Multi-source data management system for monitoring thermal endurance physiological tension index

Abstract

The invention relates to the technical field of data processing, in particular to a multi-source data management system oriented to heat tolerance physiological tension index monitoring, which comprises an acquisition module used for acquiring a PSI value, body temperature data, heart rate data and user attribute data of each testee; the data processing module is used for calculating a high-risk coefficient of each testee based on the body temperature data and the heart rate data of each testee, and calculating a display proportion of each testee in a display screen of the heat endurance physiological tension index all-in-one machine according to the high-risk coefficient, the PSI value and the user attribute data corresponding to each testee; and the display module is used for determining the display position and the display area of each testee in the display screen of the heat tolerance physiological tension index all-in-one machine based on the display proportion corresponding to each testee, and displaying the corresponding testee information according to the display position and the display area. The method can solve the technical problem that a display method with the same display ratio cannot effectively highlight testers needing to be concerned preferentially.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and particularly relates to a multi-source data management system for monitoring the physiological stress index of heat endurance. Background Art

[0002] The Physiological Stress Index (PSI) is an index used to measure an individual's physiological stress in a high-temperature environment, and is mainly used to evaluate the physiological adaptation ability of humans under heat stress conditions. Testing this index is of great significance for preventing and evaluating the health risks brought by high temperatures, optimizing the working and sports environments, and ensuring people's safety. For example, the PSI of athletes is crucial for preventing heat stroke and enhancing heat tolerance. By detecting this index, personalized training plans can be formulated to help athletes maintain their best performance under different environmental conditions.

[0003] Generally, when measuring the PSI of a test subject, a PSI integrated machine is used in a heat chamber environment for measurement. To avoid wasting heat chamber resources, multiple test subjects are usually measured simultaneously, and in the display screen of the PSI integrated machine, the test results are finally displayed with equal display ratios.

[0004] However, the display method with equal display ratios cannot effectively highlight the test subjects who need to be prioritized for attention, so as to be noticed by the recorder. Generally speaking, the larger the PSI value of a test subject, the greater the physiological stress the test subject faces, so special attention is needed. However, even if the PSI values are the same, the priorities of different populations will also vary. For example, for high-risk populations (such as the elderly, children, etc.) who are more likely to encounter heat stress, a higher priority is required. In the case of the same risk, the basic information of the test subject will also affect the priority of the PSI value. Summary of the Invention

[0005] In order to solve the technical problem that the display method with equal display ratios cannot effectively highlight the test subjects who need to be prioritized for attention, the purpose of the present invention is to provide a multi-source data management system for monitoring the physiological stress index of heat endurance, and the specific technical solutions adopted are as follows: In a first aspect, the present invention provides a multi-source data management system for monitoring the physiological stress index of heat endurance. The multi-source data management system for monitoring the physiological stress index of heat endurance is applied to a PSI integrated machine, and the multi-source data management system for monitoring the physiological stress index of heat endurance includes: An acquisition module, configured to acquire the PSI value, body temperature data, heart rate data, and user attribute data of each test subject; A data processing module, which is used to calculate the high-risk coefficients of the testers based on the body temperature data and heart rate data of the testers, determine the PSI priority performance degrees of the testers according to the high-risk coefficients, PSI values and user attribute data respectively corresponding to the testers, and calculate the display ratios of the testers on the display screen of the heat endurance physiological stress index integrated machine based on the PSI values and PSI priority performance degrees of the testers; A display module, which is used to determine the display positions and display areas of the testers on the display screen of the heat endurance physiological stress index integrated machine based on the display ratios corresponding to the testers, and display the corresponding tester information within the display area determined according to the display positions and display areas.

[0006] Optionally, the acquisition module includes: A receiving unit, which is used to receive the PSI values of the testers uploaded by the heat endurance physiological stress index integrated machine, and receive the body temperature data and heart rate data of the testers uploaded by the wearable sports core body temperature and heart rate wireless monitoring device, wherein the wearable sports core body temperature and heart rate wireless monitoring device includes an ear-hung sports core body temperature and heart rate monitoring device and / or an anal temperature core body temperature and heart rate monitoring device; An acquisition unit, which is used to acquire the user attribute data of the testers.

[0007] Optionally, the data processing module includes: A first calculation unit, which is used to calculate the first true availability and the second true availability respectively corresponding to the body temperature data and heart rate data of the testers at each moment; A second calculation unit, which is used to calculate the body temperature rise rate of the testers on the body temperature rise curve and the body temperature drop rate on the body temperature drop curve according to the first true availability, and calculate the heart rate rise rate of the testers on the heart rate rise curve and the heart rate drop rate on the heart rate drop curve according to the second true availability; A third calculation unit, which is used to calculate the high-risk coefficients of the testers based on the body temperature rise rate, the body temperature drop rate, the heart rate rise rate and the heart rate drop rate.

