A multi-source data management system for monitoring heat tolerance physiological stress index

Abstract

This invention relates to the field of data processing technology, specifically to a multi-source data management system for monitoring the physiological stress index of heat endurance. The system includes: an acquisition module for acquiring the PSI value, body temperature data, heart rate data, and user attribute data of each test subject; a data processing module for calculating the high-risk coefficient of each test subject based on their body temperature and heart rate data, and calculating the display percentage of each test subject on the integrated display screen of the thermal stress index monitoring device based on their corresponding high-risk coefficient, PSI value, and user attribute data; and a display module for determining the display position and display area of ​​each test subject on the integrated display screen of the thermal stress index monitoring device based on their corresponding display percentage, and displaying the corresponding test subject information according to the display position and display area. This application solves the technical problem that display methods with the same display percentage cannot effectively highlight test subjects requiring priority attention.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and specifically to a multi-source data management system for monitoring the physiological stress index of heat tolerance. Background Technology

[0002] The Physiological Stress Index (PSI) is an indicator used to measure an individual's physiological stress tolerance in high-temperature environments, primarily assessing the human body's physiological adaptability under heat stress conditions. Testing this index is crucial for preventing and assessing health risks associated with high temperatures, optimizing work and sports environments, and ensuring public safety. For example, in athletes, the PSI is essential for preventing heatstroke and enhancing heat tolerance. By measuring this index, personalized training plans can be developed to help athletes maintain peak performance under varying environmental conditions.

[0003] Generally, when measuring the thermal endurance physiological stress index of test subjects, a thermal endurance physiological stress index integrated machine is used in a hot chamber environment. In order to avoid wasting hot chamber resources, multiple test subjects are usually measured simultaneously, and the final test results are displayed on the screen of the thermal endurance physiological stress index integrated machine with equal display proportions.

[0004] However, using a uniform display method fails to effectively highlight test subjects requiring priority attention, thus hindering their focus on the recorder. Generally, a higher PSI value indicates greater physiological stress, necessitating special attention. However, even with the same PSI value, different groups may have different priorities. For example, high-risk groups more susceptible to heat stress (such as the elderly and children) require higher priority. Furthermore, under similar risk conditions, the test subject's baseline information also influences the priority of PSI values. Summary of the Invention

[0005] To address the technical problem that display methods with equal screen size cannot effectively highlight test subjects requiring priority attention, the present invention aims to provide a multi-source data management system for monitoring the physiological stress index of thermal endurance. The specific technical solution adopted is as follows:

[0006] In a first aspect, the present invention provides a multi-source data management system for monitoring the physiological stress index of heat endurance. This multi-source data management system is applied to an integrated heat endurance physiological stress index monitoring device. The multi-source data management system for monitoring the physiological stress index of heat endurance includes:

[0007] The acquisition module is used to acquire PSI values, body temperature data, heart rate data, and user attribute data for each test subject.

[0008] The data processing module is used to calculate the high-risk coefficient of each test subject based on the body temperature data and heart rate data of each test subject; determine the priority performance degree of each test subject's PSI based on the high-risk coefficient, PSI value and user attribute data of each test subject; and calculate the display percentage of each test subject on the display screen of the thermal endurance physiological stress index all-in-one machine based on the PSI value and the priority performance degree of each test subject.

[0009] The display module is used to determine the display position and display area of ​​each test subject in the display screen of the thermal endurance physiological stress index integrated machine based on the display ratio corresponding to each test subject, and to display the corresponding test subject information in the display area determined according to the display position and the display area.

[0010] Optionally, the acquisition module includes:

[0011] The receiving unit is used to receive the PSI values ​​of each test subject uploaded by the thermal endurance physiological stress index integrated machine, and to receive the body temperature data and heart rate data of each test subject uploaded by the wearable exercise core body temperature and heart rate wireless monitoring device. The wearable exercise core body temperature and heart rate wireless monitoring device includes an ear-hook exercise core body temperature and heart rate monitoring device and / or a rectal temperature core body temperature and heart rate monitoring device.

[0012] The data acquisition unit is used to collect user attribute data from each tester.

[0013] Optionally, the data processing module includes:

[0014] The first calculation unit is used to calculate the first real availability and the second real availability corresponding to the body temperature data and the heart rate data of each test subject at each time moment;

[0015] The second calculation unit is used to calculate the rate of increase of body temperature on the body temperature rise curve and the rate of decrease of body temperature on the body temperature fall curve for each test subject based on the first real availability, and to calculate the rate of increase of heart rate on the heart rate rise curve and the rate of decrease of heart rate on the heart rate fall curve for each test subject based on the second real availability.

