with step S200, where the physiological parameters such as heart rate and skin temperature, which can reflect the psychological stress level of the target user, are constructed into a physiological parameter index set, and based on the physiological parameter index set, the physiological parameters of the target user are detected by using a medical instrument in the process of testing the target user by using the multiple evaluation questions, and the detection results are recorded, and finally the physiological parameter detection results in multiple tests of the target user are organized into multiple physiological parameter sets, which can be used as basic data for performing subsequent stress level analysis.
Further, step S300 of the embodiment of the present application further includes:
s310: acquiring the physiological parameter index set, wherein the physiological parameter index set comprises a heart rate index, a skin temperature index and a palm perspiration index;
s320: and in the process of each evaluation problem test, detecting the heart rate, the skin temperature and the palm perspiration degree of the target user, and obtaining the plurality of physiological parameter sets.
Specifically, because the psychological state of the person changes with some physiological reactions, such as excessive anxiety and anxiety of the anxiety patient, nervous motor tension and autonomic nerve hyperactivity may be caused, the patient may feel 24528 is uncomfortable, attention is not concentrated, and the patient may sit restless, and tension headache, tremor, and may also have symptoms such as sweating, tachycardia, shortness of breath, dizziness, dry mouth, and the like. The comprehensive indexes of heart rate, skin temperature, body temperature and perspiration are also called physiological stress indexes, are indexes for evaluating organism reactions, and can reflect the psychological stress degree of a tested person to a certain extent, so that the heart rate, skin temperature and palm perspiration degree of a target user are used as a physiological parameter index set for the heart evaluation test. And referring to the physiological parameter index collection, when the target user is subjected to evaluation problem test each time, detecting physiological parameters such as heart rate, skin temperature, palm perspiration degree and the like of the target user by using a physiological index detection instrument, and arranging the physiological parameters into a collection, wherein after the evaluation problem test is carried out for a plurality of times, a plurality of physiological parameter collections can be obtained and can be used as basic data for subsequent tension degree analysis.
S400: respectively inputting the multiple physiological parameter sets into a tension degree analysis model to obtain multiple tension degree analysis results, respectively judging whether the multiple physiological parameter sets are larger than a preset tension degree threshold value, and obtaining a plurality of unqualified tension degree analysis results and a plurality of qualified tension degree analysis results which are larger than the preset tension degree threshold value;
specifically, a stress analysis model is constructed and obtained, the physiological parameter sets are respectively input into the stress analysis model, and a plurality of stress analysis results are output after the analysis of the model. The preset tension threshold is the maximum value of the tension level which ensures that a tester can perform effective psychological assessment, for example, the tension level is divided into 1, 2, 3, 4 and 5 from low to high according to the psychological tension level of the tester, if the psychological tension level of the tester is greater than 3 levels, the tension level threshold is set to be 3 levels, the obtained multiple tension level analysis results are compared with the preset tension level threshold one by one, if the tension level is greater than the preset tension level threshold, the user is informed that the psychological tension is lower in the process of performing the assessment problem test, the reliability of the test result is lower, the tension level analysis result which is greater than the preset tension level threshold is not adopted, the tension level analysis result which is less than or equal to the preset tension level threshold is used as a plurality of unqualified tension level analysis results, and the tension level analysis result which is less than or equal to the preset tension level threshold can be used as the basis of a subsequent determination assessment mode.
Further, as shown in fig. 3, step S400 of the embodiment of the present application further includes:
s410: according to the physiological parameter set acquired by the target user in the historical time, acquiring a plurality of historical physiological parameter sets, and analyzing the tension degree to acquire a plurality of historical tension degree analysis results;
s420: the stress analysis model is constructed by adopting the plurality of historical physiological parameter sets and the plurality of historical stress analysis results, the stress analysis model comprises a stress evaluation coordinate system and a plurality of historical coordinate points, and each historical coordinate point is marked by the corresponding historical stress analysis result;
s430: respectively inputting the multiple physiological parameter sets into a tension degree analysis model to obtain multiple current coordinate points;
s440: respectively acquiring K historical coordinate points nearest to the current coordinate points, acquiring a plurality of historical coordinate point sets, acquiring a historical tension degree analysis result corresponding to each historical coordinate point, and acquiring a plurality of historical tension degree analysis result sets, wherein K is an odd number greater than or equal to 3;
s450: and respectively selecting the historical tension degree analysis results with highest occurrence frequency in the multiple historical tension degree analysis result sets to obtain the multiple tension degree analysis results.