[0008] Optionally, the third calculation unit is specifically used for: Determining the ratio of the body temperature rise rate to the body temperature drop rate as the body temperature rise and fall rate ratio of the corresponding tester, and determining the ratio of the heart rate rise rate to the heart rate drop rate as the heart rate rise and fall rate ratio of the corresponding tester; Determining the product of the body temperature rise and fall rate ratio and the heart rate rise and fall rate ratio as the high-risk coefficient of the corresponding tester.

[0009] Optionally, the user attribute data includes the height value, weight value and age of the tester, and the data processing module further includes: A fourth calculation unit, configured to calculate, based on the high-risk coefficients of the testers, the height value and the weight value, the initial PSI priority performance degree of each tester under the influence of body type; A fifth calculation unit, configured to calculate, based on the initial PSI priority performance degree, the PSI value and the age of each tester, the PSI priority performance degree of each tester under the influence of metabolic differences.

[0010] Optionally, the fourth calculation unit is specifically configured to: Calculate, based on the height value and the weight value of each tester, the body type difference of each tester compared with other testers; Calculate, based on the high-risk coefficients of the testers and the body type difference, the body type influence coefficient of each tester; Determine the product of the normalized data of each tester with respect to the body type influence coefficient and the high-risk coefficient as the initial PSI priority performance degree of the tester under the influence of body type.

[0011] Optionally, the fifth calculation unit is specifically configured to: Calculate, based on the PSI values of the testers and the age of each tester, the target PSI age corresponding to multiple testers; Calculate, according to the initial PSI priority performance degree, age and the corresponding target PSI age of each tester, the PSI priority performance degree of each tester under the influence of metabolic differences.

[0012] Optionally, the data processing module further includes: A sixth calculation unit, configured to calculate, based on the PSI values of the testers and the PSI priority performance degree, the PSI display parameter of each tester; A seventh calculation unit, configured to calculate, according to the PSI display parameter of each tester, the display ratio of each tester on the display screen of the heat endurance physiological stress index integrated machine.

[0013] Optionally, the seventh calculation unit is specifically configured to: Calculate the PSI parameter accumulation sum of all testers with respect to the PSI display parameter; Determine the ratio of the PSI display parameter of each tester to the PSI parameter accumulation sum as the display ratio of the corresponding tester on the display screen of the heat endurance physiological stress index integrated machine.

[0014] Optionally, the display module includes: A first determination unit, configured to determine the display area corresponding to each of the display ratios on the display screen of the heat endurance physiological stress index integrated machine; A second determination unit, configured to sequentially determine the display positions of the respective testers corresponding to the display areas in the remaining area of the display screen of the heat endurance physiological stress index integrated machine according to the display priority order from large to small of the display ratios; A display unit, configured to display corresponding tester information in the display area determined by the display position and the display area.

[0015] The present invention has the following beneficial effects: Through the technical solution provided by the present invention, after obtaining the PSI values, body temperature data, heart rate data, and user attribute data of each tester, the data processing module calculates the high-risk coefficients of each tester based on the body temperature data and heart rate data of each tester, determines the PSI priority performance degrees of each tester according to the high-risk coefficients, PSI values, and user attribute data corresponding to each tester respectively, and calculates the display ratios of each tester on the display screen of the heat endurance physiological stress index integrated machine based on the PSI values and PSI priority performance degrees of each tester; then, the display module can determine the display positions and display areas of each tester on the display screen of the heat endurance physiological stress index integrated machine based on the display ratios corresponding to each tester, and display corresponding tester information in the display area determined by the display position and the display area. The present invention calculates the high-risk coefficient by using the body temperature and heart rate data, comprehensively considering the physiological changes of the human body in a hot environment. Then, in combination with the high-risk coefficient, PSI value, and user attribute data (such as age, body type, etc.), the PSI priority performance degree is determined. Considering that people with a larger body type have difficulty dissipating heat and poor heat regulation ability, a higher priority display degree is given under the same high-risk coefficient; at the same time, for groups with poor heat adaptation ability due to physiological metabolism differences such as the elderly and children, the final PSI priority is further adjusted. This way of comprehensive consideration of multiple factors makes the priority differentiation of different populations more reasonable, ensuring that high-risk populations receive due attention. Further, according to the calculated display ratios, the display positions and areas of the testers are reasonably arranged on the display screen of the heat endurance physiological stress index integrated machine, which enables the recorder to quickly and intuitively discover the testers who need to be focused on, greatly improving the monitoring efficiency and accuracy, and effectively solving the problem that the traditional display method cannot highlight the key points.

