CN114822847A - Physical and mental health evaluation system, method, equipment and storage medium - Google Patents
Physical and mental health evaluation system, method, equipment and storage medium Download PDFInfo
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Abstract
The invention discloses a physical and mental health evaluation system, a method, equipment and a storage medium, wherein the system comprises: the system comprises a characteristic data collection module, a physical and mental health state evaluation module and a physical and mental health evaluation report display module; the characteristic data collection module is used for obtaining at least one body characteristic data of a testee and psychological characteristic data corresponding to at least two physical and psychological evaluation scales respectively; the physical and mental health state evaluating module is used for determining comprehensive probability values respectively corresponding to at least two preset physical and mental health states based on each body characteristic data, each psychological characteristic data and the factor weight matrix; and the physical and mental health evaluation report display module is used for taking the preset physical and mental health state corresponding to the maximum comprehensive probability value as the target physical and mental health state corresponding to the testee and displaying the physical and mental health evaluation report corresponding to the target physical and mental health state. The embodiment of the invention improves the accuracy of the physical and mental health evaluation result.
Description
Technical Field
The invention relates to the technical field of physical and mental health, in particular to a physical and mental health evaluating system, method, equipment and storage medium.
Background
With the development and progress of society, people pay more and more attention to physical and mental health problems, and physical and mental health evaluation is comprehensive evaluation on physical health state and mental health state.
At present, in order to find or evaluate the physical and mental health status of a subject, the most commonly adopted method is to fill a physical and mental evaluation scale which usually contains items related to physical experience and mental experience by the subject, and the physical and mental health status of the subject is obtained according to the collected item option information and a self-carried rating mechanism of the evaluation scale.
Although the physical and mental evaluation scale comprises items related to physical experience, the selected option corresponding to the item of the subject is influenced by subjective factors, so that the final evaluation result is not scientific and reasonable enough and the accuracy is not high.
Disclosure of Invention
The invention provides a physical and mental health evaluation system, a method, equipment and a storage medium, which are used for solving the problem that the evaluation result of a single physical and mental evaluation scale is easily influenced by subjective factors and improving the accuracy of the physical and mental health evaluation result.
According to an aspect of the present invention, there is provided a physical and mental health evaluation system, comprising: the system comprises a characteristic data collection module, a physical and mental health state evaluation module and a physical and mental health evaluation report display module;
the characteristic data collection module is used for obtaining at least one body characteristic data of a tested person and psychological characteristic data corresponding to at least two physical and psychological evaluation scales respectively;
the physical and mental health state evaluating module is used for determining comprehensive probability values respectively corresponding to at least two preset physical and mental health states based on the physical characteristic data, the psychological characteristic data and the factor weight matrix; the factor weight matrix represents weight information corresponding to each physical characteristic data and each psychological characteristic data respectively;
and the physical and mental health evaluation report display module is used for taking the preset physical and mental health state corresponding to the maximum comprehensive probability value as a target physical and mental health state and displaying the physical and mental health evaluation report corresponding to the target physical and mental health state.
According to another aspect of the invention, a method for evaluating physical and mental health is provided, which comprises the following steps:
acquiring at least one body characteristic data of a testee and psychological characteristic data respectively corresponding to at least two physical and psychological evaluation scales;
determining comprehensive probability values respectively corresponding to at least two preset physical and psychological health states based on the physical characteristic data, the psychological characteristic data and the factor weight matrix; the factor weight matrix represents weight information corresponding to each physical characteristic data and each psychological characteristic data respectively;
and taking the preset physical and mental health state corresponding to the maximum comprehensive probability value as a target physical and mental health state, and displaying a physical and mental health evaluation report corresponding to the target physical and mental health state.
According to another aspect of the present invention, there is provided an electronic apparatus including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the method for evaluating physical and mental health according to any embodiment of the present invention.
According to another aspect of the present invention, a computer-readable storage medium is provided, which stores computer instructions for causing a processor to implement the method for physical and mental health assessment according to any one of the embodiments of the present invention when executed.
According to the technical scheme of the embodiment of the invention, the comprehensive probability values respectively corresponding to at least two preset physical and mental health states are determined by acquiring at least one body characteristic data of the tested person and the psychological characteristic data respectively corresponding to at least two physical and mental evaluation scales, and the preset physical and mental health state corresponding to the maximum comprehensive probability value is taken as the target physical and mental health state corresponding to the tested person, so that the problem that the evaluation result of a single physical and mental evaluation scale is easily influenced by subjective factors is solved, and the accuracy of the physical and mental health evaluation result is improved.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present invention, nor do they necessarily limit the scope of the invention. Other features of the present invention will become apparent from the following description.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic diagram of a physical and mental health evaluation system according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a physical and mental health assessment system according to a second embodiment of the present invention;
fig. 3 is a flowchart of a method for evaluating physical and mental health according to a third embodiment of the present invention;
fig. 4 is a flowchart of a specific example of a method for evaluating physical and mental health according to a third embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, shall fall within the protection scope of the present invention.
