A real-time monitoring and warning method and system for infants' body temperature

Abstract

The present invention relates to the technical field of health monitoring, and discloses a method and system for real-time monitoring and early warning of infants' body temperature. The method includes: collecting the user's body temperature and environmental temperature at fixed intervals; calculating the degree of abnormality according to the user's body temperature and historical user body temperature; adjusting the degree of abnormality according to the environmental temperature, and shortening the collection interval according to the final degree of abnormality; obtaining the user's body temperature fluctuation data after shortening the collection interval within a preset time period, and judging again whether the user's body temperature is abnormal according to the user's body temperature fluctuation data, calculating the body temperature difference between the maximum value and the minimum value of the user's body temperature within the preset time period, and calculating the user's body temperature fluctuation value between adjacent collections, and calculating the user's body temperature abnormality value according to the maximum value of the body temperature difference and the user's body temperature fluctuation value; obtaining the body temperature abnormality level according to the user's body temperature abnormality value, and giving an early warning of the body temperature abnormality level. The present invention realizes comprehensive analysis and dynamic adjustment, and improves the accuracy of body temperature abnormality early warning.

Description

Technical Field

[0001] The present invention relates to the technical field of health monitoring, and in particular, to a method and system for real-time monitoring and early warning of infants' body temperature. Background Art

[0002] Monitoring the body temperature of infants is an important means to ensure their healthy growth. Since the body temperature regulation function of infants has not yet developed completely, their body temperature is easily affected by factors such as environmental temperature and diseases, showing abnormal fluctuations.

[0003] Traditional body temperature monitoring methods mainly rely on parents or medical staff to measure manually, which have problems such as low measurement frequency, discontinuous data, and easy omission of abnormalities, and are difficult to meet the needs of real-time monitoring. In recent years, with the development of wearable devices and Internet of Things technologies, intelligent body temperature monitoring devices have gradually been applied to the field of infants' health management. However, existing technologies mainly focus on the collection and transmission of body temperature data, lacking the ability of comprehensive analysis and dynamic adjustment of abnormal body temperature. For example, in the case of large changes in environmental temperature, misjudgment is likely to occur. In addition, the existing methods analyze the body temperature fluctuations relatively simply and cannot accurately reflect the degree and trend of abnormal body temperature, resulting in insufficient timeliness and accuracy of early warning.

[0004] Therefore, it is necessary to provide a method and system for real-time monitoring and early warning of infants' body temperature to solve the problems of lack of comprehensive analysis and dynamic adjustment in the existing technology and inaccurate early warning of abnormal body temperature. Summary of the Invention

[0005] In view of this, the present invention proposes a method and system for real-time monitoring and early warning of infants' body temperature, aiming to solve the problems of lack of comprehensive analysis and dynamic adjustment in the existing technology and inaccurate early warning of abnormal body temperature.

[0006] On the one hand, the present invention proposes a method for real-time monitoring and early warning of infants' body temperature, including:

[0007] Collecting the user's body temperature and environmental temperature at fixed time intervals;

[0008] Preliminarily judging whether the user's body temperature is abnormal according to the user's body temperature and historical user body temperature. If the preliminary judgment result is abnormal, calculating the degree of abnormality according to the user's body temperature and historical user body temperature;

[0009] Judging whether to adjust the degree of abnormality according to the environmental temperature. If it is judged that adjustment is needed, adjusting the degree of abnormality according to the environmental temperature to obtain the final degree of abnormality, and shortening the collection interval according to the final degree of abnormality;

[0010] Obtain the user's body temperature fluctuation data after shortening the acquisition interval within a preset duration, and then determine again whether the user's body temperature is abnormal based on the user's body temperature fluctuation data. If the result of the re-judgment is abnormal, calculate the body temperature difference between the maximum value and the minimum value of the user's body temperature within the preset duration, and calculate the body temperature fluctuation values of adjacent acquisitions. Calculate the user's body temperature abnormality value based on the body temperature difference and the maximum value of the user's body temperature fluctuation values;

[0011] Obtain the body temperature abnormality level based on the user's body temperature abnormality value, and issue a warning for the body temperature abnormality level.

[0012] Further, when initially determining whether the user's body temperature is abnormal based on the user's body temperature and the historical user's body temperature, it includes:

[0013] Set a safety threshold, obtain the highest value of the user's historical normal body temperature, and calculate the sum value of the safety threshold and the highest value of the user's historical normal body temperature;

[0014] If the user's body temperature is lower than the sum value, initially determine that the user's body temperature is not abnormal;

[0015] If the user's body temperature is greater than or equal to the sum value, initially determine that the user's body temperature is abnormal.

