Health assessment method and device for operating personnel, electronic equipment and storage medium

Abstract

The invention discloses a health assessment method and device for an operator, electronic equipment and a storage medium, and the method comprises the steps: collecting the last physiological data and psychological data of the operator before operation, and obtaining first physiological data and first psychological data; performing clustering analysis on other physiological data and psychological data except the last collection of the operator before operation to obtain second physiological data and second psychological data; respectively generating corresponding probability scores according to the first physiological data and the first psychological data; respectively calculating and generating corresponding probability scores according to the second physiological data and the second psychological data; and according to the first physiological health probability score, the first psychological health probability score, the second physiological health probability score, the second psychological health probability score and a preset weight, generating a health score of the operator, and according to the health score, determining a health state of the operator. According to the invention, the method can achieve the precise evaluation of the health state of an operator.

Description

Technical Field

[0001] The present invention relates to the field of big data technology, and in particular to a health assessment method, device, electronic equipment and storage medium for operators. Background Art

[0002] Health assessment of operators is of great significance to ensuring production safety and improving work efficiency. Health status not only affects the operating ability and safety of operators, but is also directly related to the stability of the working environment and the overall effectiveness of the team. Especially in high-risk or high-intensity work scenarios, comprehensive and accurate assessment of the health status of operators is a key measure to prevent emergencies and reduce safety hazards.

[0003] However, existing health assessment technologies have obvious deficiencies in practice and fail to fully consider the overall health status of workers. On the one hand, existing technologies mainly rely on physiological data collected before work, usually through some immediate physiological indicators to judge whether the workers are suitable to continue working. Although these physiological data can reflect the immediate health status of workers to a certain extent, their assessment results often lack comprehensive consideration of long-term health changes, especially for health risks that may accumulate due to long-term working environment or living habits, it is difficult to make effective predictions. On the other hand, existing technologies generally ignore the impact of mental health on overall health status. With the increasing attention paid to mental health, the impact of psychological factors on the health and work efficiency of workers has become increasingly significant. Most of the existing health assessment methods do not involve mental health data, and lack a comprehensive assessment of the psychological state of workers, resulting in the assessment results may not reflect the psychological burden of workers in a high-pressure environment and its potential impact on health. Summary of the invention

[0004] The embodiment of the present invention provides a method, device, electronic device and storage medium for health assessment of workers. By implementing the present invention, the health status of workers can be fully reflected, and the accuracy of health assessment of workers can be improved.

[0005] An embodiment of the present invention provides a method for health assessment of an operator, comprising:

[0006] The last physiological data and psychological data of the operator before the operation are collected to obtain the first physiological data and the first psychological data;

[0007] Cluster analysis is performed on the other physiological data and psychological data of the operators except for the last collection before the operation to obtain the second physiological data and the second psychological data;

[0008] Calculate and generate a first physiological health probability score and a first psychological health probability score according to the first physiological data and the first psychological data;

[0009] According to the second physiological data and the second psychological data, respectively calculate and generate a second physiological health probability score and a second psychological health probability score;

[0010] A health score of the operator is calculated based on the first physiological health probability score, the first mental health probability score, the second physiological health probability score, the second mental health probability score and preset weights, and the health status of the operator is determined based on the health score.

[0011] Further, the calculating and generating a first physiological health probability score and a first psychological health probability score respectively according to the first physiological data and the first psychological data includes:

[0012] Inputting the first physiological data into a preset physiological state assessment model so that the preset physiological state assessment model calculates and generates a first physiological health probability score;

[0013] The first psychological data is input into a preset psychological state assessment model so that the preset psychological state assessment model calculates and generates a first psychological health probability score.

[0014] Furthermore, the step of calculating and generating a second physiological health probability score and a second mental health probability score based on the second physiological data and the second mental data, respectively, includes:

[0015] Inputting the second physiological data into a preset physiological state assessment model so that the preset physiological state assessment model calculates and generates a second physiological health probability score;

[0016] The second psychological data is input into a preset psychological state assessment model so that the preset psychological state assessment model calculates and generates a second psychological health probability score.