It should be noted that the terms "comprises" and "comprising," and any variations thereof, in the description and claims of the present invention and the above-described drawings, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example one
Fig. 1 is a schematic diagram of a physical and mental health evaluation system according to an embodiment of the present invention, where the embodiment is applicable to a situation of evaluating a physical and mental health state of a subject, the physical and mental health evaluation device may be implemented in a form of hardware and/or software, and the physical and mental health evaluation device may be configured in a terminal device. As shown in fig. 1, the system includes: the system comprises a characteristic data collection module 110, a physical and mental health status evaluation module 120 and a physical and mental health evaluation report display module 130.
The characteristic data collection module 110 is configured to obtain at least one body characteristic data of the subject and psychological characteristic data corresponding to at least two physical and psychological evaluation scales;
a physical and mental health status evaluating module 120, configured to determine, based on each physical characteristic data, each psychological characteristic data, and the factor weight matrix, a comprehensive probability value corresponding to each of at least two preset physical and mental health statuses; the factor weight matrix represents weight information corresponding to each body characteristic data and each psychological characteristic data respectively;
and the physical and mental health evaluation report display module 130 is configured to take the preset physical and mental health state corresponding to the maximum comprehensive probability value as the target physical and mental health state, and display the physical and mental health evaluation report corresponding to the target physical and mental health state.
Specifically, the physical characteristic data may be used to reflect the physical health condition of the subject, and the psychological characteristic data may be used to reflect the physical and psychological health condition of the subject. For example, the physical characteristic data may be sleep time data or heart rate data, and the psychological characteristic data may be a scale evaluation total score of a physical and mental evaluation scale.
In an exemplary embodiment, the characteristic data collecting module 110 may display at least one physical characteristic parameter and at least two types of fitness scales through a display device, collect physical characteristic data corresponding to the at least one physical characteristic parameter and inputted by the subject based on the display content, and statistically generate the psychological characteristic data based on scale data inputted by the subject based on the at least two types of fitness scales.
Here, an exemplary set of predetermined physical and mental health states includes "good state", "attention required", and "emergency intervention", and of course, a set of predetermined physical and mental health states includes "excellent state", "good state", "attention required", "regular follow-up", and "emergency intervention". The specific grade setting of the preset physical and mental health state is not limited, and the user can perform self-defined setting according to actual requirements.
In one embodiment, the factor weight matrix optionally includes a body weight matrix corresponding to each body characteristic data, a psychological weight matrix corresponding to each psychological characteristic data, and a body psychological weight matrix, and the physical and psychological health status evaluating module 120 includes: the body probability value determining unit is used for determining target body probability values respectively corresponding to at least two preset physical and psychological health states based on the body characteristic data and the body weight matrix; the psychological probability value determining unit is used for determining target psychological probability values respectively corresponding to at least two preset physical and psychological health states based on each psychological characteristic data and the psychological weight matrix; and the comprehensive probability value determining unit is used for determining comprehensive probability values respectively corresponding to at least two preset physical and psychological health states based on the physical probability values of the targets, the psychological probability values of the targets and the psychological weight matrix of the body.
Specifically, the body weight matrix may be used to represent weight information corresponding to each body characteristic data, the psychological weight matrix may be used to represent weight information corresponding to each psychological characteristic data, and the body psychological weight matrix may be used to represent weight information corresponding to each body factor and each psychological factor. In one embodiment, the factor weight matrix may optionally be user preset.
In an embodiment, optionally, the body probability value determining unit is specifically configured to: based on a preset body evaluation list, fuzzification processing is respectively carried out on the body characteristic data to obtain a body factor matrix; determining target body probability values respectively corresponding to at least two preset physical and psychological health states based on the body factor matrix and the body weight matrix; the preset body evaluation list comprises at least one body characteristic parameter and body characteristic data ranges corresponding to each body characteristic parameter and at least two preset physical and mental health states respectively, and the body factor matrix represents initial body probability values corresponding to each body characteristic data and the at least two preset physical and mental health states respectively.
Specifically, a body membership function is adopted, and fuzzification processing is respectively carried out on each body characteristic data based on a body evaluation list to obtain a body factor matrix. The body membership function is used for depicting the degree of body characteristic data belonging to a certain preset physical and mental health state. Exemplary function types for the body membership function include, but are not limited to, rectangular, trapezoidal, parabolic, normal, cauchy, and the like.