[0016] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present invention. Other features and advantages of the present invention will be described in detail in the subsequent specific implementation part. Description of the Drawings

[0017] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0018] Figure 1 Schematic structural diagram of a multi-source data management system for monitoring physiological stress index of heat endurance provided by an embodiment of the present invention; Figure 2 Schematic structural diagram of a multi-source data management system for monitoring physiological stress index of heat endurance provided by another embodiment of the present invention; Figure 3 Schematic example diagram of a body temperature rise and fall curve provided by an embodiment of the present invention; Explanation of reference numerals: 1 - Acquisition module, 11 - Receiving unit, 12 - Acquisition unit; 2 - Data processing module, 21 - First calculation unit, 22 - Second calculation unit, 23 - Third calculation unit, 24 - Fourth calculation unit, 25 - Fifth calculation unit, 26 - Sixth calculation unit, 27 - Seventh calculation unit; 3 - Display module, 31 - First determination unit, 32 - Second determination unit, 33 - Display unit. Detailed implementation manners

[0019] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following will, in conjunction with the accompanying drawings and preferred embodiments, elaborate in detail on a multi-source data management system for monitoring physiological stress index of heat endurance proposed according to the present invention, including its specific implementation manners, structure, features and effects. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs.

[0021] The following will specifically describe the specific solution of a multi-source data management system for monitoring physiological stress index of heat endurance provided by the present invention in conjunction with the accompanying drawings.

[0022] Please refer to Figure 1, which shows a schematic structural diagram of a multi-source data management system for monitoring physiological stress index of heat endurance provided by an embodiment of the present invention. The multi-source data management system for monitoring physiological stress index of heat endurance can be applied to an integrated machine for physiological stress index of heat endurance. The system includes: an acquisition module 1, a data processing module 2, and a display module 3. These three modules cooperate with each other to achieve the acquisition, processing, and display of data for monitoring physiological stress index of heat endurance.

[0023] Among them, the acquisition module 1 can be used to acquire the physiological stress index (PSI) values, body temperature data, heart rate data, and user attribute data (such as age, height, weight, etc.) of each tester; the data processing module 2 can be used to calculate the high-risk coefficient of each tester based on the body temperature data and heart rate data of each tester (for example, considering the characteristics of high-risk heat stress populations with rapid body temperature increase and slow recovery, large heart rate increase and slow recovery, using the ratio of the rise and fall rates of body temperature and heart rate to construct a high-risk coefficient formula to evaluate the risk level of testers in heat endurance tests), determine the PSI priority performance degree of each tester according to the high-risk coefficient, PSI value, and user attribute data corresponding to each tester (for example, people with larger body sizes have difficulty dissipating heat and poorer heat regulation ability, and under the same high-risk coefficient, their PSI priority performance degree will be higher; at the same time, the metabolic differences of different populations are also considered. Groups with poor heat adaptation ability, such as the elderly and children, will be given a higher attention weight to determine a more reasonable final PSI priority), and calculate the display proportion of each tester on the display screen of the integrated machine for physiological stress index of heat endurance based on the PSI value and PSI priority performance degree of each tester. This proportion will determine the display importance of tester information on the display screen and provide a key basis for the subsequent work of the display module; the display module 3 can be used to determine the display position and display area of each tester on the display screen of the integrated machine for physiological stress index of heat endurance based on the display proportion corresponding to each tester, and display the corresponding tester information within the display area determined according to the display position and display area. Among them, the higher the display proportion, the more prominent the display position (such as the upper left corner), and the larger the display area, so that the recorder can more intuitively and quickly pay attention to those testers who need to be monitored key points, realizing the effective monitoring and management of the physiological stress index of heat endurance.

[0024] In a specific application scenario, such as Figure 2As shown in the figure, the acquisition module 1 may include: a receiving unit 11 and a collection unit 12, which work together to obtain multi-source data. Among them, the receiving unit 11 is mainly responsible for receiving data transmitted by external devices. On the one hand, it can receive the PSI values of each tester uploaded by the thermal endurance physiological stress index integrated machine. The PSI value is a key indicator for measuring an individual's physiological stress in a high-temperature environment. By receiving this data, it provides an important basis for subsequent evaluation of the tester's thermal endurance status. On the other hand, the receiving unit 11 can also receive the body temperature data and heart rate data of each tester uploaded by the wearable sports core body temperature and heart rate wireless monitoring device. This wearable device includes an ear-hung sports core body temperature and heart rate monitoring device and / or an anal temperature core body temperature and heart rate monitoring device, which can real-time monitor the physiological data of the tester and transmit it to the receiving unit 11. For example, the ear-hung sports core body temperature and heart rate monitoring device is convenient to wear and can obtain heart rate and body temperature information in a timely manner; the anal temperature core body temperature and heart rate monitoring device may be able to more accurately reflect the change of core body temperature in some scenarios. These physiological data are crucial for analyzing the tester's body reaction in a hot environment. The collection unit 12 is responsible for collecting the user attribute data of each tester. The user attribute data includes information such as age, height, and weight. These data are important supplements for evaluating the tester's thermal endurance status. Different age and body type groups have different responses to heat stress. For example, the elderly and children are more vulnerable to heat stress, and it is relatively difficult for people with a larger body size to dissipate heat. Collecting these data helps to more comprehensively and accurately analyze the tester's thermal endurance situation in the follow-up, and provides strong support for determining their priority and display method in the thermal endurance physiological stress index monitoring.