[0016] The third calculation unit is used to calculate the high-risk coefficient of each test subject based on the rate of increase in body temperature, the rate of decrease in body temperature, the rate of increase in heart rate, and the rate of decrease in heart rate.

[0017] Optionally, the third computing unit is specifically used for:

[0018] The ratio of the rate of increase in body temperature to the rate of decrease in body temperature is determined as the body temperature rise / fall rate ratio for the corresponding test subject, and the ratio of the rate of increase in heart rate to the rate of decrease in heart rate is determined as the heart rate rise / fall rate ratio for the corresponding test subject.

[0019] The product of the ratio of body temperature rise / fall rate and the ratio of heart rate rise / fall rate is determined as the high-risk coefficient for the corresponding test subject.

[0020] Optionally, the user attribute data includes the tester's height, weight, and age, and the data processing module further includes:

[0021] The fourth calculation unit is used 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, as well as the height value and the weight value.

[0022] The fifth calculation unit is used to calculate the PSI priority performance of each test subject under the influence of metabolic differences, based on the initial PSI priority performance, the PSI value, and the age of each test subject.

[0023] Optionally, the fourth computing unit is specifically used for:

[0024] Based on the height and weight values ​​of each test subject, calculate the body shape difference between each test subject and the other test subjects;

[0025] Based on the high-risk coefficients of each test subject and the differences in body shape, the body shape influence coefficient of each test subject is calculated.

[0026] The product of the normalized data of each test subject's body size influence coefficient and the high-risk coefficient is determined as the initial PSI priority performance of the test subject under the influence of body size.

[0027] Optionally, the fifth computing unit is specifically used for:

[0028] Based on the PSI values ​​and ages of each tester, calculate the target PSI ages for multiple testers;

[0029] Based on the initial PSI priority performance, age, and corresponding target PSI age of each test subject, the PSI priority performance of each test subject under the influence of metabolic differences is calculated.

[0030] Optionally, the data processing module further includes:

[0031] The sixth calculation unit is used to calculate the PSI display parameters of each tester based on the PSI value of each tester and the priority of the PSI performance.

[0032] The seventh calculation unit is used to calculate the display percentage of each test subject on the integrated display screen of the thermal endurance physiological stress index based on the PSI display parameters of each test subject.

[0033] Optionally, the seventh computing unit is specifically used for:

[0034] Calculate the cumulative sum of PSI parameters for all testers regarding the PSI displayed parameters;

[0035] The ratio of the PSI display parameters of each test subject to the sum of the PSI parameters is determined as the display percentage of the corresponding test subject on the integrated display screen of the thermal endurance physiological stress index machine.

[0036] Optionally, the display module includes:

[0037] The first determining unit is used to determine the display area in the display screen of the thermal endurance physiological stress index all-in-one machine corresponding to each of the display proportions;

[0038] The second determining unit is used to determine the display position of each test subject in the remaining area of ​​the display screen of the thermal endurance physiological stress index integrated machine in accordance with the display priority order from large to small display proportion;

[0039] The display unit is used to display the corresponding tester information within the display area determined by the display position and the display area.

[0040] The present invention has the following beneficial effects: Through the technical solution provided by the present invention, after obtaining the PSI value, body temperature data, heart rate data, and user attribute data of each test subject, the data processing module calculates the high-risk coefficient for each test subject based on their body temperature and heart rate data. Based on the high-risk coefficient, PSI value, and user attribute data of each test subject, the priority of PSI performance for each test subject is determined. Furthermore, based on the PSI value and priority of PSI performance, the display percentage of each test subject on the integrated display screen of the thermal endurance physiological stress index machine is calculated. Then, the display module determines the display position and display area of ​​each test subject on the integrated display screen of the thermal endurance physiological stress index machine based on their corresponding display percentage, and displays the corresponding test subject information within the display area determined by the display position and display area. The present invention calculates the high-risk coefficient using body temperature and heart rate data, comprehensively considering the physiological changes of the human body in a thermal environment. Then, combining the high-risk coefficient, PSI value, and user attribute data (such as age, body type, etc.), the priority of PSI performance is determined. Considering the difficulty in heat dissipation and poor thermal regulation of larger individuals, they are given higher priority in display when the high-risk coefficient is the same. Simultaneously, for groups with poor thermal adaptation due to physiological metabolic differences, such as the elderly and children, the final priority of the PSI (Physiological Stress Index) is further adjusted. This multi-factor comprehensive approach makes the priority distinction between different groups more reasonable, ensuring that high-risk groups receive the attention they deserve. Furthermore, based on the calculated display proportions, the display position and area of ​​the test subjects on the integrated display screen of the thermal endurance physiological stress index machine are rationally arranged. This allows the recorder to quickly and intuitively identify test subjects requiring focused attention, greatly improving monitoring efficiency and accuracy, and effectively solving the problem that traditional display methods cannot highlight key individuals.

