Health assessment system and method based on AI and human physiological characteristics data

Abstract

The present invention belongs to the field of health assessment technology, and provides a health assessment system and method based on AI and human physiological characteristic data. The method includes: obtaining the first physiological characteristic data of the assessed object in the first time period, and determining the first adjustment coefficient value based on the first adjustment coefficient value and the second physiological characteristic data; obtaining the second physiological characteristic data of the assessed object in the second time period, and determining the second adjustment coefficient value based on the first adjustment coefficient value and the second physiological characteristic data; obtaining the third physiological characteristic data of the assessed object in the third time period, and using the AI ​​assessment model to evaluate the third physiological characteristic data to obtain a first health assessment value; correcting the first health assessment value according to the second adjustment coefficient value to obtain a second health assessment value; and generating a health assessment report based on the second health assessment value. The present invention comprehensively evaluates the physiological characteristic data during the assessment process and the physiological characteristic data before the assessment begins, which can reduce the influence of interference factors and has higher accuracy.

Description

Technical Field

[0001] The present invention relates to the field of health assessment technology, and in particular to a health assessment system and method based on AI and human physiological characteristic data. Background Art

[0002] Health assessment is an important part of medical diagnosis assistance, physical examination and other fields. Health assessment can help relevant personnel understand the physical health status of the person being assessed, thereby assisting them in subsequent operations such as treatment and recuperation.

[0003] After searching, the following existing patents related to health assessment were found: A health assessment system and health assessment method (CN115530833A): A health assessment system, including: an assessment chair assembly, configured to measure the subject's grip strength, heart rate, number of leg lifts, and sit-up status; a gait guidance assembly, the gait guidance assembly is configured to guide the subject to present a preset gait; and a trail, the trail is configured to measure the subject's walking speed. In the health assessment system of the embodiment of the present application, each test has a corresponding device for testing, and there is no need to post a test mark, thereby improving the assessment environment. The normal test process requires almost no participation of the assessor, reducing the labor intensity of the assessor, reducing manpower consumption, and the test results are more objective.

[0004] Cloud-based medical health assessment system and method for the elderly (CN106169031A): A cloud-based medical health assessment system for the elderly, applied to a health assessment server, the health assessment server is connected to at least one client terminal through a network, the client terminal is installed with an application that can access the health assessment server, the medical health assessment system for the elderly includes: an assessment scale establishment module, used to generate an assessment file for the user according to the user information sent from the client terminal, the user information includes the user's basic information and health information, the assessment file includes a plurality of health assessment scales; a preliminary assessment module, used to evaluate each of the health assessment scales according to a preset preliminary assessment standard The table is used for preliminary evaluation, and the preliminary evaluation result of each health evaluation scale is obtained and it is judged whether the corresponding health evaluation scale needs to be comprehensively evaluated; the comprehensive evaluation module is used to load the health evaluation scale that needs to be comprehensively evaluated, and then the health status of the user is comprehensively evaluated according to the health information contained in each loaded health evaluation scale and a comprehensive evaluation result is generated; the evaluation result generation module is used to write the preliminary evaluation result and the comprehensive evaluation result into a predetermined template file and generate an evaluation result file; the report export module is used to convert the evaluation result file into a health evaluation result report in a predetermined file format and then export and save it; the result feedback module is used to feed back the health evaluation report to the client terminal through the network. The cloud-based elderly medical health evaluation system and the elderly medical health evaluation method provided by the present invention receive user information sent by the client terminal through the network by the health evaluation server, generate an evaluation file including multiple health evaluation scales according to the user information, and then evaluate the health evaluation scale according to the preset evaluation criteria, obtain the evaluation result file and generate the corresponding report, and then feed back the report file to the client terminal. The entire health assessment process is completed by a health assessment server set up in the cloud. Users only need to establish communication with the health assessment server through the client terminal to complete the health assessment remotely. The assessment is fast and efficient, making the user's health assessment simpler and more convenient.