[0025] In a specific application scenario, such as Figure 2 As shown in the figure, the data processing module 2 may include: a first calculation unit 21, a second calculation unit 22, and a third calculation unit 23. Each unit collaborates in sequence to gradually complete the process of calculating the high-risk coefficient of each tester based on the body temperature data and heart rate data of each tester.

[0026] Specifically, the first calculation unit 21 can be used to calculate the first true availability and the second true availability corresponding to the body temperature data and heart rate data of each tester at each moment. In actual monitoring, the obtained body temperature data and heart rate data may have errors or be interfered by external factors. The true availability is a measure of the reliability of these data in reflecting the true physiological state of the tester. For example, when the tester exercises vigorously, the heart rate monitoring device may generate inaccurate data due to shaking, and the true availability of the heart rate data at this moment is relatively low. By calculating the first true availability (for body temperature data) and the second true availability (for heart rate data), it can provide a more accurate basis for subsequent calculations based on these data.

[0027] Among them, when calculating the first true availability corresponding to the body temperature data of each tester at each moment, the body temperature data of each tester at each t moment can be determined , as well as the body temperature data at the two moments before the t moment (the t - 1 moment and the t - 2 moment) and . Further, the body temperature data at the t moment , as well as the body temperature data at the two moments before the t moment (the t - 1 moment and the t - 2 moment) and are substituted into the first calculation formula, and the first true availability corresponding to the body temperature data of this tester at the t moment can be calculated . The formula characteristics of the first calculation formula are described as follows: In the formula, represents the first true availability corresponding to the body temperature data of tester A at the t moment; exp represents the exponential function with e as the base; represents the body temperature data of tester A at the t moment; represents the body temperature data of tester A at the t - 1 moment; represents the body temperature data of tester A at the t - 2 moment; represents the first change in the body temperature data of tester A at the t moment compared to the body temperature data at the t - 1 moment; represents the second change in the body temperature data of tester A at the t - 1 moment compared to the body temperature data at the t - 2 moment; represents the absolute value of the difference between the first change and the second change

[0028] When calculating the second true availability corresponding to the heart rate data of each tester at each moment, the heart rate data of each tester at each t moment can be determined , as well as the heart rate data at the two moments before the t moment (the t - 1 moment and the t - 2 moment) and . Further, the heart rate data at the t moment , as well as the heart rate data at the two moments before the t moment (the t - 1 moment and the t - 2 moment) and are substituted into the second calculation formula, and the second true availability corresponding to the heart rate data of this tester at the t moment can be calculated . The formula characteristics of the second calculation formula are described as follows: In the formula, represents the second true availability corresponding to the heart rate data of tester A at the t moment; exp represents the exponential function with e as the base; Represents the heart rate data of tester A at time t; Represents the heart rate data of tester A at time t-1; Represents the heart rate data of tester A at time t-2; Represents the third change in the heart rate data of tester A at time t compared to the heart rate data at time t-1; Represents the fourth change in the heart rate data of tester A at time t-1 compared to the heart rate data at time t-2; Represents the absolute value of the difference between the third change and the fourth change.

[0029] Specifically, the second calculation unit 22 can be used to calculate the body temperature rise rate of each tester on the body temperature rise curve and the body temperature drop rate on the body temperature drop curve according to the first true availability, and calculate the heart rate rise rate of each tester on the heart rate rise curve and the heart rate drop rate on the heart rate drop curve according to the second true availability. The body temperature will change in a hot environment. By analyzing the body temperature rise curve and the body temperature drop curve, the reaction of the tester's body to heat stress can be understood. Combining the first true availability can screen out reliable data to calculate the body temperature rise rate and the body temperature drop rate. For example, in the initial stage of heat exposure, the body temperature rises rapidly, and the body heat production rate of the tester can be judged by calculating the rise rate; after the heat exposure ends, the body temperature drops, and the drop rate reflects the body's heat dissipation ability. The heart rate is also an important indicator reflecting the body's reaction to heat stress. In a hot environment, the heart rate will change with the change of the body's metabolism. Use the second true availability to screen reliable heart rate data and calculate the heart rate rise rate and the heart rate drop rate. A fast heart rate rise rate may indicate that the body needs to transport oxygen and heat faster under heat stress, while the heart rate drop rate reflects the body's ability to return to normal metabolism.