[0041] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit the invention. Other features and advantages of the invention will be described in detail in the following detailed description section. Attached Figure Description

[0042] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0043] Figure 1 This is a schematic diagram of a multi-source data management system for monitoring the physiological stress index of heat tolerance, provided in one embodiment of the present invention.

[0044] Figure 2A schematic diagram of a multi-source data management system for monitoring the physiological stress index of heat tolerance, provided in another embodiment of the present invention;

[0045] Figure 3 This is a schematic diagram of an example of a body temperature rise and fall curve provided in one embodiment of the present invention;

[0046] Explanation of reference numerals in the attached figures:

[0047] 1-Acquisition module, 11-Receiving unit, 12-Collection unit;

[0048] 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;

[0049] 3-Display module, 31-First determining unit, 32-Second determining unit, 33-Display unit. Detailed Implementation

[0050] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a multi-source data management system for monitoring the physiological stress index of heat tolerance proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0051] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0052] The following description, in conjunction with the accompanying drawings, details a specific solution for a multi-source data management system for monitoring the physiological stress index of heat tolerance provided by this invention.

[0053] See also Figure 1 The diagram illustrates a multi-source data management system for monitoring the physiological stress index of heat endurance provided by an embodiment of the present invention. The multi-source data management system for monitoring the physiological stress index of heat endurance can be applied to an integrated machine for monitoring the 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 acquire, process, and display the monitoring data of the physiological stress index of heat endurance.

[0054] The data acquisition module 1 can acquire the Physiological Stress Index (PSI) value, body temperature data, heart rate data, and user attribute data (such as age, height, and weight) of each test subject. The data processing module 2 can calculate the high-risk coefficient for each test subject based on their body temperature and heart rate data (for example, considering the characteristics of high-risk heat stress individuals—rapid body temperature rise and slow recovery, and large heart rate rise and slow recovery—a high-risk coefficient formula is constructed using the ratio of the rate of increase / decrease in body temperature and heart rate to assess the risk level of the test subject in the heat endurance test). Based on the high-risk coefficient, PSI value, and user attribute data of each test subject, the module determines the priority of each test subject's PSI performance (for example, larger individuals have difficulty dissipating heat and have poorer thermoregulation; under the same high-risk coefficient, their priority of PSI performance will be higher). The system is designed to be more advanced; it also considers the metabolic differences among different populations, giving higher weight to groups with poor heat adaptation, such as the elderly and children, to determine a more reasonable final priority for PSI. Based on each tester's PSI value and priority performance, the system calculates the display percentage of each tester on the integrated display screen of the thermal endurance physiological stress index machine. This percentage determines the importance of the tester's information on the display screen, providing crucial information for subsequent display modules. Display module 3 can determine the display position and area of ​​each tester on the integrated display screen of the thermal endurance physiological stress index machine based on their corresponding display percentage, and display the corresponding tester information within the determined display area. A higher display percentage, a more prominent display position (e.g., upper left corner), and a larger display area allow the recorder to more intuitively and quickly focus on testers requiring key monitoring, achieving effective monitoring and management of the thermal endurance physiological stress index.