[0005] Medical health assessment system and method for the elderly (CN106295154A): A medical health assessment system for the elderly is applied to a computer device, and the medical health assessment system for the elderly includes: an assessment scale establishment module, which is used to generate an assessment file for the user according to user information input from the input and output device of the computer device, wherein the user information includes basic information and health information of the user, and the assessment file includes multiple health assessment scales; a preliminary assessment module, which is used to perform a preliminary assessment on each of the health assessment scales according to a preset preliminary assessment standard, obtain a preliminary assessment result of each health assessment scale and determine whether a comprehensive assessment is required for the corresponding health assessment scale; a comprehensive assessment module, which is used to load a health assessment scale that needs to be comprehensively assessed, and then perform a comprehensive assessment on the health status of the user according to the health information contained in each loaded health assessment scale and generate a comprehensive assessment result; an assessment result generation module, which is used to write the preliminary assessment result and the comprehensive assessment result into a predetermined template file and generate an assessment result file; a report export module, which is used to convert the assessment result file into a health assessment result report in a predetermined file format and then export and save it.

[0006] It can be seen that the above-mentioned existing patents mainly focus on the design and construction of health assessment systems, equipment or platforms, and lack detailed processing of assessment methods and assessment data, resulting in insufficient accuracy of the assessment results, making it difficult to provide effective assistance to relevant personnel in diagnosis, treatment, rehabilitation and other aspects. Summary of the invention

[0007] In this regard, the present invention provides a health assessment method, system, electronic device, computer storage medium and computer program product based on AI and human physiological characteristic data to solve the above-mentioned technical problems.

[0008] The present invention provides a health assessment method based on AI and human physiological characteristic data, including the following method steps: obtaining first physiological characteristic data of an assessed object within a first time period, and determining a first adjustment coefficient value based on the first physiological characteristic data; obtaining second physiological characteristic data of the assessed object within a second time period, and determining a second adjustment coefficient value based on the first adjustment coefficient value and the second physiological characteristic data; wherein the first time period and the second time period are located before a formal assessment time period; obtaining third physiological characteristic data of the assessed object within a third time period, and evaluating the third physiological characteristic data using an AI assessment model to obtain a first health assessment value; wherein the third time period is located within the formal assessment time period; correcting the first health assessment value based on the second adjustment coefficient value to obtain a second health assessment value; and generating a health assessment report based on the second health assessment value.

[0009] In some embodiments, the method of obtaining the first physiological characteristic data of the evaluated object within the first time period and determining the first adjustment coefficient value based on the first physiological characteristic data includes: determining multiple first time periods based on the third time period; obtaining the first sub-physiological characteristic data within the first sub-time period in each first time period, fitting the first sub-physiological characteristic data to obtain a physiological fluctuation curve, and when the physiological fluctuation curve meets specified conditions, obtaining the second sub-physiological characteristic data within the second sub-time period adjacent to the first sub-time period; using each of the second sub-physiological characteristic data as the first physiological characteristic data, and determining the first adjustment coefficient value based on each of the second sub-physiological characteristic data.

[0010] In some embodiments, judging whether the physiological fluctuation curve meets specified conditions includes: determining a smoothing parameter according to the layout position of the evaluation device body, and determining a first smoothing curve according to the smoothing parameter; wherein the first smoothing curve includes a first fluctuation curve and a second fluctuation curve connected in sequence, and the smoothing parameter includes a first amplitude, a curvature and a corresponding first time characteristic of the first fluctuation curve, and a second amplitude and a corresponding second time characteristic of the second fluctuation curve; calculating a first similarity between the physiological fluctuation curve and the first smoothing curve, and if the first similarity is greater than or equal to a first similarity threshold, determining that the physiological fluctuation curve meets the specified conditions.

[0011] In some embodiments, determining the first adjustment coefficient value based on each of the second sub-physiological characteristic data includes: calculating the difference between each of the second sub-physiological characteristic data, and then calculating the average value of the difference between each of the differences; determining the first adjustment coefficient value based on the average value of the difference according to a positive correlation.