For example, if the number of the body characteristic data is 5 and the number of the preset physical and mental health states is 3, the body factor matrix is a matrix of 3 × 5, and each column represents an initial body probability value corresponding to each body characteristic data and each preset physical and mental health state. Correspondingly, the body weight matrix is a matrix of 5 × 1, each row represents a weight coefficient corresponding to each body characteristic data, the body factor matrix is multiplied by the body weight matrix to obtain a body membership degree matrix of 3 × 1, and each row of the matrix represents a target body probability value corresponding to 3 preset physical and mental health states.
In an embodiment, optionally, the psychological probability value determining unit is specifically configured to: performing fuzzification processing on each psychological characteristic data respectively based on a preset psychological evaluation list to obtain a psychological factor matrix; determining target psychological probability values respectively corresponding to at least two preset physical and psychological health states based on the psychological factor matrix and the psychological weight matrix; the preset psychological evaluation list comprises at least one psychological characteristic parameter and psychological characteristic data ranges corresponding to each psychological characteristic parameter and at least two preset physical and mental health states respectively, and the psychological factor matrix represents initial psychological probability values corresponding to each psychological characteristic data and at least two preset physical and mental health states respectively.
Specifically, a psychological membership function is adopted, and fuzzification processing is performed on each psychological characteristic data based on a psychological evaluation list to obtain a psychological factor matrix. The psychological membership function is used for describing the degree of psychological characteristic data belonging to a certain preset physical and psychological health state. Exemplary function types of the mental membership function include, but are not limited to, rectangular, trapezoidal, parabolic, normal, cauchy, and the like.
For example, if the number of the psychological characteristic data is 6 and the number of the preset physical and mental health states is 3, the psychological factor matrix is a 3 × 6 matrix, and each column represents an initial psychological probability value corresponding to each psychological characteristic data and each preset physical and mental health state. Correspondingly, the psychological weight matrix is a 6 x 1 matrix, each row represents a weight coefficient corresponding to each psychological characteristic data, the psychological factor matrix is multiplied by the psychological weight matrix to obtain a 3 x 1 psychological membership matrix, and each row of the matrix represents a target psychological probability value corresponding to 3 preset physical and mental health states.
The body psychology weight matrix is a 2 x 1 matrix, and each row represents weight coefficients corresponding to the body factors and the psychology factors respectively. Taking the above example as an example, the body membership matrix and the psychological membership matrix form a 3 × 2 probability matrix, the probability matrix is multiplied by the body psychological weight matrix to obtain a 3 × 1 matrix, and each row of the matrix represents a comprehensive probability value corresponding to 3 preset physical and psychological health states.
According to the technical scheme of the embodiment, at least one body characteristic data of the tested person and psychological characteristic data corresponding to at least two physical and psychological evaluation scales are obtained, the comprehensive probability values corresponding to at least two preset physical and psychological health states are determined based on the body characteristic data, the psychological characteristic data and the factor weight matrix, the preset physical and psychological health state corresponding to the maximum comprehensive probability value is used as the target physical and psychological health state corresponding to the tested person, the problem that the evaluation result of a single physical and psychological evaluation scale is easily influenced by subjective factors is solved, and the accuracy of the physical and psychological health evaluation result is improved.
Example two
Fig. 2 is a schematic diagram of a physical and mental health evaluation system according to a second embodiment of the present invention, which is further optimized in the present embodiment. As shown in fig. 2, the system includes: a basic data collection module 210, a characteristic data collection module 220, a physical and mental health status evaluation module 230 and a physical and mental health evaluation report display module 240; the basic data collection module 210 is configured to obtain basic information data of the subject, and send at least one physical characteristic parameter and at least two types of physical and mental evaluation scales determined based on the basic information data to the characteristic data collection module 220.
Wherein, the basic information data can be used to describe parameter values of basic information parameters of the testee, wherein, the basic information parameters include but are not limited to at least one of sex, age, height, weight and occupation.
Specifically, at least one body characteristic parameter and at least two physical and mental evaluation scales are determined based on basic information data and a preset mapping list. The preset mapping list comprises parameter values respectively corresponding to at least one basic information parameter, at least one body characteristic parameter respectively corresponding to each parameter value, and at least two physical and mental evaluation scales.
In one embodiment, when the basic information data includes parameter values of at least two basic information parameters, an intersection of at least one body characteristic parameter corresponding to each of the parameter values of the at least two basic information parameters in the preset mapping list is used as the at least one body characteristic parameter sent to the characteristic data collection module 220, and an intersection of at least two body and mind evaluation meters corresponding to each of the parameter values of the at least two basic information parameters is used as the at least two body and mind evaluation meters sent to the characteristic data collection module 220.
For example, assuming that the basic information data includes "man" and "26 years old," the physical characteristic parameter corresponding to "man" in the preset mapping list includes a physical characteristic parameter a and a physical characteristic parameter B, the mind and body evaluation scale includes a scale a, a scale B, and a scale C, the physical characteristic parameter corresponding to "26 years old" includes a physical characteristic parameter a and a physical characteristic parameter C, and the mind and body evaluation scale includes a scale a, a scale C, and a scale D, the physical characteristic parameter a, the scale a, and the scale C are sent to the characteristic data collection module 220.