Specifically, from a collection of physiological parameters collected by the target user in a past historical time, for example, the past year, a plurality of heart rate, skin temperature and palm sweat level data are extracted, the heart rate, skin temperature and palm sweat level data are taken as a plurality of historical physiological parameter sets, and tension level analysis is performed by using the plurality of historical physiological parameter sets, wherein the tension level analysis is that a professional psychological doctor or consultant judges tension level of the user in a test from a professional angle based on data in the historical physiological parameter sets of the target user by experience, and a plurality of historical tension level analysis results are given.
Specifically, an X-axis, a Y-axis and a Z-axis of a tension evaluation coordinate system are constructed by using heart rate, skin temperature and palm perspiration levels in the plurality of historical physiological parameter sets, for example, the heart rate may be the X-axis, the skin temperature may be the Y-axis, the palm perspiration level may be the Z-axis, the heart rate may be the Y-axis, the skin temperature may be the X-axis, the palm perspiration level may be the Z-axis, and the parameter indexes and the coordinate axes may be set according to the needs. And inputting a plurality of corresponding historical physiological parameters into a coordinate system to form a plurality of historical coordinate points, wherein different heart rates, skin temperatures and palm sweat degrees form different specific coordinate values. And the plurality of historical coordinate points are marked in one-to-one correspondence with the plurality of historical tension analysis results to form the tension analysis model.
And respectively inputting the plurality of physiological parameter sets which are currently obtained into a tension degree analysis model, so that a plurality of current coordinate points can be obtained. And then respectively extracting K historical coordinate points nearest to the current coordinate points in the tension analysis model, namely, odd number of the historical coordinate points which are more than or equal to 3 and are most similar to the current coordinate points, sorting the K historical coordinate points into a plurality of historical coordinate point sets, and extracting a historical tension analysis result corresponding to each historical coordinate point through identification marks to serve as a plurality of historical tension analysis result sets. And finally, respectively selecting the historical tension degree analysis results with the highest occurrence frequency in the plurality of historical tension degree analysis result sets, namely the most similar historical tension degree analysis results, and taking the historical tension degree analysis results as the plurality of tension degree analysis results which can be used as the basis for subsequently determining the evaluation mode.
Further, step S420 of the embodiment of the present application further includes:
s421: constructing a plurality of coordinate axes in the stress assessment coordinate system based on a plurality of physiological parameter indexes in the physiological parameter index set;
s422: inputting the plurality of historical physiological parameter sets into the stress evaluation coordinate system to form a plurality of historical coordinate points;
S423: and constructing a plurality of markers by adopting the plurality of historical tension analysis results, and marking the plurality of historical coordinate points to obtain the tension analysis model.
Specifically, three physiological parameter indexes of heart rate, skin temperature and palm perspiration degree in the physiological parameter index set are used as coordinate axes in the tension evaluation coordinate system, and then the heart rate, skin temperature and palm perspiration degree in the historical physiological parameter sets are input into the tension evaluation coordinate system according to the values of the three physiological parameter indexes to form a plurality of corresponding historical coordinate points. And constructing a plurality of markers corresponding to the obtained historical tension analysis results by using the obtained historical tension analysis results, and marking the corresponding historical coordinate points to form the tension analysis model, so that the tension analysis model can be used for analyzing the tension of a target user.