[0055] In specific application scenarios, such as Figure 2As shown, the acquisition module 1 may include a receiving unit 11 and an acquisition unit 12, which work together to acquire multi-source data. The receiving unit 11 is primarily responsible for receiving data transmitted from external devices. On one hand, it can receive the PSI values ​​of each test subject uploaded by the thermal endurance physiological stress index integrated machine. The PSI value is a key indicator for measuring an individual's physiological stress tolerance in a high-temperature environment. Receiving this data provides an important basis for subsequent assessment of the test subject's thermal endurance. On the other hand, the receiving unit 11 can also receive the body temperature and heart rate data of each test subject uploaded by a wearable wireless core body temperature and heart rate monitoring device. This wearable device includes an ear-hook core body temperature and heart rate monitoring device and / or a rectal core body temperature and heart rate monitoring device, which can monitor the test subject's physiological data in real time and transmit it to the receiving unit 11. For example, the ear-hook core body temperature and heart rate monitoring device is convenient to wear and can promptly acquire heart rate and body temperature information; the rectal core body temperature and heart rate monitoring device may more accurately reflect core body temperature changes in certain scenarios. This physiological data is crucial for analyzing the test subject's physical response in a hot environment. The data acquisition unit 12 is responsible for collecting user attribute data from each test subject. This data includes information such as age, height, and weight, which is an important supplement to assessing the test subject's heat tolerance. Different age groups and body types respond differently to heat stress; for example, the elderly and children are more susceptible to heat stress, while larger individuals have more difficulty dissipating heat. Collecting this data helps in a more comprehensive and accurate analysis of the test subject's heat tolerance, providing strong support for determining its priority and display method in monitoring the physiological stress index of heat tolerance.

[0056] In specific application scenarios, such as Figure 2 As shown, 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 works in sequence to gradually complete the process of calculating the high-risk coefficient of each test subject based on their body temperature data and heart rate data.

[0057] 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 and heart rate data of each test subject at each moment. In actual monitoring, the acquired body temperature and heart rate data may contain errors or be affected by external factors. True availability measures the reliability of these data in reflecting the test subject's true physiological state. For example, when the test subject is exercising vigorously, the heart rate monitoring device may produce inaccurate data due to shaking, and the true availability of the heart rate data at that moment will be low. By calculating the first true availability (for body temperature data) and the second true availability (for heart rate data), a more accurate basis can be provided for subsequent calculations based on these data.

[0058] Specifically, when calculating the first true usability of each test subject's body temperature data at each time point, the body temperature data of each test subject at each time point t can be determined. And body temperature data at time t corresponding to the two preceding times (time t-1 and time t-2). and Furthermore, the body temperature data at time t can be further analyzed. And body temperature data at time t corresponding to the two preceding times (t-1 and t-2). and Substituting the values ​​into the first calculation formula, the body temperature data of the test subject at time t can be calculated. The corresponding first real availability. The formula characteristics of the first calculation formula are described as follows:

[0059]

[0060] In the formula, represents the first true availability of test subject A's body temperature data at time t; exp represents an exponential function with base e; This represents the body temperature data of test subject A at time t; This represents the body temperature data of test subject A at time t-1; This represents the body temperature data of test subject A at time t-2; This represents the first change in test subject A's body temperature data at time t compared to the body temperature data at time t-1; This represents the second change in test subject A's body temperature data at time t-1 compared to the body temperature data at time t-2; This represents the absolute value of the difference between the first and second changes.

[0061] When calculating the second true availability of each tester's heart rate data at each time point, the heart rate data of each tester at each time point t can be determined. Heart rate data at time t corresponding to the two preceding times (t-1 and t-2). and Furthermore, the heart rate data at time t can be further analyzed. And heart rate data at time t corresponding to the two preceding times (t-1 and t-2). and Substituting the values ​​into the second calculation formula, the heart rate data of the test subject at time t can be calculated. The corresponding second true availability. The formula characteristics of the second calculation formula are described as follows:

[0062]

[0063] In the formula, represents the second true availability of the heart rate data of test subject A at time t; exp represents an exponential function with base e; This represents the heart rate data of test subject A at time t; This represents the heart rate data of test subject A at time t-1; This represents the heart rate data of test subject A at time t-2; This represents the third change in test subject A's heart rate data at time t compared to the heart rate data at time t-1; This indicates the fourth change in test subject A's heart rate data at time t-1 compared to the heart rate data at time t-2; This represents the absolute value of the difference between the third and fourth changes.