[0030] Among them, when calculating the body temperature rise rate of each tester on the body temperature rise curve and the body temperature drop rate on the body temperature drop curve according to the first true availability, the body temperature rise and fall curve of tester A as shown in Figure 3 can be obtained first. The body temperature rise and fall curve includes a body temperature rise curve and a body temperature drop curve, and the body temperature rise curve and the body temperature drop curve intersect at time a. Further, the following formula can be constructed to represent the body temperature rise and fall curve function of tester A (the unknown parameters are , , , a, and the body temperature rise curve and the body temperature drop curve intersect at time a, so ): In the formula, represents the value of the body temperature rise and fall curve function of tester A at time t; represents the rate of increase in body temperature of tester A on the rising body temperature curve; represents the rate of decrease in body temperature of tester A on the falling body temperature curve; represents the th moment of the body temperature rising and falling curve function; is the intercept of the function corresponding to the rising body temperature curve, represents the intercept of the function corresponding to the falling body temperature curve.

[0031] Next, these unknown parameters need to be solved by minimizing the error. First, construct the following formula to represent the error sum of the body temperature rising and falling curve function of the above tester A: In the formula, represents the error sum of the body temperature rising and falling curve function of tester A, and n represents that a total of n moment data are monitored, represents the first true availability corresponding to the body temperature data of tester A at time t, represents the body temperature value of tester A at time t, represents the value of the body temperature rising and falling curve function of tester A at time t, represents the square of the error at time t, represents the square of the available error at time t. Finally, take the partial derivative of the above error sum, set the partial derivative to 0, and the least squares method for solving the system of equations can determine all unknown parameter solutions. That is, the rate of increase in body temperature and the rate of decrease in body temperature can be determined.

[0032] It should be noted that for other testers, the calculation process is the same as that of the above tester A. That is, by constructing a similar body temperature rising and falling curve function and error sum formula, and then using the least squares method to solve the unknown parameters, so as to obtain the rate of increase in body temperature on the rising body temperature curve and the rate of decrease in body temperature on the falling body temperature curve of each tester. When calculating the rate of increase in heart rate on the rising heart rate curve and the rate of decrease in heart rate on the falling heart rate curve of each tester according to the second true availability, the calculation process is also the same as that of the above tester A, which will not be elaborated here.

[0033] Specifically, the third calculation unit 23 can be used to calculate the high-risk coefficient of each tester based on the body temperature rise rate, body temperature fall rate, heart rate rise rate, and heart rate fall rate. Considering the change rates of body temperature and heart rate comprehensively can more comprehensively evaluate the physiological risks of testers in a hot environment. For example, a fast body temperature rise rate and a fast heart rate rise rate may indicate that the tester is under greater stress on the body under heat stress, and the high-risk coefficient will be correspondingly higher. By calculating the high-risk coefficient, the heat tolerance and physiological risks of different testers can be quantitatively evaluated, so as to take targeted measures in the heat tolerance physiological stress index monitoring system, such as focusing on high-risk testers, etc.

[0034] Among them, when the third calculation unit 23 calculates the high-risk coefficient of each tester based on the body temperature rise rate, body temperature fall rate, heart rate rise rate, and heart rate fall rate, specifically, the ratio of the body temperature rise rate to the body temperature fall rate can be determined as the body temperature rise and fall rate ratio of the corresponding tester, and the ratio of the heart rate rise rate to the heart rate fall rate can be determined as the heart rate rise and fall rate ratio of the corresponding tester; the product of the body temperature rise and fall rate ratio and the heart rate rise and fall rate ratio is determined as the high-risk coefficient of the corresponding tester. Its corresponding formula feature description is: In the formula, represents the high-risk coefficient of tester A; represents the body temperature rising rate of tester A; represents the body temperature falling rate of tester A; represents the heart rate rising rate of tester A; represents the heart rate falling rate of tester A; represents the body temperature rise and fall rate ratio of tester A; represents the heart rate rise and fall rate ratio of tester A.

[0035] Similarly, by using the above-mentioned first calculation unit 21, second calculation unit 22, and third calculation unit 23, the high-risk coefficient of each tester can be obtained.

[0036] In a specific application scenario, as Figure 2 shown, the data processing module 2 may further include: a fourth calculation unit 24 and a fifth calculation unit 25. Each unit collaborates in sequence to gradually complete the process of determining the PSI priority performance degree of each tester according to the high-risk coefficient, PSI value, and user attribute data corresponding to each tester.