S500: judging whether the duty ratio of the plurality of unqualified tension degree analysis results is larger than a preset proportion threshold, if so, carrying out early warning, or if not, determining an evaluation mode according to a plurality of effective evaluation problems corresponding to the plurality of qualified tension degree analysis results;
specifically, the preset proportion threshold value refers to a maximum value of a proportion of the number of times of stress in all tests of a target user preset in advance to the total number of tests, for example, 50%, the number of tests corresponding to the plurality of unqualified stress degree analysis results is divided by the total number of tests, if the obtained value is larger than the preset proportion threshold value, the user is in a psychological stress state for a long time, the reliability of all the test results is low, the pre-warning of problems in psychological health is not adopted and performed, if the proportion of the unqualified stress degree analysis results is smaller than or equal to the preset proportion threshold value, the reliability of part of the test results is illustrated, namely, the plurality of qualified stress degree analysis results are reliable, an evaluation mode is formulated according to the evaluation problem corresponding to the reliable test results, and the evaluation mode can be used for matching the corresponding psychological health evaluation model.
Further, as shown in fig. 4, step S500 of the embodiment of the present application further includes:
s510: acquiring an effective evaluation problem number threshold according to the preset proportion threshold and the number of the plurality of evaluation problems;
s520: randomly selecting and combining the evaluation questions with the number larger than the effective evaluation question number threshold value in the plurality of evaluation questions to obtain a plurality of sample effective question combinations, and taking the plurality of sample effective question combinations as a plurality of sample evaluation modes;
s530: and combining the plurality of effective evaluation questions to obtain a target effective question combination and a corresponding evaluation mode.
Specifically, the number of evaluation questions just reaching the preset proportion threshold can be obtained by multiplying the proportion value of the preset proportion threshold by the number of the plurality of evaluation questions, and the number of the evaluation questions just reaching the preset proportion threshold can be used as an effective evaluation question number threshold. In order to ensure the validity of the test, the evaluation questions with the number larger than the threshold value of the number of the valid evaluation questions are randomly selected from the plurality of evaluation questions, and are combined to obtain a plurality of sample valid question combinations which are used as a plurality of sample evaluation modes. Combining the effective evaluation questions corresponding to the qualified tension degree analysis results to obtain target effective question combinations, and matching the target effective question combinations with sample effective question combinations one by one to obtain evaluation modes corresponding to the target effective question combinations, wherein the evaluation modes can be used for matching corresponding mental health evaluation models.
S600: and inputting a plurality of effective test results of the plurality of effective assessment problems into a psychological health assessment model corresponding to the assessment mode by combining the plurality of qualified tension degree analysis results to obtain a psychological health assessment result, and carrying out early warning when the psychological health assessment result is unqualified.
Specifically, a plurality of effective test results obtained based on a plurality of effective evaluation problem tests and a corresponding plurality of qualified stress analysis results are extracted, and corresponding mental health evaluation models are matched according to evaluation modes corresponding to target effective problem combinations, wherein the mental health evaluation models are neural network models capable of continuously performing self iterative optimization, and can be obtained through monitoring training of training data sets, verification data sets and test data sets, and the mental health evaluation models can be constructed by the following steps: firstly, inputting each group of training data in a training data set into a mental health assessment model, then, adjusting network parameters of the model according to the difference value between output data and expected data corresponding to each group of training data, and further, training all data in the training data set until the network parameters meet convergence conditions, thereby completing training of the mental health assessment model. In order to ensure the accuracy of the mental health assessment model, after the accuracy test of the mental health assessment model is carried out by using the test data set, the construction of the mental health assessment model is completed. Inputting a plurality of effective test results of the plurality of effective assessment problems and the plurality of qualified tension degree analysis results into a psychological health assessment model corresponding to the assessment mode, outputting a psychological health assessment result by the psychological health assessment model, judging whether the assessment result is qualified or not, and if the psychological health assessment result is unqualified, indicating that the psychological health condition of the target user is poor, carrying out early warning, and carrying out psychological intervention and dispersion. By the method for outputting the mental health assessment result by the mental health assessment model, the accuracy of the mental health assessment result can be improved.