In one embodiment, optionally, the physical characteristic data is blood pressure data, neutrophil-lymphocyte ratio data, body mass index data, walking step number data, sedentary time data, dietary intake data, weight float data, sleep time data, or smoking amount data; the physical and mental evaluation scale is symptom self-evaluation scale, Essecker personality questionnaire-emotional scale, Kannel medical index scale, mood state scale-depression scale or university student mental stress scale.
The blood pressure data may include, among other things, systolic pressure data and/or diastolic pressure data. Among them, neutrophil-Lymphocyte ratio (NLR) data, which is the ratio between neutrophil count and Lymphocyte count, can be used to evaluate inflammatory responses and antiviral indicators in vivo. Both neutrophils and lymphocytes are white blood cells, and bacterial infection may lead to an increase in neutrophil count and viral infection may lead to an increase in lymphocyte count. Body Mass Index (BMI) data is commonly used to measure the Body's fat and thin and whether the Body is healthy. The body weight floating amount data may describe the body weight floating amount within a preset time period, and the preset time period may be 1 month or 2 months, for example. The sleep time data may describe, for example, an average sleep time within a preset time period, which may be one week or 3 days. Wherein the smoking amount data may describe the total number of cigarettes smoked over a preset period of time, which may be, for example, 1 day or a week.
Wherein, the symptom self-rating scale (symptommichecklist 90, SCL-90) is also named as 90 symptom lists, which comprise wider psychology content such as feeling, emotion, thinking, consciousness, behavior to life habit, interpersonal relationship, dietary sleep and the like, and 10 factors are adopted to respectively reflect 10 aspects of psychology conditions. In particular, the psychographic parameters corresponding to the symptom self-rating scale include, but are not limited to, the total score of SCL-90 and the number of SCL-90 positive items. Wherein, the Essenck Personality Questionnaire (EPQ) comprises four subscales, namely an internal and external tendency scale, an emotional scale, a mental allergy scale and an effectiveness scale. The emotional scale in the exen personality questionnaire is selected in the present example, and in particular, the psychological characteristic parameters corresponding to the exen personality questionnaire-emotional scale include, but are not limited to, EPQ-N total points. Among them, the Cornell Medical Index scale (CMI) is applicable to adults 14 years old and older, and is divided into 18 parts of 195 items, which mainly relate to the four aspects of physical symptoms, family history and past history, general health and habit and mental symptoms, and the M (unadapted) -R (tension) part has 51 items, which are problems regarding mood, emotion and behavior related to mental activities. Psychographic parameters corresponding to the cornell medical index scale include, but are not limited to, CMI total score and CMI _ M-R score. Wherein, the Mood state scale (POMS) is composed of 65 adjectives describing different Mood states by 6 Mood factors, which comprises 6 subscales mainly used for evaluating the short-term psychotherapy, drug dependence, addiction, emotional stimulation, the Mood states and Mood changes caused by athlete competition, and is divided into 6 subscales including an stress scale, a depression scale, an anger scale, a strength scale, a fatigue scale and a confusion scale. The present example selects the depression scale from the mood state scale, and in particular, the psychographic parameters corresponding to the mood state scale-depression scale include, but are not limited to, POMS depression score. The psychological characteristic parameters corresponding to the college student psychological stress scale comprise but are limited to the psychological stress scores.
On the basis of the above embodiment, optionally, the physical and mental health status evaluating module 230 further includes a factor weight matrix determining unit, configured to: determining a factor weight matrix by adopting a chromatography analysis method based on the comparison judgment matrix; the comparison and judgment matrix represents the importance degree between every two factors, and comprises a body comparison matrix corresponding to at least two types of body characteristic data, a psychological comparison matrix corresponding to at least two types of psychological characteristic data and a body psychological comparison matrix.
The analytic hierarchy process is a systematic method which takes a complex multi-target decision problem as a system, decomposes a target into a plurality of targets or criteria, further decomposes the targets into a plurality of layers of multi-index, and calculates the single-layer sequence and the total sequence of the layers by a qualitative index fuzzy quantization method to be taken as the target and multi-scheme optimization decision. The chromatography determines a matrix characteristic vector based on a comparison judgment matrix, and finally, a weighting summation method recurs to obtain a factor weight matrix.
Specifically, the comparison and judgment matrix may be preset by an expert in the psychology and psychology industry.
The method has the advantages that the rationality of the factor weight matrix can be improved, and the accuracy of subsequent physical and mental health evaluation results is further improved.