[0012] In some embodiments, the method of obtaining the second physiological characteristic data of the evaluated object in the second time period, and determining the second adjustment coefficient value according to the first adjustment coefficient value and the second physiological characteristic data, includes: obtaining the second physiological characteristic data of the evaluated object in the second time period, and fitting a second smoothing curve according to the second physiological characteristic data; wherein the second time period is closer to the third time period than the first time period; calculating the second similarity between the second smoothing curve and the third smoothing curve, and if the second similarity is greater than or equal to a second similarity threshold, setting the second adjustment coefficient value to the first value; otherwise, setting the second adjustment coefficient value to the second value; wherein the third smoothing curve is obtained by fitting the first smoothing curves, and the first value is less than the second value; and the second similarity threshold is determined according to the first adjustment coefficient value.

[0013] In some embodiments, the second similarity threshold is determined according to the first adjustment coefficient value, including: the second similarity threshold is positively correlated with the first adjustment coefficient value.

[0014] In some embodiments, generating a health assessment report based on the second health assessment value includes: calling a health assessment report template according to an assessment target; filling each of the second health assessment values ​​into a designated item of the health assessment report template, and deriving the result assessment content associated with the designated item based on the second health assessment value; integrating and generating a health assessment report.

[0015] The present invention also provides a health assessment system based on AI and human physiological characteristic data, including an intelligent wearable device and an assessment device body; the intelligent wearable device includes a plurality of physiological sensors and a first communication device; the physiological sensors are used to detect and obtain the human physiological characteristic data of the assessed object at different time periods; the first communication device is used to send the human physiological characteristic data to the assessment device body; the assessment device body includes a processing module, a storage module and a second communication device; the second communication device is used to receive the human physiological characteristic data and forward it to the processing module; the storage module stores a computer program; the processing module is used to retrieve and execute the computer program in the storage module to execute any of the methods described above and output a health assessment report.

[0016] The present invention also provides an electronic device, comprising: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor executes the computer program to implement any of the methods described above.

[0017] The present invention provides a computer storage medium, wherein the computer-readable storage medium stores a computer program, and is characterized in that: the computer program is executed by a processor to implement any of the above methods.

[0018] The present invention also provides a computer program product. When the computer program product is run on a terminal, the terminal implements any of the above methods when executing the computer program product.

[0019] The beneficial effect of the present invention is that the scheme of the present invention not only relies on the physiological characteristic data during the evaluation process, but also takes into account the physiological characteristic data before the evaluation begins, which can reduce the influence of certain interference factors and make the evaluation result more accurate and objective. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0021] Figure 1 It is a flowchart of a health assessment method based on AI and human physiological characteristic data disclosed in an embodiment of the present invention.

[0022] Figure 2 It is a structural schematic diagram of a health assessment system based on AI and human physiological characteristic data disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0023] The following is a description of the implementation of the present application by specific specific embodiments. People familiar with the technology can easily understand other advantages and effects of the present application from the contents disclosed in this specification. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0024] In addition, the technical features involved in the different embodiments of the present application described below can be combined with each other as long as they do not conflict with each other.

[0025] like Figure 1 As shown, an embodiment of the present invention discloses a health assessment method based on AI and human physiological characteristic data, including the following steps: obtaining first physiological characteristic data of an assessed object within a first time period, and determining a first adjustment coefficient value based on the first physiological characteristic data; obtaining second physiological characteristic data of an assessed object within a second time period, and determining a second adjustment coefficient value based on the first adjustment coefficient value and the second physiological characteristic data; wherein the first time period and the second time period are located before a formal assessment time period; obtaining third physiological characteristic data of an assessed object within a third time period, and evaluating the third physiological characteristic data using an AI assessment model to obtain a first health assessment value; wherein the third time period is located within a formal assessment time period; correcting the first health assessment value based on the second adjustment coefficient value to obtain a second health assessment value; and generating a health assessment report based on the second health assessment value.