Further, step S600 of the embodiment of the present application further includes:
s610: acquiring a plurality of historical effective test result sets, a plurality of historical qualified tension degree analysis result sets and a plurality of historical psychological health assessment results according to test data in a plurality of effective assessment problem history times corresponding to the assessment mode;
s620: adopting the plurality of historical effective test result sets, the plurality of historical qualified tension degree analysis result sets and the plurality of historical mental health assessment results as construction data to construct the mental health assessment model corresponding to the assessment mode;
s630: inputting the effective test results and the qualified tension degree analysis results into the mental health assessment model to obtain the mental health assessment result.
Specifically, from a past period of time, in test data of psychological tests on a target user by using a plurality of corresponding effective evaluation questions in the evaluation mode, extracting a plurality of effective test results as a plurality of historical effective test result sets, extracting a plurality of qualified stress analysis results as a plurality of historical qualified stress analysis result sets, extracting a plurality of historical psychological health evaluation results, and training, verifying and testing by using the construction data as construction data by using the plurality of historical effective test result sets, the plurality of historical qualified stress analysis result sets and the plurality of historical psychological health evaluation results to obtain the psychological health evaluation model corresponding to the evaluation mode. And taking the effective test results and the qualified tension degree analysis results as input data, inputting the input data into the mental health assessment model corresponding to the assessment mode, and outputting the corresponding mental health assessment result by the mental health assessment model, so that the accuracy of the mental health assessment result can be improved.
Further, step S620 of the embodiment of the present application further includes:
s621: based on a BP neural network, constructing the psychological health assessment model, wherein input data of the psychological health assessment model comprises test results of a plurality of effective assessment questions corresponding to the assessment mode and a plurality of tension degree analysis results;
s622: marking and dividing the data of the plurality of historical effective test result sets, the plurality of historical qualified tension degree analysis result sets and the plurality of historical psychological health assessment results to obtain a training data set, a verification data set and a test data set;
s623: and performing supervision training on the mental health assessment model by adopting the training data set, the verification data set and the test data set, updating and adjusting network parameters according to errors of actual output and expected output until convergence conditions are met, and then performing verification and test to obtain the mental health assessment model under the condition that preset conditions are met.
Specifically, the BP neural network is a multi-layer feedforward neural network trained according to an error reverse propagation algorithm, a mathematical equation of a mapping relation between input and output is not required to be determined in advance, a certain rule is learned only through self training, and a result closest to an expected output value is obtained when an input value is given. The application is based on the architecture of a BP neural network model, and combines data such as a historical effective test result set and the like to carry out model training, so as to obtain the psychological health assessment model, and the psychological health assessment model uses test results of a plurality of effective assessment questions corresponding to the assessment mode and a plurality of tension degree analysis results as input data to output the psychological health assessment result.
Specifically, the process of constructing the mental health assessment model may be: extracting the multiple historical effective test result sets, the multiple historical qualified stress analysis result sets and the multiple historical psychological health assessment results from psychological assessment data before a target user, marking and dividing the data into a training data set, a verification data set and a test data set by using a uniform random sampling mode, inputting one group of training data in the training data set into a psychological health assessment model for supervision training, then carrying out network parameter adjustment on the model by the difference value of output data and expected data corresponding to the group of training data, further training all data in the training data until the training of all the training data and the adjustment of network parameters are completed, enabling the network parameters to meet convergence conditions, inputting data in the verification data set into the psychological health assessment model, and finally adjusting the network parameters by the difference value of the output data corresponding to the verification data and the expected data, thereby completing the training of the psychological health assessment model. In order to ensure the accuracy of the mental health assessment model, the mental health assessment model can be tested by using a test data set, the test accuracy is set to be 85%, if the test accuracy of the current test data set meets 85%, the mental health assessment model is constructed, and the mental health assessment model can be used for carrying out mental health assessment on a target user so as to judge whether the mental condition of the user needs early warning or not.