[0064] Specifically, the second calculation unit 22 can be used to calculate the rate of temperature rise on the temperature rise curve and the rate of temperature fall on the temperature fall curve for each test subject based on the first real availability, and to calculate the rate of heart rate rise on the heart rate rise curve and the rate of heart rate fall on the heart rate fall curve for each test subject based on the second real availability. Body temperature changes in a hot environment; by analyzing the temperature rise and fall curves, we can understand the test subject's response to heat stress. Combining the first real availability allows us to filter reliable data to calculate the rates of temperature rise and fall. For example, in the initial stage of heat exposure, body temperature rises rapidly; calculating the rate of rise indicates the rate at which the test subject's body produces heat. After heat exposure ends, body temperature falls; the rate of fall reflects the body's ability to dissipate heat. Heart rate is also an important indicator of the body's response to heat stress. In a hot environment, heart rate changes with changes in the body's metabolism. The second real availability is used to filter reliable heart rate data and calculate the rates of heart rate rise and fall. A rapid increase in heart rate may indicate that the body needs to transport oxygen and heat more quickly under heat stress, while a rapid decrease in heart rate reflects the body's ability to return to normal metabolism.

[0065] In calculating the rate of temperature rise on the temperature rise curve and the rate of temperature fall on the temperature fall curve for each test subject based on the first true availability, the following can be obtained first: Figure 3 The temperature rise and fall curves of test subject A are shown below. These curves include a temperature rise curve and a temperature fall curve, which intersect at time a. Furthermore, the following formula can be constructed to represent the temperature rise and fall curve function of test subject A (with unknown parameters). , , The curves showing the increase and decrease of body temperature intersect at time a, therefore... ):

[0066]

[0067]

[0068] In the formula, The value of the function representing the body temperature rise and fall curve of test subject A at time t; This indicates the rate of temperature rise for test subject A on the temperature rise curve; This indicates the rate of temperature decrease for test subject A on the temperature decrease curve; The function representing the body temperature rise and fall curve At that moment; This is the intercept of the function corresponding to the body temperature rise curve. This represents the intercept of the function corresponding to the curve of body temperature decrease.

[0069] Next, we need to solve for these unknown parameters by minimizing the error. First, we construct the following formula to represent the sum of errors in the body temperature rise and fall curve function of the above test subject A:

[0070]

[0071] In the formula, Let represent the sum of errors in the body temperature rise and fall curve function of test subject A, and n represent the data collected at a total of n time points. This represents the first true availability of test subject A's body temperature data at time t. This represents the body temperature of test subject A at time t. This represents the value of the body temperature rise and fall curve function for test subject A at time t. Let represent the squared error at time t. Let represent the squared error available at time t. Finally, by taking the partial derivatives of the above errors and assuming they are zero, the least squares method can be used to solve the system of equations to determine the solutions for all unknown parameters. Thus, the rate of body temperature rise can be determined. and rate of decrease in body temperature .

[0072] It should be noted that the calculation process for other test subjects is the same as that for test subject A. It involves constructing a similar body temperature rise and fall curve function, error, and formula, then using the least squares method to solve for the unknown parameters, thereby obtaining the rate of temperature rise for each test subject on the temperature rise curve. and the rate of decrease in body temperature on the body temperature decrease curve Based on the second real availability, the rate of heart rate rise for each test subject on the heart rate rise curve was calculated. and the rate of heart rate decrease on the heart rate decrease curve The calculation process is the same as that of test subject A, and will not be repeated here.

[0073] Specifically, the third calculation unit 23 can be used to calculate the high-risk coefficient for each test subject based on the rates of body temperature rise, body temperature fall, heart rate rise, and heart rate fall. By comprehensively considering the rates of change in body temperature and heart rate, the physiological risks to test subjects in a thermal environment can be assessed more comprehensively. For example, a rapid rate of both body temperature and heart rate rise may indicate that the test subject is experiencing greater stress under heat stress, resulting in a correspondingly higher high-risk coefficient. By calculating the high-risk coefficient, the heat tolerance and physiological risks of different test subjects can be quantitatively assessed, enabling targeted measures to be taken in the heat tolerance physiological stress index monitoring system, such as focusing on high-risk test subjects.

[0074] Specifically, when calculating the high-risk coefficient for each test subject based on the rates of body temperature rise, body temperature fall, heart rate rise, and heart rate fall, the third calculation unit 23 can determine the ratio of the rates of body temperature rise to fall as the corresponding test subject's body temperature rise / fall rate ratio, and the ratio of the rates of heart rate rise to fall as the corresponding test subject's heart rate rise / fall rate ratio; the product of the body temperature rise / fall rate ratio and the heart rate rise / fall rate ratio is determined as the corresponding test subject's high-risk coefficient. The corresponding formula is characterized as follows:

[0075]

[0076] In the formula, This indicates the high-risk factor for test subject A; This indicates the rate of temperature rise in test subject A; This indicates the rate at which test subject A's body temperature decreased; This indicates the rate at which test subject A's heart rate rises to its maximum. This indicates the rate at which test subject A's heart rate decreases. This indicates the ratio of the rate of increase to decrease in body temperature for test subject A; This indicates the ratio of the rate of increase to decrease in test subject A's heart rate.