[0037] Specifically, the fourth calculation unit 24 can be used to calculate the initial PSI priority performance degree of each tester under the influence of body type based on the high-risk coefficient, height value, and weight value of each tester. Body type is an important factor in monitoring the physiological stress index of heat endurance. Because people with larger body types usually have difficulty dissipating heat and relatively poor heat regulation ability, even if their high-risk coefficients are the same, the risks they face in a hot environment may be greater, so higher attention priorities need to be given.

[0038] Among them, when the fourth calculation unit 24 calculates the initial PSI priority performance degree of each tester under the influence of body type based on the high-risk coefficient, height value, and weight value of each tester, it can first calculate the body type difference of each tester compared to other testers based on the height value and weight value of each tester; then calculate the body type influence coefficient of each tester based on the high-risk coefficient and body type difference of each tester; multiply the normalized data of each tester regarding the body type influence coefficient by the high-risk coefficient to determine the initial PSI priority performance degree of the tester under the influence of body type. The corresponding formula feature description is as follows: In the formula, represents the initial PSI priority performance degree of tester A under the influence of body type; f represents the maximum-minimum normalization function (compared with other testers); N represents a total of N testers; exp represents the exponential function with base e; represents the high-risk coefficient of tester A; represents the high-risk coefficient of tester i; represents the similarity degree of the high-risk coefficient between tester A and tester i; represents the sum of the similarity degrees of the high-risk coefficient between tester A and N testers; represents the proportion of the similarity degree of the high-risk coefficient between tester i and tester A among N testers; represents the body type difference of tester A compared to tester i; represents the weight of tester A; represents the height of tester A; represents the body type of tester A; represents the weight of tester i; represents the height of tester i; represents the body type of tester i; represents the body type influence coefficient of tester A.

[0039] Specifically, the fifth calculation unit 25 can further consider the PSI value and the age of the tester based on the initial PSI priority performance degree obtained by the fourth calculation unit 24, and calculate the PSI priority performance degree of each tester under the influence of metabolic differences. This is because people of different ages have different physiological metabolisms and different adaptability in the thermal environment. For example, the adaptability of the elderly and children in the thermal environment is relatively poor, and even if the initial PSI priority performance degree is the same, they need more attention.

[0040] Among them, when the fifth calculation unit 25 calculates the PSI priority performance degree of each tester under the influence of metabolic differences based on the initial PSI priority performance degree, the PSI value and the age of each tester, it can calculate the target PSI age corresponding to multiple testers based on the PSI value and the age of each tester; according to the initial PSI priority performance degree, age and the corresponding target PSI age of each tester, calculate the PSI priority performance degree of each tester under the influence of metabolic differences. The corresponding formula feature description is as follows: In the formula, represents the PSI priority performance degree of tester A under the influence of metabolic differences; f represents the maximum-minimum normalization function (compared with other testers); represents the age of tester A; represents the target PSI age corresponding to N testers; represents the difference between tester A and the target PSI age; represents the initial PSI priority performance degree of tester A under the influence of body shape; N represents a total of N testers; represents the PSI value of tester i; exp represents the exponential function with e as the base; represents the PSI optimality of tester i (because the lower the PSI, the better the heat endurance); represents the relative PSI optimality of test i; represents the age of tester i.

[0041] In a specific application scenario, as Figure 2 shown, the data processing module 2 may further include: a sixth calculation unit 26 and a seventh calculation unit 27. Each unit cooperates in sequence to gradually complete the process of calculating the display ratio of each tester on the display screen of the heat endurance physiological stress index integrated machine based on the PSI value and the PSI priority performance degree of each tester.

[0042] Specifically, the sixth calculation unit 26 can be used to calculate the PSI display parameter of each tester based on the PSI value of each tester and the PSI priority performance degree. Among them, the PSI display parameter = PSI priority performance degree × PSI value. For example, if the PSI value of tester A is 80 and the PSI priority performance degree (calculated by factors such as age and body type) is 1.2, then its PSI display parameter is 1.2 × 80 = 96.

[0043] The seventh calculation unit 27 can be used to calculate the display proportion of each tester on the display screen of the heat endurance physiological stress index integrated machine according to the PSI display parameter of each tester. Specifically, the PSI parameter sum of all testers regarding the PSI display parameter can be calculated; the ratio of the PSI display parameter of each tester to the PSI parameter sum is determined as the display proportion of the corresponding tester on the display screen of the heat endurance physiological stress index integrated machine. The corresponding formula feature description is as follows: In the formula, represents the display proportion of tester A on the display screen of the heat endurance physiological stress index integrated machine; represents the PSI priority performance degree of tester A; represents the PSI value of tester A; represents the PSI priority performance degree of tester i; represents the PSI value of tester i; N represents there are a total of N testers; represents the PSI display parameter of tester A; represents the PSI parameter sum of all testers regarding the PSI display parameter.