[0017] Furthermore, the preset physiological state assessment model is trained in the following ways, including:

[0018] Acquire historical physiological data and corresponding physiological status labels of several operators; wherein the physiological status labels are physiological health scores of the historical physiological data;

[0019] Constructing a first training set based on historical physiological data and corresponding physiological state labels;

[0020] The first training set is randomly divided into several batches of first training samples according to a preset first number, and the first training samples of each batch are sequentially input into the physiological state assessment model to train the physiological state assessment model until a preset first training number is reached; wherein, the physiological state assessment model outputs a physiological health probability score corresponding to the first training sample each time a batch of first training samples is received; a first loss function value is calculated by cross entropy loss according to the physiological health probability score and the corresponding physiological state label; and the physiological state assessment model is updated by using an optimizer according to the first loss function value.

[0021] Furthermore, the physiological health score of the historical physiological data is obtained by:

[0022] Acquire historical physiological data of several operators; wherein the historical physiological data includes: blood sugar health data, blood pressure health data, BMI health data, cardiovascular health data, liver function health data and blood health data;

[0023] According to the health problems corresponding to the historical physiological data of several operators, the physiological proportional factor of each historical physiological data is determined;

[0024] The historical physiological health score of each operator is calculated and generated based on the historical physiological data of each operator and the physiological proportional factor.

[0025] Furthermore, the preset mental state assessment model is trained in the following ways, including:

[0026] Obtaining historical psychological data and corresponding psychological state labels of several operators; wherein the psychological state label is the psychological health score of the historical psychological data;

[0027] Construct a second training set based on historical psychological data and corresponding psychological state labels;

[0028] The second training set is randomly divided into several batches of second training samples according to a preset second number, and the second training samples of each batch are input into the psychological state assessment model in turn, and the psychological state assessment model is trained until a preset second training number is reached; wherein, when the psychological state assessment model receives each batch of second training samples, it outputs the mental health probability score corresponding to the second training sample; according to the mental health probability score and the corresponding mental state label, a second loss function value is calculated by cross entropy loss; and the psychological state assessment model is updated by using an optimizer according to the second loss function value.

[0029] Furthermore, the mental health score of the historical mental data is obtained by:

[0030] Acquire historical psychological data of several operators; wherein the historical psychological data includes: anxiety data, depression data, stress data, sleep quality data, attention deficit data and post-traumatic stress response data;

[0031] According to the health problems corresponding to the historical psychological data of several operators, the psychological proportional factors of each historical psychological data are determined;

[0032] Based on the historical psychological data of each operator and the psychological proportion factor, the historical mental health score of each operator is calculated and generated.

[0033] Based on the above method embodiment, the present invention provides a corresponding device embodiment.

[0034] An embodiment of the present invention provides a health assessment device for workers, comprising: a data acquisition module, a health probability score calculation module and a health status assessment module;

[0035] The data collection module is used to collect the last physiological data and psychological data of the operator before the operation to obtain the first physiological data and the first psychological data; and to perform cluster analysis on the other physiological data and psychological data of the operator before the operation except the last collection to obtain the second physiological data and the second psychological data;

[0036] The health probability score calculation module is used to calculate and generate a first physiological health probability score and a first mental health probability score according to the first physiological data and the first psychological data; and to calculate and generate a second physiological health probability score and a second mental health probability score according to the second physiological data and the second psychological data;

[0037] The health status assessment module is used to calculate and generate a health score for the operator based on a first physiological health probability score, a first mental health probability score, a second physiological health probability score, a second mental health probability score and preset weights, and determine the health status of the operator based on the health score.

[0038] Based on the above method embodiment, the present invention provides a corresponding electronic device embodiment.

[0039] An embodiment of the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the health assessment method for operators described in any one of the above method embodiments can be implemented.

[0040] Based on the above method item embodiments, the present invention provides a corresponding storage medium item embodiment.