[0077] Similarly, the high-risk coefficient for each test subject can be obtained by using the first calculation unit 21, the second calculation unit 22, and the third calculation unit 23.

[0078] In specific application scenarios, such as Figure 2 As shown, the data processing module 2 may also include: a fourth calculation unit 24 and a fifth calculation unit 25. Each unit works in turn to gradually complete the process of determining the priority of each tester's PSI performance based on the high-risk coefficient, PSI value and user attribute data corresponding to each tester.

[0079] Specifically, the fourth calculation unit 24 can be used to calculate the initial PSI priority performance of each test subject under the influence of body size, based on the high-risk coefficient, height, and weight values ​​of each test subject. Body size is an important factor in monitoring the physiological stress index of heat endurance because larger individuals usually have difficulty dissipating heat and have relatively poor thermoregulation. Even with the same high-risk coefficient, they may face greater risks in hot environments, so they need to be given higher priority.

[0080] Specifically, the fourth calculation unit 24, when calculating the initial PSI priority performance of each tester under the influence of body type based on the high-risk coefficient, height, and weight values ​​of each tester, can first calculate the body type difference of each tester compared to other testers based on their height and weight values; then, based on the high-risk coefficient and body type difference of each tester, calculate the body type influence coefficient of each tester; and finally, multiply the normalized data of each tester's body type influence coefficient with the high-risk coefficient to determine the initial PSI priority performance of the tester under the influence of body type. The corresponding formula feature description is as follows:

[0081]

[0082]

[0083] In the formula, denoted by , indicating the initial PSI priority of test subject A under the influence of body size; f represents the maximum and minimum value normalization function (compared to other test subjects); N represents the total number of test subjects; exp represents the exponential function with base e. This indicates the high-risk factor for test subject A; This represents the high-risk coefficient for test subject i; This indicates the degree of similarity between tester A and tester i regarding the high-risk coefficient; This represents the sum of the similarity between tester A and N other testers regarding the high-risk coefficient; This represents the percentage of tester i's high-risk similarity to tester A among N testers; This indicates the difference in body size between tester A and tester i; This represents the weight of test subject A; This represents the height of test subject A; This indicates the body type of test subject A; This represents the weight of test subject i; Indicates the height of test subject i; This represents the body size of test subject i; This represents the influence coefficient of test subject A's body shape.

[0084] Specifically, the fifth calculation unit 25 can, based on the initial PSI priority performance obtained from the fourth calculation unit 24, further consider the PSI value and the age of the test subject to calculate the PSI priority performance of each test subject under the influence of metabolic differences. This is because people of different ages have different physiological metabolisms and different abilities to adapt to hot environments. For example, the elderly and children have relatively poor adaptability to hot environments, and even if the initial PSI priority performance is the same, they require more attention.

[0085] Specifically, the fifth calculation unit 25, when calculating the PSI priority performance of each test subject under the influence of metabolic differences based on the initial PSI priority performance, PSI value, and age of each test subject, can calculate the target PSI age for multiple test subjects based on their PSI values ​​and ages; and calculate the PSI priority performance of each test subject under the influence of metabolic differences based on their initial PSI priority performance, age, and corresponding target PSI age. The corresponding formula characteristics are described as follows:

[0086]

[0087]

[0088] In the formula, This indicates the degree of PSI priority performance of test subject A under the influence of metabolic differences; f represents the maximum and minimum value normalization function (compared to other test subjects). This indicates the age of test subject A; This represents the target PSI age for N test subjects; This indicates the difference in age between test subject A and the target PSI; This indicates the initial PSI priority performance of test subject A under the influence of body size; N represents the total number of test subjects. represents the PSI value of tester i; exp represents an exponential function with base e; This indicates the optimality of PSI for tester i (because the lower the PSI, the better the thermal resistance). This indicates the relative optimality of the PSI of test i; This represents the age of test subject i.