In summary, the embodiment of the application has at least the following technical effects:
according to the application, a psychological health assessment test is carried out on a target user by adopting an assessment problem to obtain a plurality of test results, physiological parameters of the target user are collected in the test process to carry out tension degree analysis to obtain a plurality of tension degree analysis results, whether the tension degree analysis results are larger than a preset tension degree threshold value or not is judged respectively, if the ratio of the unqualified tension degree analysis results is larger than a preset proportion threshold value, early warning is carried out, or if the ratio of the unqualified tension degree analysis results is not larger than the preset proportion threshold value, an assessment mode is determined according to the qualified tension degree analysis results, the assessment mode is input into a corresponding psychological health assessment model to obtain a psychological health assessment result, and when the psychological health assessment result is unqualified, early warning is carried out.
The technical effect of improving the accuracy of the psychological health assessment result is achieved.
Example two
Based on the same inventive concept as the mental health assessment and early warning method in the foregoing embodiments, as shown in fig. 5, the present application provides a mental health assessment and early warning system, and the system and method embodiments in the embodiments of the present application are based on the same inventive concept. Wherein the system comprises:
an evaluation problem acquisition module 11, wherein the evaluation problem acquisition module 11 is used for acquiring a plurality of evaluation problems for performing mental health evaluation on a user;
A test result obtaining module 12, where the test result obtaining module 12 is configured to test a target user by using the multiple evaluation questions to obtain multiple test results;
the physiological parameter set obtaining module 13 is configured to collect physiological parameters of the target user according to a physiological parameter index set during the multiple evaluation problem testing processes, so as to obtain multiple physiological parameter sets;
the stress analysis result obtaining module 14 is configured to input the plurality of physiological parameter sets into a stress analysis model to obtain a plurality of stress analysis results, and determine whether the plurality of physiological parameter sets are greater than a preset stress threshold, to obtain a plurality of unqualified stress analysis results greater than the preset stress threshold, and a plurality of qualified stress analysis results;
the evaluation mode determining module 15 is configured to determine whether the duty ratio of the plurality of unqualified stress level analysis results is greater than a preset proportion threshold, if yes, perform early warning, or if no, determine an evaluation mode according to a plurality of effective evaluation questions corresponding to the plurality of qualified stress level analysis results;
The mental health assessment result obtaining module 16 is configured to input a plurality of effective test results of the plurality of effective assessment questions and the plurality of qualified stress analysis results into a mental health assessment model corresponding to the assessment mode, obtain a mental health assessment result, and perform early warning when the mental health assessment result is unqualified.
Further, the system further comprises:
the physiological parameter index set acquisition module is used for acquiring the physiological parameter index set, wherein the physiological parameter index set comprises a heart rate index, a skin temperature index and a palm perspiration index;
the physiological parameter set obtaining module is used for detecting the heart rate, skin temperature and palm sweat degree of the target user in the process of testing each evaluation problem to obtain the physiological parameter sets.
Further, the system further comprises:
the tension analysis module is used for acquiring a plurality of historical physiological parameter sets according to the physiological parameter sets acquired by the target user in the historical time, and carrying out tension analysis to acquire a plurality of historical tension analysis results;
The tension analysis model construction module is used for constructing the tension analysis model by adopting the plurality of historical physiological parameter sets and the plurality of historical tension analysis results, wherein the tension analysis model comprises a tension evaluation coordinate system and a plurality of historical coordinate points, and each historical coordinate point is marked by the corresponding historical tension analysis result;
the current coordinate point obtaining module is used for respectively inputting the plurality of physiological parameter sets into the tension degree analysis model to obtain a plurality of current coordinate points;
the historical tension degree analysis result set obtaining module is used for respectively obtaining K historical coordinate points nearest to the current coordinate points, obtaining a plurality of historical coordinate point sets, obtaining a historical tension degree analysis result corresponding to each historical coordinate point, and obtaining a plurality of historical tension degree analysis result sets, wherein K is an odd number greater than or equal to 3;
the tension degree analysis result obtaining module is used for respectively selecting the historical tension degree analysis results with highest occurrence frequency in the plurality of historical tension degree analysis result sets to obtain the plurality of tension degree analysis results.