On the basis of the above embodiment, optionally, when the physical assessment scale includes a symptom self-assessment scale, the psychological characteristic data corresponding to the symptom self-assessment scale includes the option value data of item 15, and when the physical assessment scale includes a cornell medical index scale, the psychological characteristic data corresponding to the cornell medical index scale includes the option value data of item 162, and accordingly, the system further includes an emergency alarm module, configured to: and if the option value data of the item 15 is greater than 2 or the option value data of the item 162 is yes, taking the preset physical and mental health state with the highest severity level of the at least two preset physical and mental health states as a target physical and mental health state, and executing emergency alarm operation.
For example, the emergency alarm operation may be sending the option value data of item 15, the option value data of item 162, and/or a physical and mental health assessment report corresponding to the target physical and mental health status to the psychological counselor by means of mail, short message, or WeChat.
The advantage of such an arrangement is that the real physical and mental health status of the tested person can be quickly found, so that the subsequent evaluation result of the physical and mental health status evaluation module 230 does not influence the identification of the real physical and mental health status, and the evaluation result of the physical and mental health evaluation system is inaccurate.
The physical characteristic parameters and the psychosomatic evaluation scales suitable for the testees with different identities may be different, for example, the neutrophil-lymphocyte ratio data comparison is suitable for the female testees, the cornell medical index table is suitable for the adults aged 14 years old and older, and the like, the technical scheme of the embodiment, by arranging the basic data collection module, the basic information data of the testee is obtained, and at least one body characteristic parameter and at least two types of physical and mental evaluation scales determined based on the basic information data are sent to the characteristic data collection module, so that the problem of poor individuation of the obtained body characteristic data and the obtained mental characteristic data is solved, the adaptation scene of the physical and mental health evaluation system is widened, the correlation degree and the matching degree between the obtained characteristic data and the identity of the testee are improved, and the accuracy of the physical and mental health evaluation result is further improved.
EXAMPLE III
Fig. 3 is a flowchart of a physical and mental health evaluation method according to a third embodiment of the present invention, which is applicable to the evaluation of the physical and mental health status of a subject, and can be executed by a physical and mental health evaluation device. As shown in fig. 3, the method includes:
s310, obtaining at least one body characteristic data of the testee and psychological characteristic data corresponding to at least two physical and psychological evaluation scales respectively.
In one embodiment, optionally, the physical characteristic data is blood pressure data, neutrophil-lymphocyte ratio data, body mass index data, walking step number data, sedentary time data, dietary intake data, weight float data, sleep time data, or smoking amount data; the physical and mental assessment scale is symptom self-assessment scale, Essecker personality questionnaire-emotional scale, Kannel medical index scale or mood state scale-depression scale.
In one embodiment, optionally, the obtaining at least one physical characteristic data of the subject and the psychological characteristic data corresponding to at least two kinds of physical and mental evaluation scales respectively comprises: acquiring basic information data of a testee, determining at least one body characteristic parameter and at least two body and mind evaluation scales based on the basic information data, and acquiring body characteristic data respectively corresponding to the body characteristic parameters and psychological characteristic data respectively corresponding to the body and mind evaluation scales.
Wherein, the basic information data can be used to describe parameter values of basic information parameters of the testee, wherein, the basic information parameters include but are not limited to at least one of sex, age, height, weight and occupation.
In an exemplary embodiment, the psychological characteristic parameters corresponding to the at least one physical characteristic parameter and the at least two physical and mental evaluation scales respectively may form an evaluation set. For example, the evaluation set V is [ SCL-90 total score, SCL-90 number of positive items, EPQ-N total score, CMI _ M-R score, POMS depression score, psychological stress score, systolic blood pressure, diastolic blood pressure, BMI, number of steps, sedentary, weight fluctuation value, sleep, smoking ], and the set of factors U of a certain subject acquired based on the evaluation set V is [46, 37, 35, 29, 8, 13, 91, 110, 69, 18.90, 8000, 0.499, 2, 3, 0 ].
S320, determining comprehensive probability values respectively corresponding to at least two preset physical and psychological health states based on the physical characteristic data, the psychological characteristic data and the factor weight matrix.
In this embodiment, the factor weight matrix represents weight information corresponding to each physical characteristic data and each psychological characteristic data.
Here, an exemplary set of predetermined physical and mental health states includes "good state", "attention required", and "emergency intervention", and of course, a set of predetermined physical and mental health states includes "excellent state", "good state", "attention required", "regular follow-up", and "emergency intervention". The specific grade setting of the preset physical and mental health state is not limited, and the user can perform self-defined setting according to actual requirements.