[0044] In a specific application scenario, as Figure 2 shown, the display module 3 may include: a first determination unit 31, a second determination unit 32, and a display unit 33. By the collaborative work of the three units, the display proportion calculated by the data processing module can be converted into an actual display effect, ensuring that the display screen of the heat endurance physiological stress index integrated machine can highlight the key points and facilitate the recorder to pay attention to high-risk testers.

[0045] Specifically, the main function of the first determination unit 31 is to determine the corresponding display area on the display screen of the heat endurance physiological stress index integrated machine according to the display ratio of each tester. The display ratio is comprehensively calculated based on the tester's PSI value, high-risk coefficient, basic information, etc. The higher the ratio, the more attention the tester needs. The first determination unit 31 can allocate the display area according to this ratio. For example, if the display ratio of tester A is 30% and the total effective display area of the display screen is 100 square centimeters, then the display area corresponding to tester A may be 30 square centimeters. In this way, the importance of different testers can be intuitively distinguished from the display area. The information display area of the tester with a larger ratio is larger and easier to notice.

[0046] The second determination unit 32 can be used to sequentially determine the display positions of the corresponding display areas of each tester in the remaining area of the display screen of the heat endurance physiological stress index integrated machine according to the display priority order from large to small of the display ratio. Specifically, when determining the display position, the second determination unit 32 will give priority to arranging the testers with a high display ratio in prominent positions. For example, the tester with the highest display ratio is first placed in the upper left corner of the display screen, which is the area that people's visual attention first focuses on. Then, for the next tester with a high display ratio, in the remaining display area, a position that meets the requirements of its display area is searched in the order from left to right. If there is not enough space in the current row, a suitable position will be searched in the next row, and the largest available area that meets the requirements in the remaining area is selected to place the information of this tester. In this way, it is ensured that the information of important testers can be prominently displayed on the display screen, facilitating the recorder to quickly obtain key information.

[0047] The display unit 33 can be used to display the corresponding tester information in the display area determined by the display position and the display area. Specifically, after the previous two units determine the display position and the display area, the display unit 33 is responsible for displaying the corresponding tester information in the corresponding display area. This information may include the basic information of the tester (such as age, height, weight), the real-time monitored body temperature and heart rate data, PSI value, and relevant safety tips, etc. The display unit 33 will present this information in a clear and easy-to-read manner according to the determined display area, ensuring that the recorder can clearly see the key data of each tester at a glance, so as to timely discover potential high-risk testers and take corresponding measures.

[0048] In summary, the technical solution in the present application can calculate the high-risk coefficient by using body temperature and heart rate data, and comprehensively consider the physiological changes of the human body in a hot environment. Subsequently, by combining the high-risk coefficient, PSI value, and user attribute data (such as age, body type, etc.), the priority performance degree of PSI is determined. Considering that people with a larger body type have difficulty dissipating heat and poor heat regulation ability, a higher priority display degree is given under the same high-risk coefficient; at the same time, for groups with poor heat adaptation ability due to physiological metabolism differences such as the elderly and children, the final priority of PSI is further adjusted. This way of comprehensively considering multiple factors makes the priority differentiation for different populations more reasonable, ensuring that high-risk populations receive due attention. Further, according to the calculated display ratio, the display position and area of the tester are reasonably arranged on the display screen of the heat endurance physiological stress index integrated machine, which enables the recorder to quickly and intuitively identify the testers who need to be focused on, greatly improving the monitoring efficiency and accuracy, and effectively solving the problem that the traditional display method cannot highlight the key points.

[0049] It should be noted that: the above sequence of the embodiments of the present invention is only for description and does not represent the superiority or inferiority of the embodiments. And the above specific embodiments of this specification have been described. Additionally, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0050] Each embodiment in this specification is described in a progressive manner, and the same or similar parts among the embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0051] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A multi-source data management system for monitoring heat tolerance physiological stress index, characterized in that: The multi-source data management system for monitoring the heat endurance physiological stress index is applied to the heat endurance physiological stress index integrated machine, and the multi-source data management system for monitoring the heat endurance physiological stress index includes: The acquisition module is used to obtain the PSI value, body temperature data, heart rate data and user attribute data of each tester; A data processing module, for calculating the high-risk coefficient of each tester based on the body temperature data and the heart rate data of each tester, determining the PSI priority performance degree of each tester according to the high-risk coefficient, the PSI value and the user attribute data respectively corresponding to each tester, and calculating the display proportion of each tester in the heat endurance physiological stress index integrated machine display screen based on the PSI value of each tester and the PSI priority performance degree; The display module is used to determine the display position and display area of ​​each tester in the display screen of the thermal endurance physiological stress index integrated machine based on the display proportion corresponding to each tester, and display the corresponding tester information in the display area determined according to the display position and the display area.