[0041] An embodiment of the present invention provides a storage medium having a computer program stored thereon. When the computer program is executed by a processor, the health assessment method for operators described in any one of the above method embodiments can be implemented.

[0042] Compared with the prior art, the present invention has the following beneficial effects:

[0043] The embodiment of the present invention provides a health assessment method, device, electronic device and storage medium for operators. The method obtains the first physiological data, first psychological data, second physiological data and second psychological data of the operator, and combines cluster analysis and scoring calculation to comprehensively assess the health status of the operator. The first psychological data is obtained by clustering analysis of other psychological data collected by the operator before the operation except for the last collection, showing the psychological health status of the operator; the second physiological data is the physiological data collected for the last time before the operation, which directly reflects the immediate physiological condition of the operator; the second psychological data is the psychological data collected for the last time before the operation, which can reflect the current psychological state of the operator. This design effectively combines historical physiological data, historical psychological data, immediate physiological data and immediate psychological data, so that the health assessment can be more comprehensive and accurate. By implementing the present invention, the long-term health change trend of the operator can be reflected, and combined with the psychological data of the operator, a comprehensive and accurate assessment of the health status of the operator can be achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 It is a flowchart of a health assessment method for operators provided in one embodiment of the present invention.

[0045] Figure 2 It is a structural schematic diagram of a health assessment device for operators provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] like Figure 1 As shown, an embodiment of the present invention provides a health assessment method for workers, which includes at least the following steps:

[0048] Step S1, collecting the last physiological data and psychological data of the operator before the operation to obtain the first physiological data and the first psychological data;

[0049] It should be noted that the collection of the last physiological and psychological data of the operator before the operation can be obtained through the data in the physical examination report. Specifically, the physiological data usually included in the physical examination report, such as heart rate, blood pressure, body temperature, blood sugar, BMI and other health indicators, can be further divided into blood sugar health data, blood pressure health data, BMI health data, cardiovascular health data, liver function health data and blood health data; while psychological data can be obtained through the standardized psychological assessment tools used during the physical examination, such as anxiety data, depression data, stress data, sleep quality data, attention deficit data and post-traumatic stress response data and other assessment results. As a collection source, the physical examination report data not only facilitates the rapid acquisition of information, but also ensures the standardization and reliability of the data, providing an accurate basis for subsequent health assessments.

[0050] It is understandable that directly capturing the current physiological and psychological conditions of the operators, thereby reflecting their actual health level before the start of the operation, provides a real-time basis for subsequent health assessments.

[0051] Step S2, performing cluster analysis on the physiological data and psychological data of the operator before the operation except for the last collection, to obtain second physiological data and second psychological data;

[0052] It should be noted that when clustering the physiological and psychological data of the operators except for the last collection before the operation, a variety of common clustering methods can be used, including K-means clustering, hierarchical clustering, and DBSCAN clustering.

[0053] It is understandable that by clustering the physiological data and psychological data of the operators except for the last collection before the operation, the second physiological data and the second psychological data are obtained, which can comprehensively reflect the health change trend of the operators over a longer period of time. By extracting key features from historical data through cluster analysis methods, it is possible not only to remove redundant information in the data, but also to effectively reveal the regular changes in the long-term health status of the operators. Compared with the analysis of single data, cluster analysis can more accurately capture the commonalities and differences between multiple data, thereby providing deeper insights into health status. The generated second physiological data and second psychological data can not only provide a scientific basis for evaluating the long-term health change trend of operators, but also assist in identifying potential chronic health risks or mental health problems, ensuring the comprehensiveness and reliability of health assessments.

[0054] Step S3, calculating and generating a first physiological health probability score and a first psychological health probability score respectively according to the first physiological data and the first psychological data;

[0055] Specifically, in a preferred embodiment, the step of calculating and generating a first physiological health probability score and a first psychological health probability score based on the first physiological data and the first psychological data, respectively, includes:

[0056] Inputting the first physiological data into a preset physiological state assessment model so that the preset physiological state assessment model calculates and generates a first physiological health probability score;

[0057] The first psychological data is input into a preset psychological state assessment model so that the preset psychological state assessment model calculates and generates a first psychological health probability score.