In one embodiment, optionally, the factor weight matrix includes a body weight matrix corresponding to each body characteristic data, a psychological weight matrix corresponding to each psychological characteristic data, and a body psychological weight matrix, and accordingly, the determining, based on each body characteristic data, each psychological characteristic data, and the factor weight matrix, a comprehensive probability value corresponding to each of at least two preset physical and psychological health states includes: determining target body probability values respectively corresponding to at least two preset physical and psychological health states based on the body characteristic data and the body weight matrix; determining target psychological probability values respectively corresponding to at least two preset physical and psychological health states based on each psychological characteristic data and the psychological weight matrix; and determining comprehensive probability values respectively corresponding to at least two preset physical and psychological health states based on the physical probability values of the targets, the psychological probability values of the targets and the psychological weight matrix of the body.
Taking the above example as an example, the body weight matrix A body ＝[0.125，0.125，0.125，0.125，0.125，0.125，0.125，0.125]Psychological weighting matrix A mind ＝[0.037，0.148，0.148，0.185，0.111，0.185，0.185]Physical psychology weight matrix A body_mind ＝[0.377,0.623]。
In an embodiment, optionally, determining target body probability values respectively corresponding to at least two preset physical and mental health states based on the body characteristic data and the body weight matrix includes: based on a preset body evaluation list, fuzzification processing is respectively carried out on the body characteristic data to obtain a body factor matrix; determining target body probability values respectively corresponding to at least two preset physical and psychological health states based on the body factor matrix and the body weight matrix; the preset body evaluation list comprises at least one body characteristic parameter and body characteristic data ranges corresponding to each body characteristic parameter and at least two preset physical and mental health states respectively, and the body factor matrix represents initial body probability values corresponding to each body characteristic data and the at least two preset physical and mental health states respectively.
Table 1 is a preset body evaluation list provided in the third embodiment of the present invention.
Table 1 explains a set of predetermined physical and mental health states including "good state", "attention is required", and "emergency intervention" as an example. The "μ" and "σ" in table 1 were obtained by fitting normal distribution to the subject population data. It should be noted that table 1 is only exemplary explained, and does not limit the physical characteristic data range corresponding to each physical characteristic parameter, and the user can perform custom setting according to actual requirements.
Taking the above example as an example, the body factor matrix R body A matrix of 8 x 3, R body ＝[0.720，0.250，0.030；0.902，0.088，0.011；0.590，0.366，0.044；0.956，0.040，0.005；0.882，0.106，0.013；0.644，0.318，0.038；0，0，1；1，0，0]. Body factor matrix R body And the body weight matrix A body Multiplying to obtain a body membership matrix B body ＝[0.7118，0.1457，0.1425]And the body membership degree matrix is used for representing target body probability values respectively corresponding to at least two preset physical and psychological health states.
In an embodiment, optionally, determining target psychological probability values respectively corresponding to at least two preset physical and mental health states based on each psychological characteristic data and the psychological weight matrix includes: performing fuzzification processing on each psychological characteristic data respectively based on a preset psychological evaluation list to obtain a psychological factor matrix; determining target psychological probability values respectively corresponding to at least two preset physical and psychological health states based on the psychological factor matrix and the psychological weight matrix; the preset psychological evaluation list comprises at least one psychological characteristic parameter and psychological characteristic data ranges corresponding to each psychological characteristic parameter and at least two preset physical and mental health states respectively, and the psychological factor matrix represents initial psychological probability values corresponding to each psychological characteristic data and at least two preset physical and mental health states respectively.
Table 2 is a preset psychological evaluation list provided in the third embodiment of the present invention.
Table 2 explains a set of predetermined physical and mental health states including "good state", "attention is required", and "emergency intervention" as an example. It should be noted that table 2 is only exemplary for explanation, and does not limit the range of the psychological characteristic data corresponding to each psychological characteristic parameter, and the user can perform custom setting according to actual needs.
Taking the above example as an example, the psychological factor matrix R mind Is a 7 x 3 matrix, R mind ＝[0.997，0.002，0.000；0.129，0.569，0.301；0.975，0.022，0.003；0.356，0.544，0.100；0.989，0.100，0.001；0.375，0.534，0.092；0.966，0.030，0.004]. Psychological factor matrix R mind And the psychological weight matrix A mind After multiplication, obtaining a psychological membership matrix B mind ＝[0.6248，0.2940，0.0812]And the psychological membership matrix is used for representing target psychological probability values respectively corresponding to at least two preset physical and psychological health states.
Taking the above example as an example, the physical membership matrix and the psychological membership matrix are formed into a 3 x 2 probability matrix, and the probability matrix and the physical psychological weight matrix a body_mind Multiplying to obtain a 3 x 1 matrix, wherein each row of the matrix represents a comprehensive probability value corresponding to 3 preset physical and psychological health states respectively. An evaluation matrix evaluate _ matrix [0.6596, 0.2347, 0.1057 ] formed by the integrated probability values corresponding to the 3 predetermined physical and mental health states, respectively]。
S330, taking the preset physical and mental health state corresponding to the maximum comprehensive probability value as a target physical and mental health state, and displaying a physical and mental health evaluation report corresponding to the target physical and mental health state.