[0026] The implementation of the health assessment scheme of the present invention relies on an intelligent wearable device, which includes a physiological characteristic data detection module, a processing module, a communication module and other auxiliary modules, wherein the physiological characteristic data detection module includes a variety of detection sensors, which can realize the measurement of physiological parameters such as heart rate, blood pressure, blood sugar, body temperature, etc.; when used, it is equipped on the body of the object being assessed, such as the wrist, thigh, arm, heart position, etc. The assessment method of the present invention is implemented based on the physiological characteristic data of three time periods. Specifically, the corresponding adjustment coefficient value is obtained based on the physiological characteristic data of the first time period and the second time period before the formal assessment period of the object being assessed. Then, the third physiological characteristic data of the object being assessed is obtained in the formal assessment period, that is, the third time period, and the corresponding health assessment value is obtained by using the trained AI assessment model to evaluate, and then the aforementioned adjustment coefficient value is used to correct the health assessment value, and finally a more accurate health assessment value is obtained, thereby generating a more accurate health assessment report. Therefore, the scheme of the present invention not only relies on the physiological characteristic data in the assessment process, but also takes into account the physiological characteristic data before the assessment begins, which can reduce the influence of certain interference factors and make the assessment result more accurate and objective.

[0027] In addition, the implementation of the health assessment scheme of the present invention also relies on the assessment device body, which is mainly used to communicate with the smart wearable device to obtain the physiological characteristic data detected by it at different time periods, and then process these physiological characteristic data in the above manner to obtain the final health assessment value, and generate a health assessment report accordingly. The assessment device body can be set up in a medical institution or at the residence of the person being assessed.

[0028] In some embodiments, the method of obtaining the first physiological characteristic data of the evaluated object within the first time period and determining the first adjustment coefficient value based on the first physiological characteristic data includes: determining multiple first time periods based on the third time period; obtaining the first sub-physiological characteristic data within the first sub-time period in each first time period, fitting the first sub-physiological characteristic data to obtain a physiological fluctuation curve, and when the physiological fluctuation curve meets specified conditions, obtaining the second sub-physiological characteristic data within the second sub-time period adjacent to the first sub-time period; using each of the second sub-physiological characteristic data as the first physiological characteristic data, and determining the first adjustment coefficient value based on each of the second sub-physiological characteristic data.

[0029] In the embodiment of the present invention, since people's lives are usually regular, and such regular activities will have a certain impact on certain physiological parameters, which may cause the health assessment to be distorted. In this regard, the present invention is set to determine multiple first time periods based on the formal evaluation period, that is, the third time period. For example, the third time period is 8:00-8:20 am on the 12th, and 8:00-8:20 am on the 8th to 11th is taken as the first time period; of course, the similarity of dates can also be specifically considered, such as working days and holidays, which will not be described in detail. Then, the sub-physiological characteristic data is obtained for the first part of each first time period, and the curve characteristics of its physiological fluctuation curve are analyzed. When the curve characteristics meet certain conditions, it is determined that the physiological characteristics of the evaluated object at this time are similar to the physiological characteristics of the formal evaluation period, and have reference value, and are retained; otherwise, the first sub-physiological characteristic data is obtained again and the above analysis is performed after a certain period of iteration until the conditions are met, and the sub-physiological characteristic data of the second sub-time period is obtained. In addition, when the subsequent iteration exceeds the above-mentioned 8:00-8:20 period, the first period can be abandoned, that is, the physiological characteristic data thereof is no longer analyzed. Finally, the first adjustment coefficient value is determined based on the above-mentioned plurality of second sub-physiological characteristic data.

[0030] In some embodiments, judging whether the physiological fluctuation curve meets specified conditions includes: determining a smoothing parameter according to the layout position of the evaluation device body, and determining a first smoothing curve according to the smoothing parameter; wherein the first smoothing curve includes a first fluctuation curve and a second fluctuation curve connected in sequence, and the smoothing parameter includes a first amplitude, a curvature and a corresponding first time characteristic of the first fluctuation curve, and a second amplitude and a corresponding second time characteristic of the second fluctuation curve; calculating a first similarity between the physiological fluctuation curve and the first smoothing curve, and if the first similarity is greater than or equal to a first similarity threshold, determining that the physiological fluctuation curve meets the specified conditions.