2. The multi-source data management system for monitoring heat tolerance physiological stress index according to claim 1 is characterized in that: The acquisition module comprises: A receiving unit, used to receive the PSI value of each tester uploaded by the thermal endurance physiological stress index integrated machine, and receive the body temperature data and heart rate data of each tester uploaded by the wearable sports core body temperature and heart rate wireless monitoring device, wherein the wearable sports core body temperature and heart rate wireless monitoring device includes an ear-hook sports core body temperature and heart rate monitoring device and / or a rectal temperature core body temperature and heart rate monitoring device; The collecting unit is used to collect the user attribute data of each tester.

3. The multi-source data management system for monitoring heat tolerance physiological stress index according to claim 1, characterized in that: The data processing module comprises: A first calculation unit, used for calculating the first real availability and the second real availability respectively corresponding to the body temperature data and the heart rate data of each tester at each moment; a second calculating unit, configured to calculate a body temperature rising rate on a body temperature rising curve and a body temperature falling rate on a body temperature falling curve of each tester according to the first real availability, and to calculate a heart rate rising rate on a heart rate rising curve and a heart rate falling rate on a heart rate falling curve of each tester according to the second real availability; The third calculation unit is used to calculate the high-risk factor of each tester based on the body temperature rising rate, the body temperature falling rate, the heart rate rising rate and the heart rate falling rate.

4. The multi-source data management system for monitoring heat tolerance physiological stress index according to claim 3 is characterized in that: The third computing unit is specifically used for: The ratio of the body temperature increase rate to the body temperature decrease rate is determined as the body temperature increase and decrease rate ratio of the corresponding test subject, and the ratio of the heart rate increase rate to the heart rate decrease rate is determined as the heart rate increase and decrease rate ratio of the corresponding test subject; The product of the body temperature rise and fall rate ratio and the heart rate rise and fall rate ratio is determined as the high-risk coefficient of the corresponding tester.

5. The multi-source data management system for monitoring heat tolerance physiological stress index according to claim 1, characterized in that: The user attribute data includes the tester's height, weight and age. The data processing module also includes: A fourth calculation unit, configured to calculate the initial PSI priority performance degree of each test subject under the influence of body shape based on the high-risk coefficient of each test subject and the height value and the weight value; A fifth calculation unit is used to calculate the PSI priority performance degree of each test subject under the influence of metabolic differences based on the initial PSI priority performance degree, the PSI value and the age of each test subject.

6. The multi-source data management system for monitoring heat tolerance physiological stress index according to claim 5, characterized in that: The fourth computing unit is specifically configured to: Based on the height value and the weight value of each tester, calculating the body shape difference between each tester and other testers; Calculating the body shape influence coefficient of each tester based on the high-risk coefficient of each tester and the body shape difference; The product of the normalized data of the body shape influence coefficient of each test subject and the high-risk coefficient is determined as the initial PSI priority performance level of the test subject under the influence of body shape.

7. The multi-source data management system for monitoring heat tolerance physiological stress index according to claim 5, characterized in that: The fifth computing unit is specifically configured to: Calculating target PSI ages corresponding to the multiple testers based on the PSI values ​​of the testers and the ages of the testers; The PSI priority performance degree of each test subject under the influence of metabolic differences is calculated according to the initial PSI priority performance degree, age and the corresponding target PSI age of each test subject.

8. The multi-source data management system for monitoring heat tolerance physiological stress index according to claim 1, characterized in that: The data processing module also includes: A sixth calculation unit, configured to calculate a PSI display parameter of each tester based on the PSI value of each tester and the PSI priority performance degree; The seventh calculation unit is used to calculate the display proportion of each tester in the heat endurance physiological stress index integrated machine display screen according to the PSI display parameters of each tester.

9. The multi-source data management system for monitoring heat tolerance physiological stress index according to claim 8, characterized in that: The seventh computing unit is specifically used for: Calculating the cumulative sum of the PSI parameters of all testers with respect to the PSI display parameters; The ratio of the PSI display parameter of each tester to the cumulative sum of the PSI parameters is determined as the display proportion of the corresponding tester in the display screen of the thermal endurance physiological stress index integrated machine.

10. The multi-source data management system for monitoring heat tolerance physiological stress index according to claim 1, characterized in that: The display module comprises: A first determining unit is used to determine the display area of ​​each display proportion corresponding to the display area in the display screen of the thermal endurance physiological stress index integrated machine; A second determining unit is used to determine, in order of display priority from large to small, the display positions of the test subjects corresponding to the display area in the remaining area of ​​the display screen of the thermal endurance physiological stress index integrated machine; A display unit is used to display corresponding tester information in a display area determined by the display position and the display area.

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