[0016] Further, when determining whether to adjust the abnormal degree based on the environmental temperature, it includes:

[0017] Set the highest value of the environmental temperature. If the environmental temperature is higher than the highest value of the environmental temperature, determine that the abnormal degree needs to be adjusted;

[0018] If the environmental temperature is lower than or equal to the highest value of the environmental temperature, determine that the abnormal degree does not need to be adjusted.

[0019] Further, when it is determined that adjustment is required, and the abnormal degree is adjusted according to the environmental temperature to obtain the final abnormal degree, it includes:

[0020] Calculate the difference between the environmental temperature and the highest value of the environmental temperature, set a first difference and a second difference, and the first difference is less than the second difference;

[0021] If the difference is less than the first difference, adjust the abnormal degree through a first adjustment coefficient;

[0022] If the difference is greater than or equal to the first difference and less than or equal to the second difference, adjust the abnormal degree through a second adjustment coefficient;

[0023] If the difference is greater than the second difference, adjust the abnormal degree through a third adjustment coefficient;

[0024] Among them, the value range of the adjustment coefficient is 1 > the first adjustment coefficient > the second adjustment coefficient > the third adjustment coefficient > 0, and the final abnormality degree is the product value of the abnormality degree and the adjustment coefficient.

[0025] Further, when shortening the acquisition interval duration according to the final abnormality degree, it includes:

[0026] Set a first abnormality degree limit value and a second abnormality degree limit value, and the first abnormality degree limit value is less than the second abnormality degree limit value;

[0027] If the final abnormality degree is less than the first abnormality degree limit value, adjust the acquisition interval duration through a first shortening coefficient;

[0028] If the final abnormality degree is greater than or equal to the first abnormality degree limit value and less than or equal to the second abnormality degree limit value, adjust the acquisition interval duration through a second shortening coefficient;

[0029] If the final abnormality degree is greater than the second abnormality degree limit value, adjust the acquisition interval duration through a third shortening coefficient;

[0030] Among them, the value range of the shortening coefficient is 1 > the first shortening coefficient > the second shortening coefficient > the third shortening coefficient > 0; and the shortened acquisition interval duration is the product value of the acquisition interval duration before shortening and the shortening coefficient.

[0031] Further, when re - judging whether the user's body temperature is abnormal according to the user's body temperature fluctuation data, it includes:

[0032] If the user's body temperature data collected after shortening the acquisition interval duration within the preset duration are all less than the highest value of the user's historical normal body temperature, the re - judgment result is that the user's body temperature is not abnormal;

[0033] Otherwise, the re - judgment result is that the user's body temperature is abnormal.

[0034] Further, when calculating the body temperature difference between the maximum value and the minimum value of the user's body temperature within the preset duration, calculating the body temperature fluctuation value of adjacent acquisitions, and calculating the user's body temperature abnormality value according to the body temperature difference and the maximum value of the user's body temperature fluctuation value, it includes:

[0035] Calculate the body temperature difference through the following formula:

[0036] ΔT = Tmax - Tmin;

[0037] In the above formula, ΔT represents the body temperature difference, Tmax represents the maximum value of the user's body temperature within the preset duration, and Tmin represents the minimum value of the user's body temperature within the preset duration;

[0038] Calculate the user body temperature fluctuation value between adjacent collections by the following formula:

[0039] ΔTj = ∣T i - T i-1 ∣;

[0040] In the above formula, ΔTj represents the body temperature fluctuation value of the j-th user, j = 1, 2, 3, …, n; T i is the body temperature of the user collected for the i-th time, and T i-1 is the body temperature of the user collected for the (i - 1)-th time; i = 2, 3, …, n;

[0041] Extract the maximum value from all the user body temperature fluctuation values between adjacent collections by the following formula:

[0042] ΔTmax = max(ΔT1, ΔT2, ΔT3, …, ΔTn);

[0043] In the above formula, ΔTmax represents the maximum value of the user body temperature fluctuation value, and ΔTj represents the body temperature fluctuation value of the j-th user, j = 1, 2, 3, …, n;

[0044] Calculate the user body temperature anomaly value by the following formula:

[0045]

[0046] In the above formula, A represents the user body temperature anomaly value, ΔT represents the body temperature difference, and ΔTmax represents the maximum value of the user body temperature fluctuation value.