Further, the system further comprises:
the coordinate axis construction module is used for constructing a plurality of coordinate axes in the tension evaluation coordinate system based on a plurality of physiological parameter indexes in the physiological parameter index set;
the historical coordinate point acquisition module is used for inputting the plurality of historical physiological parameter sets into the tension evaluation coordinate system to form a plurality of historical coordinate points;
and the tension degree analysis model obtaining module is used for constructing a plurality of markers by adopting the plurality of historical tension degree analysis results and marking the plurality of historical coordinate points to obtain the tension degree analysis model.
Further, the system further comprises:
the effective evaluation problem number threshold acquisition module is used for acquiring an effective evaluation problem number threshold according to the preset proportion threshold and the number of the plurality of evaluation problems;
the sample effective problem combination acquisition module is used for randomly selecting the evaluation problems with the number larger than the threshold value of the effective evaluation problems in the plurality of evaluation problems to be combined, so as to obtain a plurality of sample effective problem combinations and serve as a plurality of sample evaluation modes;
The target effective problem combination acquisition module is used for combining the plurality of effective evaluation problems to obtain target effective problem combinations and corresponding evaluation modes.
Further, the system further comprises:
the historical effective test result set acquisition module is used for acquiring a plurality of historical effective test result sets, a plurality of historical qualified tension degree analysis result sets and a plurality of historical psychological health assessment results according to test data in a plurality of effective assessment problem history times corresponding to the assessment mode;
the psychological health assessment model construction module is used for constructing the psychological health assessment model corresponding to the assessment mode by adopting the plurality of historical effective test result sets, the plurality of historical qualified tension degree analysis result sets and the plurality of historical psychological health assessment results as construction data;
the psychological health assessment result obtaining module is used for inputting the effective test results and the qualified tension degree analysis results into the psychological health assessment model to obtain the psychological health assessment result.
Further, the system further comprises:
the psychological health assessment model construction module is used for constructing the psychological health assessment model based on the BP neural network, and input data of the psychological health assessment model comprise test results of a plurality of effective assessment questions corresponding to the assessment mode and a plurality of tension degree analysis results;
the data set obtaining module is used for marking and dividing the plurality of historical effective test result sets, the plurality of historical qualified tension degree analysis result sets and the plurality of historical psychological health assessment results to obtain a training data set, a verification data set and a test data set;
the mental health assessment model obtaining module is used for performing supervision training on the mental health assessment model by adopting the training data set, the verification data set and the test data set, updating and adjusting network parameters according to errors of actual output and expected output until convergence conditions are met, and then performing verification and test to obtain the mental health assessment model under the condition that preset conditions are met.
It should be noted that the sequence of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. And the foregoing description has been directed to specific embodiments of this specification. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
The foregoing description of the preferred embodiments of the application is not intended to limit the application to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and scope of the application are intended to be included within the scope of the application.
The specification and figures are merely exemplary illustrations of the present application and are considered to cover any and all modifications, variations, combinations, or equivalents that fall within the scope of the application. It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the scope of the application. Thus, the present application is intended to include such modifications and alterations insofar as they come within the scope of the application or the equivalents thereof.