[0031] In an embodiment of the present invention, the evaluated object generally performs physiological calming (e.g., sitting in meditation) before the formal evaluation. Therefore, the physiological curve of the evaluated object before the evaluation begins includes two parts, namely, the aforementioned first fluctuation curve and the second fluctuation curve. The first fluctuation curve is mainly an ascending curve of the physiological characteristic data (caused by exercise), and the second fluctuation curve is a stable curve corresponding to the calming process (basically in a flat state). In view of the fact that the physiological characteristic curve of the evaluated object meets the characteristics of the above-mentioned calming curve during the actual evaluation, the present invention determines the specified conditions based on the above-mentioned calming curve, that is, to determine whether the first sub-physiological characteristic data in the first sub-period has a high similarity with the calming curve (mainly involving the similarity of the curve trend). If so, it is retained for use.

[0032] In addition, the location of the evaluation device body will affect the calming parameters. Specifically, the evaluation device body may be arranged in a medical institution or in the home of the evaluated object. In the former case, the evaluated object needs to spend more physical energy to go to the medical institution. The larger amount of exercise in the process will have a greater interference effect on the physiological characteristic data of the evaluated object; while in the latter case, the amount of exercise (such as housework) of the evaluated object is significantly smaller, and the interference effect on the physiological characteristic data is smaller. Therefore, when the evaluation device body is arranged in a medical institution, the first amplitude (which may be the maximum amplitude in the first fluctuation curve), the curvature and the corresponding first time feature can be adjusted to make the first fluctuation curve steeper and last longer; when the evaluation device body is arranged in the home of the evaluated object, the first amplitude, curvature and the corresponding first time feature can be adjusted to make the first fluctuation curve smoother and last shorter. In addition, the second amplitude and the corresponding second time feature of the second fluctuation curve can be obtained based on a large amount of statistical data, mainly describing the physiological characteristic curve of a normal person in a calm state, or based on the historical data of the evaluated object, which is more accurate.

[0033] It should be noted that the similarity can be calculated using an existing method without any specific limitation.

[0034] In some embodiments, determining the first adjustment coefficient value based on each of the second sub-physiological characteristic data includes: calculating the difference between each of the second sub-physiological characteristic data, and then calculating the average value of the difference between each of the differences; determining the first adjustment coefficient value based on the average value of the difference according to a positive correlation.

[0035] In the embodiment of the present invention, the difference between the two and the average difference value are calculated for the plurality of second sub-physiological characteristic data collected in the earlier time period. The larger the average difference value, the greater the fluctuation of the physiological characteristic data of the assessed object in normal times, and the greater the impact on the accuracy of this health assessment, and the corresponding first adjustment coefficient value is set to be larger; otherwise, the first adjustment coefficient value is set to be smaller.

[0036] In some embodiments, the method of obtaining the second physiological characteristic data of the evaluated object in the second time period, and determining the second adjustment coefficient value according to the first adjustment coefficient value and the second physiological characteristic data, includes: obtaining the second physiological characteristic data of the evaluated object in the second time period, and fitting a second smoothing curve according to the second physiological characteristic data; wherein the second time period is closer to the third time period than the first time period; calculating the second similarity between the second smoothing curve and the third smoothing curve, and if the second similarity is greater than or equal to a second similarity threshold, setting the second adjustment coefficient value to the first value; otherwise, setting the second adjustment coefficient value to the second value; wherein the third smoothing curve is obtained by fitting the first smoothing curves, and the first value is less than the second value; and the second similarity threshold is determined according to the first adjustment coefficient value.