Taking the above example as an example, the target physical and mental health state is "state good".
Fig. 4 is a flowchart of a specific example of a method for evaluating physical and mental health according to a third embodiment of the present invention. Specifically, after evaluation is started, basic information data of a subject is first acquired, in fig. 4, taking an example that basic information parameters include gender, when the gender of the subject is "female", a female evaluation list corresponding to "female" in a preset mapping list is acquired, when the gender of the subject is "male", a male evaluation list corresponding to "male" in the preset mapping list is acquired, and an evaluation set is constructed based on the acquired evaluation lists, wherein the evaluation set includes at least one body characteristic parameter and at least one psychological characteristic parameter corresponding to at least two kinds of physical and mental evaluation scales respectively. Obtaining a factor set of the subject based on the evaluation set, wherein the factor set comprises at least one body characteristic data and at least two physical and mental evaluation measurementsThe tables respectively correspond to psychological characteristic data. Based on a preset body evaluation list, fuzzification processing is respectively carried out on each body characteristic data to obtain a body factor matrix R 1 A matrix R of body factors 1 And the body weight matrix A 1 Multiplying to obtain a body membership matrix B 1 . Meanwhile, based on a preset psychological evaluation list, fuzzification processing is respectively carried out on each psychological characteristic data to obtain a psychological factor matrix R 2 The psychological factor matrix R 2 And the psychological weight matrix A 2 Multiplying to obtain a psychological membership matrix B 2 . Membership matrix B of body 1 And a psychological membership matrix B 2 And multiplying the formed matrix by a body psychological weight matrix H to obtain an evaluation matrix. The evaluation matrix represents comprehensive probability values corresponding to at least two preset physical and mental health states respectively, the preset physical and mental health state corresponding to the maximum comprehensive probability value is used as a target physical and mental health state, and a physical and mental health evaluation report corresponding to the target physical and mental health state is displayed.
According to the technical scheme of the embodiment, at least one body characteristic data of the testee and the psychological characteristic data corresponding to at least two body and mind evaluation scales are obtained, the comprehensive probability values corresponding to at least two preset body and mind health states are determined based on the body characteristic data, the psychological characteristic data and the factor weight matrix, the preset body and mind health state corresponding to the maximum comprehensive probability value is used as the target body and mind health state corresponding to the testee, the problem that the evaluation result of a single body and mind evaluation scale is easily influenced by subjective factors is solved, and the accuracy of the body and mind health evaluation result is improved.
Example four
Fig. 5 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present invention. The electronic device 10 is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 5, the electronic device 10 includes at least one processor 11, and a memory communicatively connected to the at least one processor 11, such as a Read Only Memory (ROM)12, a Random Access Memory (RAM)13, and the like, wherein the memory stores a computer program executable by the at least one processor, and the processor 11 can perform various suitable actions and processes according to the computer program stored in the Read Only Memory (ROM)12 or the computer program loaded from a storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data necessary for the operation of the electronic apparatus 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to the bus 14.
A number of components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, or the like; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, or the like. The processor 11 performs the various methods and processes described above, such as a method of physical and mental health assessment.
In some embodiments, the wellness evaluation method may be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When loaded into RAM 13 and executed by processor 11, the computer program may perform one or more of the steps of the method for assessing physical and mental health described above. Alternatively, in other embodiments, the processor 11 may be configured to perform the wellness evaluation method in any other suitable way (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
The computer program for implementing the method for assessing physical and mental health of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be performed. A computer program can execute entirely on a machine, partly on a machine, as a stand-alone software package partly on a machine and partly on a remote machine or entirely on a remote machine or server.
EXAMPLE five
An embodiment of the present invention further provides a computer-readable storage medium, where a computer instruction is stored in the computer-readable storage medium, and the computer instruction is used to enable a processor to execute a method for evaluating physical and mental health, where the method includes:
acquiring at least one body characteristic data of a testee and psychological characteristic data respectively corresponding to at least two physical and psychological evaluation scales;
determining comprehensive probability values respectively corresponding to at least two preset physical and psychological health states based on the physical characteristic data, the psychological characteristic data and the factor weight matrix; the factor weight matrix represents weight information corresponding to each body characteristic data and each psychological characteristic data respectively;
and taking the preset physical and mental health state corresponding to the maximum comprehensive probability value as a target physical and mental health state, and displaying a physical and mental health evaluation report corresponding to the target physical and mental health state.
In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical host and VPS service are overcome.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present invention may be executed in parallel, sequentially, or in different orders, and are not limited herein as long as the desired results of the technical solution of the present invention can be achieved.