Claims (7)
1. A mental health assessment and early warning system, the system comprising:
the evaluation problem acquisition module is used for acquiring a plurality of evaluation problems for performing mental health evaluation on the user;
the test result obtaining module is used for testing the target user by adopting the plurality of evaluation problems to obtain a plurality of test results;
the physiological parameter set obtaining module is used for collecting physiological parameters of the target user according to the physiological parameter index set in the process of testing the plurality of evaluation problems to obtain a plurality of physiological parameter sets;
the tension degree analysis result obtaining module is used for respectively inputting the multiple physiological parameter sets into a tension degree analysis model to obtain multiple tension degree analysis results, respectively judging whether the multiple physiological parameter sets are larger than a preset tension degree threshold value or not, and obtaining a plurality of unqualified tension degree analysis results and a plurality of qualified tension degree analysis results which are larger than the preset tension degree threshold value;
the evaluation mode determining module is used for judging whether the duty ratio of the plurality of unqualified tension degree analysis results is larger than a preset proportion threshold value, if so, early warning is carried out, or if not, an evaluation mode is determined according to a plurality of effective evaluation problems corresponding to the plurality of qualified tension degree analysis results;
The psychological health assessment result obtaining module is used for inputting a plurality of effective test results of the plurality of effective assessment problems into a psychological health assessment model corresponding to the assessment mode by combining the plurality of qualified tension degree analysis results, obtaining a psychological health assessment result, and carrying out early warning when the psychological health assessment result is unqualified;
the method comprises the steps of respectively inputting the multiple physiological parameter sets into a tension degree analysis model to obtain multiple tension degree analysis results, wherein the steps comprise:
the tension analysis module is used for acquiring a plurality of historical physiological parameter sets according to the physiological parameter sets acquired by the target user in the historical time, and carrying out tension analysis to acquire a plurality of historical tension analysis results;
the tension analysis model construction module is used for constructing the tension analysis model by adopting the plurality of historical physiological parameter sets and the plurality of historical tension analysis results, wherein the tension analysis model comprises a tension evaluation coordinate system and a plurality of historical coordinate points, and each historical coordinate point is marked by the corresponding historical tension analysis result;
The current coordinate point obtaining module is used for respectively inputting the plurality of physiological parameter sets into the tension degree analysis model to obtain a plurality of current coordinate points;
the historical tension degree analysis result set obtaining module is used for respectively obtaining K historical coordinate points nearest to the current coordinate points, obtaining a plurality of historical coordinate point sets, obtaining a historical tension degree analysis result corresponding to each historical coordinate point, and obtaining a plurality of historical tension degree analysis result sets, wherein K is an odd number greater than or equal to 3;
the tension degree analysis result obtaining module is used for respectively selecting the historical tension degree analysis results with highest occurrence frequency in the plurality of historical tension degree analysis result sets to obtain the plurality of tension degree analysis results.
2. The system of claim 1, wherein during the plurality of assessment problem tests, respectively, the physiological parameters of the target user are collected according to a set of physiological parameter indicators to obtain a plurality of sets of physiological parameters, comprising:
The physiological parameter index set acquisition module is used for acquiring the physiological parameter index set, wherein the physiological parameter index set comprises a heart rate index, a skin temperature index and a palm perspiration index;
the physiological parameter set obtaining module is used for detecting the heart rate, skin temperature and palm sweat degree of the target user in the process of testing each evaluation problem to obtain the physiological parameter sets.
3. The system of claim 1, wherein constructing the stress analysis model using the plurality of historical physiological parameter sets and the plurality of historical stress analysis results comprises:
the coordinate axis construction module is used for constructing a plurality of coordinate axes in the tension evaluation coordinate system based on a plurality of physiological parameter indexes in the physiological parameter index set;
the historical coordinate point acquisition module is used for inputting the plurality of historical physiological parameter sets into the tension evaluation coordinate system to form a plurality of historical coordinate points;
and the tension degree analysis model obtaining module is used for constructing a plurality of markers by adopting the plurality of historical tension degree analysis results and marking the plurality of historical coordinate points to obtain the tension degree analysis model.
4. The system of claim 1, wherein determining an evaluation pattern based on a number of effective evaluation questions corresponding to the number of acceptable tension analysis results comprises:
the effective evaluation problem number threshold acquisition module is used for acquiring an effective evaluation problem number threshold according to the preset proportion threshold and the number of the plurality of evaluation problems;
the sample effective problem combination acquisition module is used for randomly selecting the evaluation problems with the number larger than the threshold value of the effective evaluation problems in the plurality of evaluation problems to be combined, so as to obtain a plurality of sample effective problem combinations and serve as a plurality of sample evaluation modes;
the target effective problem combination acquisition module is used for combining the plurality of effective evaluation problems to obtain target effective problem combinations and corresponding evaluation modes.