[0037] In an embodiment of the present invention, the evaluated object is generally required to sit in meditation for a certain period of time before the formal evaluation to calm down various physiological parameters. However, due to insufficient calming time, failure to strictly sit in meditation or other factors, the calming target may not reach the expected level, resulting in the physiological characteristic data in the formal evaluation stage not being able to reflect normal health conditions. In this regard, the present invention obtains the second calming curve in the calming stage by fitting, and calculates its similarity with the third calming curve (equivalent curve of each first calming curve) (involving the similarity of curve trend and amplitude). If the similarity is high enough, it means that the physiological characteristic data at the end of the second period has entered the second fluctuation curve and the degree of entry is large, that is, the evaluated object is sufficiently "calmed" at this time, and the second adjustment coefficient value is set to the first value (for example, 1), and the first health assessment value in the formal evaluation stage is used as the standard; otherwise, it means that the physiological characteristic data at the end of the second period has not entered the second fluctuation curve or the degree of entry is insufficient, and the second adjustment coefficient value is set to the second value (a value less than 1) to reduce the abnormality of the health assessment value in the formal evaluation stage.

[0038] The first value may be a fixed value, and the second value may be a non-fixed value. Specifically, the second value may be negatively correlated to increase according to the extent to which the second similarity is less than the second similarity threshold, that is, the closer it is to 1.

[0039] In some embodiments, the second similarity threshold is determined according to the first adjustment coefficient value, including: the second similarity threshold is positively correlated with the first adjustment coefficient value.

[0040] In the embodiment of the present invention, the first adjustment coefficient reflects the fluctuation range of the physiological characteristics of the evaluated object in daily life. Therefore, the larger the fluctuation range, the lower the credibility of the first smooth curve and the subsequent third smooth curve. At this time, the second similarity threshold needs to be set larger to ensure that the evaluated object has entered the second fluctuation curve in the smooth stage and the degree of entry is large, that is, it has been sufficiently "smoothed". Otherwise, the second similarity threshold is set smaller.

[0041] In some embodiments, generating a health assessment report based on the second health assessment value includes: calling a health assessment report template according to an assessment target; filling each of the second health assessment values ​​into a designated item of the health assessment report template, and deriving the result assessment content associated with the designated item based on the second health assessment value; integrating and generating a health assessment report.

[0042] In an embodiment of the present invention, a variety of health assessment report templates are pre-stored in the system, and the corresponding template can be called according to the purpose of this assessment; then the second health assessment value obtained above is filled into the corresponding entry, and the corresponding result assessment content can be determined according to the preset assessment criteria and the second health assessment value; finally, all the contents are integrated to obtain a complete health assessment report.

[0043] like Figure 2 As shown, an embodiment of the present invention also discloses a health assessment system based on AI and human physiological characteristic data, including an intelligent wearable device and an assessment device body; the intelligent wearable device includes a plurality of physiological sensors and a first communication device; the physiological sensor is used to detect and obtain the human physiological characteristic data of the assessed object at different time periods; the first communication device is used to send the human physiological characteristic data to the assessment device body; the assessment device body includes a processing module, a storage module and a second communication device; the second communication device is used to receive the human physiological characteristic data and forward it to the processing module; the storage module stores a computer program; the processing module is used to retrieve and execute the computer program in the storage module to execute the method of the aforementioned embodiment and output a health assessment report.

[0044] An embodiment of the present invention further discloses an electronic device, comprising: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, characterized in that: the processor executes the computer program to implement the method described in the above embodiment.

[0045] An embodiment of the present invention further discloses a computer storage medium, wherein the computer-readable storage medium stores a computer program, and is characterized in that: the computer program is executed by a processor to implement the method described in the above embodiment.

[0046] The embodiment of the present invention further discloses a computer program product. When the computer program product is run on a terminal, the terminal implements the method described in the above embodiment.

[0047] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0048] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0049] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0050] The above description is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention.