[0058] Step S4, calculating and generating a second physiological health probability score and a second mental health probability score according to the second physiological data and the second mental data;

[0059] Specifically, in a preferred embodiment, the step of calculating and generating a second physiological health probability score and a second mental health probability score based on the second physiological data and the second mental data, respectively, includes:

[0060] Inputting the second physiological data into a preset physiological state assessment model so that the preset physiological state assessment model calculates and generates a second physiological health probability score;

[0061] The second psychological data is input into a preset psychological state assessment model so that the preset psychological state assessment model calculates and generates a second psychological health probability score.

[0062] Exemplarily, the preset physiological state assessment model is trained in the following manner, including:

[0063] Acquire historical physiological data and corresponding physiological status labels of several operators; wherein the physiological status labels are physiological health scores of the historical physiological data;

[0064] Constructing a first training set based on historical physiological data and corresponding physiological state labels;

[0065] The first training set is randomly divided into several batches of first training samples according to a preset first number, and the first training samples of each batch are sequentially input into the physiological state assessment model to train the physiological state assessment model until a preset first training number is reached; wherein, the physiological state assessment model outputs a physiological health probability score corresponding to the first training sample each time a batch of first training samples is received; a first loss function value is calculated by cross entropy loss according to the physiological health probability score and the corresponding physiological state label; and the physiological state assessment model is updated by using an optimizer according to the first loss function value.

[0066] Exemplarily, the physiological health score of historical physiological data is obtained by the following methods, including:

[0067] Acquire historical physiological data of several operators; wherein the historical physiological data includes: blood sugar health data, blood pressure health data, BMI health data, cardiovascular health data, liver function health data and blood health data;

[0068] According to the health problems corresponding to the historical physiological data of several operators, the physiological proportional factor of each historical physiological data is determined;

[0069] The historical physiological health score of each operator is calculated and generated based on the historical physiological data of each operator and the physiological proportional factor.

[0070] In an optional embodiment, according to the health problems corresponding to the historical physiological data of a number of operators, the physiological proportional factor of each historical physiological data is determined, including:

[0071] The various health problems involved are determined through the historical physiological data of the operators; the historical physiological data include blood sugar health data, blood pressure health data, BMI health data, cardiovascular health data, liver function health data and blood health data, which correspond to different physiological health problems, including blood sugar health problems, blood pressure health problems, BMI health problems, cardiovascular health problems, liver function health problems and blood health problems; for each physiological health problem, its related physiological indicators are analyzed, and the abnormal rate of the physiological health problem is calculated, so as to further determine the physiological proportion factor of each physiological data.

[0072] For a total number of m workers, a physiological health problem Q1 is selected, which is associated with k physiological indicators. Let the jth indicator value of the i-th worker be x i，j , the corresponding normal value range is s j，normal ; If the indicator value exceeds the normal range, it will be counted as an abnormal indicator, and the number of abnormal indicators for each operator n will be counted i ;

[0073]

[0074] Where I represents the indicator function, if the condition is met, the result is 1, otherwise it is 0;

[0075] In order to prevent a single operator from significantly affecting the abnormal rate of physiological health problems due to multiple abnormal indicators, the weight of each abnormal indicator is set in a decreasing manner; the abnormal weight t of the i-th operator is defined as i for:

[0076]

[0077] Summarize the abnormal weights of all operators to obtain the abnormal rate of physiological health problem Q1

[0078]

[0079] Count the abnormality rates of all physiological health problems and calculate their total abnormality rate Q total :

[0080]

[0081] For a physiological health problem Q1, its physiological proportional factor The ratio of the abnormality rate of this physiological health problem to the total abnormality rate:

[0082]

[0083] Optionally, a preset mental state assessment model is trained by:

[0084] Obtaining historical psychological data and corresponding psychological state labels of several operators; wherein the psychological state label is the psychological health score of the historical psychological data;

[0085] Construct a second training set based on historical psychological data and corresponding psychological state labels;

[0086] The second training set is randomly divided into several batches of second training samples according to a preset second number, and the second training samples of each batch are input into the psychological state assessment model in turn, and the psychological state assessment model is trained until a preset second training number is reached; wherein, when the psychological state assessment model receives each batch of second training samples, it outputs the mental health probability score corresponding to the second training sample; according to the mental health probability score and the corresponding mental state label, a second loss function value is calculated by cross entropy loss; and the psychological state assessment model is updated by using an optimizer according to the second loss function value.

[0087] Optionally, obtain the mental health score of historical mental data through the following methods, including:

[0088] Acquire historical psychological data of several operators; wherein the historical psychological data includes: anxiety data, depression data, stress data, sleep quality data, attention deficit data and post-traumatic stress response data;

[0089] According to the health problems corresponding to the historical psychological data of several operators, the psychological proportional factors of each historical psychological data are determined;

[0090] Based on the historical psychological data of each operator and the psychological proportion factor, the historical mental health score of each operator is calculated and generated.

[0091] For example, the various mental health problems involved are identified through the historical psychological data of the operators. The historical psychological data include anxiety data, depression data, stress data, sleep quality data, attention deficit data and post-traumatic stress response data, which correspond to different mental health problems, including anxiety health problems, depression health problems, stress health problems, sleep quality health problems, attention deficit health problems and post-traumatic stress response health problems; for each mental health problem, the relevant psychological indicators are analyzed, and the abnormal rate of mental health problems is calculated, so as to further determine the proportional factor of each psychological data.

[0092] For a total number of n workers, a mental health problem P1 is selected, which is associated with k psychological indicators. Let the jth psychological indicator value of the i-th worker be y i，j , and its corresponding normal value range is r j，normal If the indicator value exceeds the normal range, it will be counted as an abnormal indicator, and the number of abnormal psychological indicators of each operator will be counted. i , the formula is:

[0093]

[0094] Where I(·) is an indicator function, and the result is 1 if the condition is met, otherwise it is 0.

[0095] In order to prevent a single operator from significantly affecting the abnormal rate of mental health problems due to multiple abnormal psychological indicators, the weight of each abnormal psychological indicator is set in a decreasing manner. Define the abnormal weight v of the i-th operator i for:

[0096]

[0097] Summarize the abnormal weights of all operators to obtain the abnormal rate of mental health problem P1

[0098]

[0099] Count the abnormal rates of all mental health problems and calculate their total abnormal rate P total :

[0100]

[0101] For a mental health problem i , psychological scale factor is the ratio of the abnormal rate of this mental health problem to the total abnormal rate:

[0102]

[0103] Step S5, calculating and generating a health score of the operator according to the first physiological health probability score, the first mental health probability score, the second physiological health probability score, the second mental health probability score and preset weights, and determining the health status of the operator according to the health score.

[0104] Specifically, according to the operator's physical and mental health scores and preset weights, the final health score result can be calculated comprehensively. total , and determine the health status of the operator based on this score. Specifically, the first physiological health probability score, the first mental health probability score, the second physiological health probability score, and the second mental health probability score will be assigned corresponding weights ω1, ω2, ω3, ω4 according to their respective importance, and weighted summed. Health score result total Calculated by the following formula:

[0105] Result total =100·(ω1·result1+ω2·result2+ω3·result3+ω4·result4)

[0106] Based on the above method embodiment, the present invention provides a corresponding device embodiment.

[0107] Among them, result1 represents the first physiological health probability score, result2 represents the first mental health probability score, result3 represents the second physiological health probability score; result4 represents the second mental health probability score; the preset weight coefficients of ω1, ω2, ω3, and ω4 scores are used to measure the relative importance of each score in the final health score.