The above-described embodiments should not be construed as limiting the scope of the invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A physical and mental health evaluation system, comprising: the system comprises a characteristic data collection module, a physical and mental health state evaluation module and a physical and mental health evaluation report display module;
the characteristic data collection module is used for obtaining at least one body characteristic data of a tested person and psychological characteristic data corresponding to at least two physical and psychological evaluation scales respectively;
the physical and mental health state evaluating module is used for determining comprehensive probability values respectively corresponding to at least two preset physical and mental health states based on the physical characteristic data, the psychological characteristic data and the factor weight matrix; the factor weight matrix represents weight information corresponding to each physical characteristic data and each psychological characteristic data;
and the physical and mental health evaluation report display module is used for taking the preset physical and mental health state corresponding to the maximum comprehensive probability value as a target physical and mental health state and displaying the physical and mental health evaluation report corresponding to the target physical and mental health state.
2. The system according to claim 1, wherein the factor weight matrix comprises a body weight matrix corresponding to each of the body characteristic data, a psychological weight matrix corresponding to each of the psychological characteristic data, and a body psychological weight matrix, and the physical and psychological health status evaluating module comprises:
a body probability value determining unit, configured to determine target body probability values corresponding to at least two preset physical and mental health states, respectively, based on each of the body feature data and the body weight matrix;
a psychological probability value determining unit, configured to determine target psychological probability values corresponding to at least two preset physical and psychological health states, respectively, based on each of the psychological characteristic data and the psychological weight matrix;
and the comprehensive probability value determining unit is used for determining comprehensive probability values respectively corresponding to at least two preset physical and mental health states based on the target body probability values, the target psychological probability values and the body psychological weight matrix.
3. The system according to claim 2, characterized in that the body probability value determination unit is specifically configured to:
based on a preset body evaluation list, performing fuzzification processing on the body characteristic data respectively to obtain a body factor matrix;
determining target body probability values respectively corresponding to at least two preset physical and psychological health states based on the body factor matrix and the body weight matrix;
the preset body evaluation list comprises at least one body characteristic parameter and body characteristic data ranges corresponding to each body characteristic parameter and at least two preset physical and mental health states respectively, and the body factor matrix represents initial body probability values corresponding to each body characteristic data and the at least two preset physical and mental health states respectively.
4. The system according to claim 2, wherein the psychological probability value determining unit is specifically configured to:
performing fuzzification processing on each psychological characteristic data respectively based on a preset psychological evaluation list to obtain a psychological factor matrix;
determining target psychological probability values respectively corresponding to at least two preset physical and psychological health states based on the psychological factor matrix and the psychological weight matrix;
the preset psychological evaluation list comprises at least one psychological characteristic parameter and a psychological characteristic data range corresponding to each psychological characteristic parameter and at least two preset physical and mental health states respectively, and the psychological factor matrix represents initial psychological probability values corresponding to each psychological characteristic data and at least two preset physical and mental health states respectively.
5. The system according to claim 2, wherein the physical and mental health status evaluation module further comprises a factor weight matrix determination unit for:
determining a factor weight matrix by adopting a chromatography analysis method based on the comparison judgment matrix; the comparison and judgment matrix represents the importance degree between every two factors, and comprises a body comparison matrix corresponding to at least two types of body characteristic data, a psychological comparison matrix corresponding to at least two types of psychological characteristic data and a body psychological comparison matrix.
6. The system according to claim 1, further comprising a basic data collecting module for obtaining basic information data of the subject and sending at least one physical characteristic parameter and at least two psychometric scales determined based on the basic information data to the characteristic data collecting module.
7. The system according to any one of claims 1 to 6, wherein the physical characteristic data is blood pressure data, neutrophil-lymphocyte ratio data, body mass index data, walking step number data, sedentary time data, dietary intake data, body weight floating amount data, sleep time data, or smoking amount data, and the psychometric scale is a symptom self-rating scale, an Esselness questionnaire-mood scale, a Kannel medical index scale, a mood state scale-depression scale, or a university student mental stress scale.
8. A physical and mental health evaluation method is characterized by comprising the following steps:
acquiring at least one body characteristic data of a testee and psychological characteristic data respectively corresponding to at least two physical and psychological evaluation scales;
determining comprehensive probability values respectively corresponding to at least two preset physical and psychological health states based on the physical characteristic data, the psychological characteristic data and the factor weight matrix; the factor weight matrix represents weight information corresponding to each physical characteristic data and each psychological characteristic data respectively;
and taking the preset physical and mental health state corresponding to the maximum comprehensive probability value as a target physical and mental health state, and displaying a physical and mental health evaluation report corresponding to the target physical and mental health state.
9. An electronic device, characterized in that the electronic device comprises:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the method of assessing physical and mental health of claim 8.
10. A computer-readable storage medium storing computer instructions for causing a processor to execute the method for assessing physical and mental health of claim 8.
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