[0047] Further, when obtaining the body temperature anomaly level according to the user body temperature anomaly value and performing a body temperature anomaly level warning, it includes:

[0048] Set a first anomaly value and a second anomaly value, where the first anomaly value is less than the second anomaly value;

[0049] If the user body temperature anomaly value is less than or equal to the first anomaly value, the body temperature anomaly level is level one, and a body temperature anomaly level one warning is performed;

[0050] If the user body temperature anomaly value is greater than the first anomaly value and less than or equal to the second anomaly value, the body temperature anomaly level is level two, and a body temperature anomaly level two warning is performed;

[0051] If the user body temperature anomaly value is greater than the second anomaly value, the body temperature anomaly level is level three, and a body temperature anomaly level three warning is performed;

[0052] The body temperature anomaly levels are level one, level two, and level three from low to high, and the warning levels are level one warning, level two warning, and level three warning from low to high.

[0053] Compared with the prior art, the beneficial effects of the present invention are as follows: By collecting the user's body temperature and environmental temperature at fixed intervals, it is possible to monitor the real-time changes in the body temperature of infants and young children, and conduct comprehensive analysis in combination with the environmental temperature, improving the accuracy of the data. Secondly, by initially judging the body temperature abnormality based on historical body temperature data and dynamically adjusting the degree of abnormality in combination with the environmental temperature, it is possible to effectively avoid misjudgment caused by changes in the environmental temperature and improve the accuracy of early warning. In addition, by shortening the collection interval according to the final degree of abnormality, it is possible to quickly respond when the body temperature is abnormal, obtain more detailed body temperature fluctuation data in a timely manner, and further enhance the real-time performance and sensitivity of monitoring. Finally, by calculating the body temperature difference and the body temperature fluctuation value of adjacent collections, comprehensively evaluating the body temperature abnormality value, and dividing the body temperature abnormality level according to the abnormality value, it is possible to provide clear early warning information for parents or medical staff, facilitating the adoption of corresponding intervention measures. This method not only improves the intelligent level of infant body temperature monitoring, but also provides a scientific basis for the health management of infants and young children, and has important practical application value.

[0054] On the other hand, the present application also provides a real-time monitoring and early warning system for infant body temperature, including:

[0055] A collection module configured to collect the user's body temperature and environmental temperature at fixed intervals;

[0056] A preliminary judgment module configured to preliminarily judge whether the user's body temperature is abnormal based on the user's body temperature and historical user body temperature. If the preliminary judgment result is abnormal, calculate the degree of abnormality based on the user's body temperature and historical user body temperature;

[0057] An adjustment module configured to judge whether to adjust the degree of abnormality according to the environmental temperature. If it is judged that adjustment is required, adjust the degree of abnormality according to the environmental temperature to obtain the final degree of abnormality, and shorten the collection interval according to the final degree of abnormality;

[0058] A re-judgment module configured to obtain the user's body temperature fluctuation data after shortening the collection interval within a preset time period, re-judge whether the user's body temperature is abnormal based on the user's body temperature fluctuation data. If the re-judgment result is abnormal, calculate the body temperature difference between the maximum and minimum body temperatures of the user within the preset time period, and calculate the body temperature fluctuation value of adjacent collections, and calculate the user's body temperature abnormality value based on the body temperature difference and the maximum value of the user's body temperature fluctuation value;

[0059] An early warning module configured to obtain the body temperature abnormality level based on the user's body temperature abnormality value and issue an early warning of the body temperature abnormality level.

[0060] It can be understood that the real-time monitoring and early warning method and system for infant body temperature provided by the present application have the same beneficial effects, which will not be elaborated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] By reading the following detailed description of the preferred embodiments, various other advantages and benefits will become clear to those of ordinary skill in the art. The drawings are only for the purpose of showing the preferred embodiments and are not considered to be a limitation of the present invention. Moreover, throughout the drawings, the same reference numerals are used to represent the same components. In the drawings:

[0062] Figure 1 It is a flowchart of the real-time monitoring and warning method for the body temperature of infants and young children provided by an embodiment of the present invention;

[0063] Figure 2 It is a functional block diagram of the real-time monitoring and warning system for the body temperature of infants and young children provided by an embodiment of the present invention. Detailed Embodiments

[0064] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the drawings. Although the exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be fully conveyed to those skilled in the art. It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the drawings and in combination with the embodiments.