[0089] In specific application scenarios, such as Figure 2 As shown, the data processing module 2 may also include: a sixth calculation unit 26 and a seventh calculation unit 27. Each unit works in sequence to gradually complete the process of calculating the display ratio of each test subject on the integrated display screen of the thermal endurance physiological stress index based on the PSI value and the priority performance of each PSI.

[0090] Specifically, the sixth calculation unit 26 can be used to calculate the PSI display parameter for each tester based on their PSI value and PSI priority performance level. The PSI display parameter is calculated as: PSI priority performance level × PSI value. For example, if tester A has a PSI value of 80 and a PSI priority performance level (calculated based on factors such as age and body type) of 1.2, then their PSI display parameter is 1.2 × 80 = 96.

[0091] The seventh calculation unit 27 can be used to calculate the display percentage of each test subject on the integrated display screen of the thermal endurance physiological stress index machine based on the PSI display parameters of each test subject. Specifically, it can calculate the sum of the PSI parameters of all test subjects; the ratio of each test subject's PSI display parameter to the sum of the PSI parameters is determined as the display percentage of the corresponding test subject on the integrated display screen of the thermal endurance physiological stress index machine. The corresponding formula feature description is:

[0092]

[0093] In the formula, This indicates the percentage of test subject A displayed on the integrated display screen of the thermal endurance physiological stress index machine; This indicates the degree of PSI priority performance of test subject A; This represents the PSI value of test subject A; This indicates the degree of PSI priority performance of tester i; This represents the PSI value of tester i; N represents the total number of testers. This indicates the PSI display parameters for tester A; This represents the sum of the PSI parameters displayed by all testers.

[0094] In specific application scenarios, such as Figure 2 As shown, the display module 3 may include a first determining unit 31, a second determining unit 32, and a display unit 33. Through the coordinated work of the three units, the display ratio calculated by the data processing module can be converted into the actual display effect, ensuring that the display screen of the thermal endurance physiological stress index integrated machine can highlight the key points and make it convenient for the recorder to focus on high-risk test subjects.

[0095] Specifically, the primary function of the first determining unit 31 is to determine the corresponding display area on the integrated display screen of the thermal endurance physiological stress index (PSI) machine based on the display percentage of each test subject. The display percentage is calculated comprehensively based on the test subject's PSI value, high-risk coefficient, and basic information. A higher percentage indicates that the test subject requires more attention. The first determining unit 31 can allocate the display area based on this percentage. For example, if test subject A's display percentage is 30%, and the total effective display area of ​​the screen is 100 square centimeters, then test subject A's corresponding display area might be 30 square centimeters. In this way, the importance of different test subjects can be intuitively distinguished from the display area; test subjects with higher percentages have a larger information display area and are more easily noticed.

[0096] The second determining unit 32 is used to sequentially determine the display position of each test subject within the remaining area of ​​the integrated display screen of the thermal endurance physiological stress index machine, according to the display priority order from largest to smallest display percentage. Specifically, when determining the display position, the second determining unit 32 will prioritize placing test subjects with high display percentages in prominent positions. For example, the test subject with the highest display percentage will be placed in the upper left corner of the screen, which is the area that people's visual attention will first focus on. Then, for the next test subject with a high display percentage, a position that meets the display area requirements will be searched in the remaining display area from left to right. If there is not enough space in the current row, a suitable position will be searched in the next row, selecting the largest available area in the remaining area that meets the requirements to place the test subject's information. In this way, important test subject information is ensured to be prominently displayed on the screen, making it convenient for the recorder to quickly obtain key information.

[0097] Display unit 33 is used to display corresponding test subject information within a display area defined by the display position and area. Specifically, after the display position and area are determined by the preceding two units, display unit 33 is responsible for displaying the corresponding test subject information within the designated display area. This information may include the test subject's basic information (such as age, height, and weight), real-time monitored body temperature and heart rate data, PSI value, and relevant safety prompts. Display unit 33 will present this information in a clear and easy-to-read manner according to the defined display area, ensuring that the recorder can clearly see the key data of each test subject, thereby promptly identifying potentially high-risk test subjects and taking appropriate measures.