[0108] Calculated health score result total It will be used to determine the health status of the workers. According to the specific value of the health score, the health status of the workers can be divided into multiple levels, such as "healthy", "mild discomfort", "moderate discomfort", "severe discomfort", etc., so as to take corresponding preventive or intervention measures to ensure the safety and health of the workers.

[0109] like Figure 2 As shown, an embodiment of the present invention provides a health assessment device for workers, including: a data acquisition module 101, a health probability score calculation module 102 and a health status assessment module 103;

[0110] The data collection module 101 is used to collect the last physiological data and psychological data of the operator before the operation to obtain the first physiological data and the first psychological data; perform cluster analysis on the other physiological data and psychological data of the operator before the operation except the last collection to obtain the second physiological data and the second psychological data;

[0111] The health probability score calculation module 102 is used to calculate and generate a first physiological health probability score and a first mental health probability score according to the first physiological data and the first psychological data; and to calculate and generate a second physiological health probability score and a second mental health probability score according to the second physiological data and the second psychological data;

[0112] The health status assessment module 103 is used to calculate and generate a health score for the operator based on the first physiological health probability score, the first mental health probability score, the second physiological health probability score, the second mental health probability score and preset weights, and determine the health status of the operator based on the health score.

[0113] It should be noted that the embodiments of the device described above correspond to the above embodiments of the present invention, and can implement any of the methods described above in the present invention. In addition, the embodiments of the above-mentioned device are merely schematic, wherein the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which can be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art can understand and implement it without paying any creative work.

[0114] Based on the above method embodiment of the present invention, a corresponding electronic device embodiment is provided.

[0115] An embodiment of the present invention provides an electronic device, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the health assessment method for operators described in any one of the present invention is implemented, or, when the processor executes the computer program, the functions of the modules in the above-mentioned device embodiments are implemented.

[0116] Exemplarily, the computer program may be divided into one or more modules, which are stored in the memory and executed by the processor to implement the present invention. The one or more modules may be a series of computer program instruction segments capable of implementing specific functions, which are used to describe the execution process of the computer program in the terminal device.

[0117] The terminal device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0118] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal device, and uses various interfaces and lines to connect various parts of the entire terminal device.

[0119] The memory can be used to store the computer program and / or module, and the processor realizes various functions of the terminal device by running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required for a function, etc.; the data storage area can store data created according to the use of the mobile phone, etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0120] Based on the above method embodiment, the present invention provides a storage medium embodiment;

[0121] Another embodiment of the present invention provides a storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the storage medium is located is controlled to execute any of the above-mentioned health assessment methods for operators of the present invention.

[0122] The storage medium is a computer-readable storage medium, and the computer program includes computer program code, which may be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium may be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0123] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples, unless they are contradictory.

[0124] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for health assessment of workers, characterized in that: include: The last physiological data and psychological data of the operator before the operation are collected to obtain the first physiological data and the first psychological data; Cluster analysis is performed on the other physiological data and psychological data of the operators except for the last collection before the operation to obtain the second physiological data and the second psychological data; Calculate and generate a first physiological health probability score and a first mental health probability score according to the first physiological data and the first psychological data; According to the second physiological data and the second psychological data, respectively calculate and generate a second physiological health probability score and a second psychological health probability score; A health score of the operator is calculated based on the first physiological health probability score, the first mental health probability score, the second physiological health probability score, the second mental health probability score and preset weights, and the health status of the operator is determined based on the health score.

2. A health assessment method for workers as claimed in claim 1, characterized in that: The step of calculating and generating a first physiological health probability score and a first psychological health probability score respectively according to the first physiological data and the first psychological data includes: Inputting the first physiological data into a preset physiological state assessment model so that the preset physiological state assessment model calculates and generates a first physiological health probability score; The first psychological data is input into a preset psychological state assessment model so that the preset psychological state assessment model calculates and generates a first psychological health probability score.