[0065] In some embodiments of the present application, referring to Figure 1 as shown, this embodiment provides a real-time monitoring and warning method for the body temperature of infants and young children, including the following steps:

[0066] S100. Collect the user's body temperature and environmental temperature at fixed intervals;

[0067] S200. Initially determine whether the user's body temperature is abnormal based on the user's body temperature and historical user body temperature. If the initial determination result is abnormal, calculate the degree of abnormality based on the user's body temperature and historical user body temperature;

[0068] S300. Determine whether to adjust the degree of abnormality according to the environmental temperature. If it is determined that adjustment is required, adjust the degree of abnormality according to the environmental temperature to obtain the final degree of abnormality, and shorten the collection interval according to the final degree of abnormality;

[0069] S400. Obtain the user's body temperature fluctuation data after shortening the collection interval within a preset duration, and determine again whether the user's body temperature is abnormal based on the user's body temperature fluctuation data. If the re-determination result is abnormal, calculate the body temperature difference between the maximum and minimum values of the user's body temperature within the preset duration, and calculate the user's body temperature fluctuation value between adjacent collections. Calculate the user's body temperature abnormality value based on the maximum value of the body temperature difference and the user's body temperature fluctuation value;

[0070] S500. Obtain the body temperature abnormality level based on the abnormal body temperature value of the user, and issue a warning for the body temperature abnormality level.

[0071] It can be understood that by collecting the user's body temperature and environmental temperature at fixed intervals, the change of the body temperature of infants can be monitored in real time, and comprehensive analysis can be carried out in combination with the environmental temperature, improving the accuracy of the data. Secondly, by initially judging the body temperature abnormality based on the historical body temperature data and dynamically adjusting the degree of abnormality in combination with the environmental temperature, the misjudgment caused by the change of the environmental temperature can be effectively avoided, and the accuracy of the warning can be improved. In addition, by shortening the collection interval according to the final degree of abnormality, a quick response can be made when the body temperature is abnormal, and more detailed body temperature fluctuation data can be obtained in time, further enhancing the real-time performance and sensitivity of the monitoring. Finally, by calculating the body temperature difference and the body temperature fluctuation value of adjacent collections, comprehensively evaluating the abnormal body temperature value, and dividing the body temperature abnormality level according to the abnormal value, clear warning information can be provided for parents or medical staff, facilitating the adoption of corresponding intervention measures. This method not only improves the intelligent level of infant body temperature monitoring, but also provides a scientific basis for infant health management, and has important practical application value.

[0072] In some embodiments of the present application, when initially judging whether the user's body temperature is abnormal based on the user's body temperature and historical user body temperature, it includes:

[0073] Set a safety threshold, obtain the highest value of the user's historical normal body temperature, and calculate the sum value of the safety threshold and the highest value of the user's historical normal body temperature;

[0074] If the user's body temperature is lower than the sum value, it is initially judged that the user's body temperature is not abnormal;

[0075] If the user's body temperature is greater than or equal to the sum value, it is initially judged that the user's body temperature is abnormal.

[0076] It can be understood that by calculating the sum value of the safety threshold and the highest value of the historical normal body temperature, the abnormal judgment standard can be dynamically adjusted, avoiding misjudgment caused by individual differences or environmental changes, and improving the accuracy of the judgment. Secondly, this method is simple and efficient, and only needs to compare the current body temperature with the preset sum value to quickly judge whether it is abnormal, which is suitable for real-time monitoring scenarios. In addition, by analyzing in combination with historical data, the normal body temperature range of the user can be better reflected, reducing the overreaction to accidental fluctuations and enhancing the judgment stability. This preliminary judgment method based on the safety threshold and historical data not only improves the reliability of body temperature abnormality detection, but also provides a reliable basis for subsequent detailed analysis and warning, and has important practical application value.

[0077] In some embodiments of the present application, when judging whether to adjust the degree of abnormality according to the environmental temperature, it includes:

[0078] Set the maximum environmental temperature. If the environmental temperature is higher than the maximum environmental temperature, it is determined that the degree of abnormality needs to be adjusted.

[0079] If the environmental temperature is lower than or equal to the maximum environmental temperature, it is determined that the degree of abnormality does not need to be adjusted.