[0098] In summary, the technical solution in this application calculates a high-risk coefficient using body temperature and heart rate data, comprehensively considering the physiological changes of the human body in a thermal environment. Then, combining the high-risk coefficient, PSI value, and user attribute data (such as age and body type), the priority of PSI display is determined. Considering that larger individuals have difficulty dissipating heat and poor thermal regulation, they are given a higher priority display level when the high-risk coefficient is the same. Simultaneously, for groups such as the elderly and children whose physiological metabolic differences lead to poor thermal adaptation, the final PSI priority is further adjusted. This multi-factor comprehensive consideration approach makes the priority distinction between different groups more reasonable, ensuring that high-risk groups receive due attention. Furthermore, according to the calculated display proportion, the display position and area of ​​the test subjects on the integrated display screen of the thermal endurance physiological stress index machine are reasonably arranged. This allows the recorder to quickly and intuitively identify test subjects requiring special attention, greatly improving monitoring efficiency and accuracy, and effectively solving the problem that traditional display methods cannot highlight key points.

[0099] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0100] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0101] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A multi-source data management system for monitoring the physiological stress index of heat tolerance, characterized in that, The multi-source data management system for monitoring the physiological stress index of heat endurance is applied to the integrated machine for monitoring the physiological stress index of heat endurance. The multi-source data management system for monitoring the physiological stress index of heat endurance includes: The acquisition module is used to acquire PSI values, body temperature data, heart rate data, and user attribute data for each test subject. The data processing module is used to calculate the high-risk coefficient of each test subject based on the body temperature data and heart rate data of each test subject; determine the priority performance degree of each test subject's PSI based on the high-risk coefficient, PSI value and user attribute data of each test subject; and calculate the display percentage of each test subject on the display screen of the thermal endurance physiological stress index all-in-one machine based on the PSI value and the priority performance degree of each test subject. The display module is used to determine the display position and display area of ​​each test subject in the display screen of the thermal endurance physiological tension index integrated machine based on the display ratio corresponding to each test subject, and to display the corresponding test subject information in the display area determined according to the display position and the display area; The data processing module further includes: The sixth calculation unit is used to calculate the PSI display parameters of each tester based on the PSI value of each tester and the priority of the PSI performance. The seventh calculation unit is used to calculate the display percentage of each test subject on the integrated display screen of the thermal endurance physiological stress index based on the PSI display parameters of each test subject. The seventh calculation unit is specifically used for: Calculate the cumulative sum of PSI parameters for all testers regarding the PSI displayed parameters; The ratio of the PSI display parameters of each test subject to the sum of the PSI parameters is determined as the display percentage of the corresponding test subject on the display screen of the thermal endurance physiological stress index integrated machine. The display module includes: The first determining unit is used to determine the display area in the display screen of the thermal endurance physiological stress index all-in-one machine corresponding to each of the display proportions; The second determining unit is used to determine the display position of each test subject in the remaining area of ​​the display screen of the thermal endurance physiological stress index integrated machine in descending order of display priority according to the display ratio; The display unit is used to display the corresponding tester information within the display area determined by the display position and the display area.

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

3. The multi-source data management system for monitoring the physiological stress index of heat tolerance according to claim 1, characterized in that, The data processing module includes: The first calculation unit is used to calculate the first real availability and the second real availability corresponding to the body temperature data and the heart rate data of each test subject at each time moment; The second calculation unit is used to calculate the rate of increase of body temperature on the body temperature rise curve and the rate of decrease of body temperature on the body temperature fall curve for each test subject based on the first real availability, and to calculate the rate of increase of heart rate on the heart rate rise curve and the rate of decrease of heart rate on the heart rate fall curve for each test subject based on the second real availability. The third calculation unit is used to calculate the high-risk coefficient of each test subject based on the rate of increase in body temperature, the rate of decrease in body temperature, the rate of increase in heart rate, and the rate of decrease in heart rate.

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

5. The multi-source data management system for monitoring the physiological stress index of heat tolerance 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: The fourth calculation unit is used 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, as well as the height value and the weight value. The fifth calculation unit is used to calculate the PSI priority performance of each test subject under the influence of metabolic differences, based on the initial PSI priority performance, the PSI value, and the age of each test subject.

6. The multi-source data management system for monitoring the physiological stress index of heat tolerance according to claim 5, characterized in that, The fourth calculation unit is specifically used for: Based on the height and weight values ​​of each test subject, calculate the body shape difference between each test subject and the other test subjects; Based on the high-risk coefficients of each test subject and the differences in body shape, the body shape influence coefficient of each test subject is calculated. The product of the normalized data of each test subject's body size influence coefficient and the high-risk coefficient is determined as the initial PSI priority performance of the test subject under the influence of body size.

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

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