Claims

1. A health assessment method based on AI and human physiological characteristics data, characterized by: The method includes the following steps: obtaining the first physiological characteristic data of the evaluated object in the first time period, and determining a first adjustment coefficient value according to the first physiological characteristic data; obtaining the second physiological characteristic data of the evaluated object in the second time period, and determining a second adjustment coefficient value according to the first adjustment coefficient value and the second physiological characteristic data; wherein the first time period and the second time period are located before the formal evaluation time period; obtaining the third physiological characteristic data of the evaluated object in the third time period, and using the AI ​​evaluation model to evaluate the third physiological characteristic data to obtain a first health evaluation value; wherein the third time period is located in the formal evaluation time period; correcting the first health evaluation value according to the second adjustment coefficient value to obtain a second health evaluation value; generating a health evaluation report according to the second health evaluation value; Wherein, obtaining the first physiological characteristic data of the evaluated object in the first time period, and determining the first adjustment coefficient value according to the first physiological characteristic data, includes: determining multiple first time periods according to the third time period; obtaining the first sub-physiological characteristic data in the first sub-time period in each first time period, fitting the first sub-physiological characteristic data to obtain a physiological fluctuation curve, and when the physiological fluctuation curve meets the specified conditions, obtaining the second sub-physiological characteristic data in the second sub-time period adjacent to the first sub-time period; taking each of the second sub-physiological characteristic data as the first physiological characteristic data, and determining the first adjustment coefficient value according to each of the second sub-physiological characteristic data; Wherein, determining the first adjustment coefficient value according to each of the second sub-physiological characteristic data includes: calculating the difference between each of the second sub-physiological characteristic data, and then calculating the average value of the difference of each of the difference values; determining the first adjustment coefficient value according to the average value of the difference according to a positive correlation relationship; Among them, obtaining the second physiological characteristic data of the evaluated object in the second time period, and determining the second adjustment coefficient value according to the first adjustment coefficient value and the second physiological characteristic data, includes: obtaining the second physiological characteristic data of the evaluated object in the second time period, and fitting a second smoothing curve according to the second physiological characteristic data; wherein the second time period is closer to the third time period than the first time period; calculating the second similarity between the second smoothing curve and the third smoothing curve, if the second similarity is greater than or equal to the second similarity threshold, setting the second adjustment coefficient value to the first value; otherwise, setting the second adjustment coefficient value to the second value; wherein the third smoothing curve is obtained by fitting the first smoothing curves, and the first value is less than the second value, wherein the smoothing parameters are determined according to the layout position of the evaluation device body, and the first smoothing curve is determined according to the smoothing parameters; and the second similarity threshold is determined according to the first adjustment coefficient value.

2. A health assessment method based on AI and human physiological characteristic data according to claim 1, characterized in that: Judging whether the physiological fluctuation curve meets the specified conditions includes: the first smoothing curve includes a first fluctuation curve and a second fluctuation curve connected in sequence, the smoothing parameters include a first amplitude, a curvature and a corresponding first time feature of the first fluctuation curve, and a second amplitude and a corresponding second time feature of the second fluctuation curve; calculating a first similarity between the physiological fluctuation curve and the first smoothing curve, and if the first similarity is greater than or equal to a first similarity threshold, determining that the physiological fluctuation curve meets the specified conditions.

3. A health assessment method based on AI and human physiological characteristic data according to claim 2, characterized in that: The second similarity threshold is determined according to the first adjustment coefficient value, including: the second similarity threshold is positively correlated with the first adjustment coefficient value.

4. A health assessment system based on AI and human physiological characteristic data, comprising an intelligent wearable device and an assessment device body; the intelligent wearable device comprises a plurality of physiological sensors and a first communication device; the physiological sensors are used to detect and obtain the human physiological characteristic data of the assessed object at different time periods; the first communication device is used to send the human physiological characteristic data to the assessment device body; the assessment device body comprises a processing module, a storage module and a second communication device; the second communication device is used to receive the human physiological characteristic data and forward it to the processing module; the storage module stores a computer program; the characteristics are as follows: The processing module is used to call and execute the computer program in the storage module to perform the method according to any one of claims 1-3 and output a health assessment report.

5. An electronic device comprising: At least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor executes the computer program to implement the method according to any one of claims 1 to 3.

6. A computer-readable storage medium storing a computer program, characterized in that: The computer program is executed by a processor to implement the method according to any one of claims 1 to 3.

7. A computer program product, characterized in that: When the computer program product runs on a terminal, the terminal implements the method according to any one of claims 1 to 3.

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