[0080] In some embodiments of the present application, when it is determined that adjustment is required and the degree of abnormality is adjusted according to the environmental temperature to obtain the final degree of abnormality, it includes:

[0081] Calculate the difference between the environmental temperature and the maximum environmental temperature, and set a first difference and a second difference, where the first difference is less than the second difference.

[0082] If the difference is less than the first difference, adjust the degree of abnormality by the first adjustment coefficient.

[0083] If the difference is greater than or equal to the first difference and less than or equal to the second difference, adjust the degree of abnormality by the second adjustment coefficient.

[0084] If the difference is greater than the second difference, adjust the degree of abnormality by the third adjustment coefficient.

[0085] Among them, the value range of the adjustment coefficient is 1 > the first adjustment coefficient > the second adjustment coefficient > the third adjustment coefficient > 0, and the final degree of abnormality is the product value of the degree of abnormality and the adjustment coefficient.

[0086] It can be understood that by setting the maximum environmental temperature and calculating the difference between it and the environmental temperature, the influence of the environmental temperature on the body temperature abnormality judgment can be effectively identified, avoiding misjudgment caused by high-temperature environments and improving accuracy. Secondly, by adopting a segmented adjustment strategy and selecting different adjustment coefficients according to the size of the difference, the influence degree of the environmental temperature on the degree of abnormality can be finely reflected, making the adjustment more scientific and reasonable. In addition, by multiplying the degree of abnormality by the adjustment coefficient to obtain the final degree of abnormality, the abnormality judgment result can be dynamically corrected, enhancing adaptability and robustness. This method not only improves the accuracy of body temperature abnormality judgment but also provides more reliable data support for subsequent early warning and intervention, having important practical application value.

[0087] In some embodiments of the present application, when shortening the acquisition interval duration according to the final degree of abnormality, it includes:

[0088] Set a first abnormality degree limit value and a second abnormality degree limit value, where the first abnormality degree limit value is less than the second abnormality degree limit value.

[0089] If the final degree of abnormality is less than the first abnormality degree limit value, adjust the acquisition interval duration by the first shortening coefficient.

[0090] If the final abnormal degree is greater than or equal to the first abnormal degree limit value and less than or equal to the second abnormal degree limit value, the acquisition interval duration is adjusted by the second shortening coefficient;

[0091] If the final abnormal degree is greater than the second abnormal degree limit value, the acquisition interval duration is adjusted by the third shortening coefficient;

[0092] Among them, the value range of the shortening coefficient is 1 > the first shortening coefficient > the second shortening coefficient > the third shortening coefficient > 0; and the shortened acquisition interval duration is the product value of the acquisition interval duration before shortening and the shortening coefficient.

[0093] It can be understood that by setting the first abnormal degree limit value and the second abnormal degree limit value and adopting a segmented adjustment strategy, the acquisition frequency can be flexibly adjusted according to the severity of the abnormal degree, ensuring a lower acquisition frequency when the body temperature abnormality is relatively mild to save resources, and quickly increasing the acquisition frequency when the abnormal degree is relatively high to obtain more detailed body temperature data, thereby improving the efficiency and accuracy of monitoring. Secondly, the setting of the shortening coefficient makes the adjustment of the acquisition interval duration more refined, and can dynamically optimize the data acquisition strategy according to the change of the abnormal degree. In addition, by shortening the acquisition interval duration, more subtle body temperature fluctuations can be captured in a timely manner when the body temperature is abnormal, providing more comprehensive data support for subsequent abnormal judgment and early warning. This method not only improves the real-time performance and sensitivity of monitoring, but also optimizes the resource utilization efficiency.

[0094] In some embodiments of the present application, when re-determining whether the user's body temperature is abnormal according to the user's body temperature fluctuation data, it includes:

[0095] If all the user's body temperature data collected after shortening the acquisition interval duration within the preset duration are less than the maximum value of the user's historical normal body temperature, the re-determination result is that the user's body temperature is not abnormal;

[0096] Otherwise, the re-determination result is that the user's body temperature is abnormal.