3. A method for health assessment of workers as claimed in claim 2, characterized in that: The step of calculating and generating a second physiological health probability score and a second mental health probability score respectively according to the second physiological data and the second mental data comprises: Inputting the second physiological data into a preset physiological state assessment model so that the preset physiological state assessment model calculates and generates a second physiological health probability score; The second psychological data is input into a preset psychological state assessment model so that the preset psychological state assessment model calculates and generates a second psychological health probability score.

4. A method for health assessment of workers as claimed in claim 3, characterized in that: The preset physiological state assessment model is trained by: Acquire historical physiological data and corresponding physiological status labels of several operators; wherein the physiological status labels are physiological health scores of the historical physiological data; Constructing a first training set based on historical physiological data and corresponding physiological state labels; The first training set is randomly divided into several batches of first training samples according to a preset first number, and the first training samples of each batch are sequentially input into the physiological state assessment model to train the physiological state assessment model until a preset first training number is reached; wherein, the physiological state assessment model outputs a physiological health probability score corresponding to the first training sample each time a batch of first training samples is received; a first loss function value is calculated by cross entropy loss according to the physiological health probability score and the corresponding physiological state label; and the physiological state assessment model is updated by using an optimizer according to the first loss function value.

5. A method for health assessment of workers as claimed in claim 4, characterized in that: Get physiological health scores of historical physiological data through the following methods, including: Acquire historical physiological data of several operators; wherein the historical physiological data includes: blood sugar health data, blood pressure health data, BMI health data, cardiovascular health data, liver function health data and blood health data; According to the health problems corresponding to the historical physiological data of several operators, the physiological proportional factor of each historical physiological data is determined; The historical physiological health score of each operator is calculated and generated based on the historical physiological data of each operator and the physiological proportional factor.

6. A method for health assessment of workers as claimed in claim 5, characterized in that: The preset mental state assessment model is trained by: Obtaining historical psychological data and corresponding psychological state labels of several operators; wherein the psychological state label is the psychological health score of the historical psychological data; Construct a second training set based on historical psychological data and corresponding psychological state labels; The second training set is randomly divided into several batches of second training samples according to a preset second number, and the second training samples of each batch are input into the psychological state assessment model in turn, and the psychological state assessment model is trained until a preset second training number is reached; wherein, when the psychological state assessment model receives each batch of second training samples, it outputs the mental health probability score corresponding to the second training sample; according to the mental health probability score and the corresponding mental state label, a second loss function value is calculated by cross entropy loss; and the psychological state assessment model is updated by using an optimizer according to the second loss function value.

7. A method for health assessment of workers as claimed in claim 6, characterized in that: Get mental health scores for historical mental data through: Acquire historical psychological data of several operators; wherein the historical psychological data includes: anxiety data, depression data, stress data, sleep quality data, attention deficit data and post-traumatic stress response data; According to the health problems corresponding to the historical psychological data of several operators, the psychological proportional factors of each historical psychological data are determined; Based on the historical psychological data of each operator and the psychological proportion factor, the historical mental health score of each operator is calculated and generated.

8. A health assessment device for workers, characterized in that: include: Data collection module, health probability score calculation module and health status assessment module; The data collection module is used to collect the last physiological data and psychological data of the operator before the operation to obtain the first physiological data and the first psychological data; and to perform cluster analysis on the other physiological data and psychological data of the operator before the operation except the last collection to obtain the second physiological data and the second psychological data; The health probability score calculation module is used to calculate and generate a first physiological health probability score and a first mental health probability score according to the first physiological data and the first psychological data; According to the second physiological data and the second psychological data, respectively calculate and generate a second physiological health probability score and a second psychological health probability score; The health status assessment module is used to calculate and generate a health score for operator i based on a first physiological health probability score, a first mental health probability score, a second physiological health probability score, a second mental health probability score and preset weights, and determine the health status of the operator based on the health score.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the health assessment method for operators described in any one of claims 1 to 7 can be implemented.

10. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it can implement the health assessment method for operators described in any one of claims 1 to 7.

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