5. The system of claim 1, wherein inputting the plurality of effective test results of the plurality of effective assessment questions, in combination with the plurality of acceptable stress analysis results, into a mental health assessment model corresponding to the assessment mode, to obtain a mental health assessment result, comprises:
The historical effective test result set acquisition module is used for acquiring a plurality of historical effective test result sets, a plurality of historical qualified tension degree analysis result sets and a plurality of historical psychological health assessment results according to test data in a plurality of effective assessment problem history times corresponding to the assessment mode;
the psychological health assessment model construction module is used for constructing the psychological health assessment model corresponding to the assessment mode by adopting the plurality of historical effective test result sets, the plurality of historical qualified tension degree analysis result sets and the plurality of historical psychological health assessment results as construction data;
the psychological health assessment result obtaining module is used for inputting the effective test results and the qualified tension degree analysis results into the psychological health assessment model to obtain the psychological health assessment result.
6. The system of claim 5, wherein constructing the mental health assessment model corresponding to the assessment model using the plurality of historical valid test result sets, a plurality of historical qualified stress analysis result sets, and a plurality of historical mental health assessment results as construction data comprises:
The psychological health assessment model construction module is used for constructing the psychological health assessment model based on the BP neural network, and input data of the psychological health assessment model comprise test results of a plurality of effective assessment questions corresponding to the assessment mode and a plurality of tension degree analysis results;
the data set obtaining module is used for marking and dividing the plurality of historical effective test result sets, the plurality of historical qualified tension degree analysis result sets and the plurality of historical psychological health assessment results to obtain a training data set, a verification data set and a test data set;
the mental health assessment model obtaining module is used for performing supervision training on the mental health assessment model by adopting the training data set, the verification data set and the test data set, updating and adjusting network parameters according to errors of actual output and expected output until convergence conditions are met, and then performing verification and test to obtain the mental health assessment model under the condition that preset conditions are met.
7. A mental health assessment and early warning method, the method comprising:
Acquiring a plurality of evaluation questions for performing mental health evaluation on a user;
testing the target user by adopting the plurality of evaluation problems to obtain a plurality of test results;
respectively acquiring physiological parameters of the target user according to a physiological parameter index set in the process of testing the plurality of evaluation problems to obtain a plurality of physiological parameter sets;
respectively inputting the multiple physiological parameter sets into a tension degree analysis model to obtain multiple tension degree analysis results, respectively judging whether the multiple physiological parameter sets are larger than a preset tension degree threshold value, and obtaining a plurality of unqualified tension degree analysis results and a plurality of qualified tension degree analysis results which are larger than the preset tension degree threshold value;
judging whether the duty ratio of the plurality of unqualified tension degree analysis results is larger than a preset proportion threshold, if so, carrying out early warning, or if not, determining an evaluation mode according to a plurality of effective evaluation problems corresponding to the plurality of qualified tension degree analysis results;
inputting the plurality of qualified tension degree analysis results into a psychological health assessment model corresponding to the assessment mode to obtain psychological health assessment results, and carrying out early warning when the psychological health assessment results are unqualified;
The method comprises the steps of respectively inputting the multiple physiological parameter sets into a tension degree analysis model to obtain multiple tension degree analysis results, wherein the steps comprise:
according to the physiological parameter set acquired by the target user in the historical time, acquiring a plurality of historical physiological parameter sets, and analyzing the tension degree to acquire a plurality of historical tension degree analysis results;
the stress analysis model is constructed by adopting the plurality of historical physiological parameter sets and the plurality of historical stress analysis results, the stress analysis model comprises a stress evaluation coordinate system and a plurality of historical coordinate points, and each historical coordinate point is marked by the corresponding historical stress analysis result;
respectively inputting the multiple physiological parameter sets into a tension degree analysis model to obtain multiple current coordinate points;
respectively acquiring K historical coordinate points nearest to the current coordinate points, acquiring a plurality of historical coordinate point sets, acquiring a historical tension degree analysis result corresponding to each historical coordinate point, and acquiring a plurality of historical tension degree analysis result sets, wherein K is an odd number greater than or equal to 3;
and respectively selecting the historical tension degree analysis results with highest occurrence frequency in the multiple historical tension degree analysis result sets to obtain the multiple tension degree analysis results.
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