[0097] In some embodiments of the present application, when calculating the body temperature difference between the maximum value and the minimum value of the user's body temperature within the preset duration, and calculating the user's body temperature fluctuation value between adjacent acquisitions, and calculating the user's body temperature abnormal value according to the body temperature difference and the maximum value of the user's body temperature fluctuation value, it includes:

[0098] The body temperature difference is calculated by the following formula:

[0099] ΔT = Tmax - Tmin;

[0100] In the above formula, ΔT represents the body temperature difference, Tmax represents the maximum value of the user's body temperature within the preset duration, and Tmin represents the minimum value of the user's body temperature within the preset duration;

[0101] Calculate the user body temperature fluctuation value between adjacent acquisitions by the following formula:

[0102] ΔTj = ∣T i -T i-1 ∣;

[0103] In the above formula, ΔTj represents the body temperature fluctuation value of the j-th user, j = 1, 2, 3, …, n; T i is the body temperature of the user collected for the i-th time, and T i-1 is the body temperature of the user collected for the (i - 1)-th time; i = 2, 3, …, n;

[0104] Extract the maximum value from all the user body temperature fluctuation values between adjacent acquisitions by the following formula:

[0105] ΔTmax = max(ΔT1, ΔT2, ΔT3, …, ΔTn);

[0106] In the above formula, ΔTmax represents the maximum value of the user body temperature fluctuation value, and ΔTj represents the body temperature fluctuation value of the j-th user, j = 1, 2, 3, …, n;

[0107] Calculate the user body temperature anomaly value by the following formula:

[0108]

[0109] In the above formula, A represents the user body temperature anomaly value, ΔT represents the body temperature difference, and ΔTmax represents the maximum value of the user body temperature fluctuation value.

[0110] It can be understood that by calculating the difference between the maximum and minimum body temperatures within a preset time period, the overall change range of the body temperature can be reflected, thereby capturing the abnormal fluctuation trend of the body temperature. Secondly, by calculating the body temperature fluctuation values between adjacent acquisitions and extracting the maximum value thereof, the instantaneous fluctuation situation of the body temperature can be further identified, enhancing the sensitivity to abnormal signals. Finally, by comprehensively calculating the body temperature difference and the maximum value of the body temperature fluctuation value to calculate the user body temperature anomaly value, the abnormal degree of the body temperature can be comprehensively evaluated, avoiding misjudgment that may be caused by a single index. This method not only improves the accuracy and reliability of body temperature abnormality judgment, but also provides a scientific basis for subsequent body temperature abnormality level classification and early warning, and has important practical application value. At the same time, by re-judging whether the user body temperature is abnormal, the preliminary judgment result can be further verified, enhancing the robustness and intelligent level of the judgment.

[0111] In some embodiments of the present application, when obtaining the body temperature abnormality level based on the user body temperature anomaly value and performing a body temperature abnormality level early warning, it includes:

[0112] Set a first anomaly value and a second anomaly value, where the first anomaly value is less than the second anomaly value;

[0113] If the abnormal body temperature value of the user is less than or equal to the first abnormal value, the body temperature abnormality level is the first level, and a first-level warning for body temperature abnormality is issued;

[0114] If the abnormal body temperature value of the user is greater than the first abnormal value and less than or equal to the second abnormal value, the body temperature abnormality level is the second level, and a second-level warning for body temperature abnormality is issued;

[0115] If the abnormal body temperature value of the user is greater than the second abnormal value, the body temperature abnormality level is the third level, and a third-level warning for body temperature abnormality is issued;

[0116] The body temperature abnormality levels are, from low to high, the first level, the second level, and the third level, and the warning levels are, from low to high, the first-level warning, the second-level warning, and the third-level warning.

[0117] It can be understood that by dividing the first abnormal value and the second abnormal value, the degree of body temperature abnormality is refined into three levels, which can more accurately reflect the severity of body temperature abnormality and provide a clear reference basis for parents or medical staff. Secondly, triggering corresponding warnings according to different abnormal levels can achieve hierarchical response, avoid overreaction to minor abnormalities, and at the same time ensure timely intervention measures for serious abnormalities, improving the pertinence and practicality of warnings. In addition, this hierarchical warning mechanism can effectively reduce the false alarm rate and enhance the reliability and user experience of the system. Through multi-level abnormal levels and warning designs, this method not only improves the intelligent level of body temperature monitoring but also provides scientific and flexible support for the health management of infants and young children, with important practical application value.

[0118] On the other hand, referring to Figure 2 as shown, the present application also provides an infant body temperature real-time monitoring and warning system for applying the above-mentioned infant body temperature real-time monitoring and warning method, including:

[0119] An acquisition module configured to acquire the user's body temperature and the environmental temperature at fixed time intervals;

[0120] A preliminary judgment module configured to preliminarily judge whether the user's body temperature is abnormal according to the user's body temperature and the historical user body temperature. If the preliminary judgment result is abnormal, calculate the degree of abnormality according to the user's body temperature and the historical user body temperature;

[0121] An adjustment module configured to judge whether to adjust the degree of abnormality according to the environmental temperature. If it is judged that adjustment is required, adjust the degree of abnormality according to the environmental temperature to obtain the final degree of abnormality, and shorten the acquisition interval according to the final degree of abnormality;

[0122] A re - judgment module, configured to obtain the user's body temperature fluctuation data after shortening the acquisition interval within a preset duration, re - judge whether the user's body temperature is abnormal according to the user's body temperature fluctuation data. If the re - judgment result is abnormal, calculate the body temperature difference between the maximum value and the minimum value of the user's body temperature within the preset duration, and calculate the body temperature fluctuation value of adjacent acquisitions. Calculate the user's body temperature abnormality value according to the body temperature difference and the maximum value of the user's body temperature fluctuation value;

[0123] An early - warning module, configured to obtain the body temperature abnormality level according to the user's body temperature abnormality value and perform an early - warning of the body temperature abnormality level.

[0124] It can be understood that, firstly, the acquisition module can acquire the user's body temperature and environmental temperature at fixed intervals, ensuring the real - time and continuity of data, and providing a reliable basis for subsequent analysis. Secondly, the preliminary judgment module quickly judges whether the body temperature is abnormal by combining historical body temperature data and safety thresholds, and calculates the degree of abnormality, improving the efficiency and accuracy of abnormality detection. The adjustment module dynamically adjusts the degree of abnormality according to the environmental temperature, avoiding misjudgment caused by changes in the environmental temperature, and enhancing the adaptability and robustness of the system. The re - judgment module further verifies the abnormal situation by analyzing the body temperature fluctuation data after shortening the acquisition interval, and calculates the body temperature abnormality value by combining the body temperature difference and the fluctuation value, ensuring the scientific and comprehensive nature of the abnormal judgment. Finally, the early - warning module classifies the abnormality level according to the body temperature abnormality value and triggers the corresponding early - warning, realizing hierarchical response, which not only avoids over - reaction to minor abnormalities but also can take intervention measures in a timely manner for serious abnormalities. Through the collaborative work of multiple modules, this system not only improves the accuracy and real - time of body temperature monitoring but also provides intelligent and scientific support for the health management of infants and young children, having important practical application value.

[0125] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer - usable storage media (including but not limited to disk storage, CD - ROM, optical storage, etc.) containing computer - usable program code.

[0126] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of flows and / or blocks in the flowchart and / or block diagram. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or means for implementing the functions specified in one block or multiple blocks.

[0127] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or means for implementing the functions specified in one block or multiple blocks.

[0128] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or means for implementing the functions specified in one block or multiple blocks.

[0129] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: it is still possible to modify the specific implementation manners of the present invention or make equivalent replacements, and any modification or equivalent replacement that does not depart from the spirit and scope of the present invention shall be covered by the protection scope of the claims of the present invention.

Claims

1. A method for real-time monitoring and early warning of infant body temperature, characterized in that: include: Collect user body temperature and ambient temperature at fixed intervals; Preliminarily determine whether the user's body temperature is abnormal based on the user's body temperature and historical user's body temperature. If the preliminary determination result is abnormal, calculate the degree of abnormality based on the user's body temperature and historical user's body temperature; Determine whether to adjust the abnormality degree according to the ambient temperature, and if it is determined that adjustment is required, adjust the abnormality degree according to the ambient temperature to obtain a final abnormality degree, and shorten the collection interval according to the final abnormality degree; Obtain the user's body temperature fluctuation data after shortening the collection interval within a preset time period, and judge again whether the user's body temperature is abnormal according to the user's body temperature fluctuation data. If the result of the second judgment is abnormal, calculate the body temperature difference between the maximum and minimum values ​​of the user's body temperature within the preset time period, and calculate the user's body temperature fluctuation values ​​collected adjacently, and calculate the user's body temperature abnormality value according to the body temperature difference and the maximum value of the user's body temperature fluctuation value; The abnormal body temperature level is obtained according to the abnormal body temperature value of the user, and an abnormal body temperature level warning is issued.

2. The method for real-time monitoring and early warning of infant body temperature according to claim 1, characterized in that: The preliminary determination of whether the user's body temperature is abnormal based on the user's body temperature and historical user's body temperature includes: Set a safety threshold, obtain the highest historical normal body temperature of the user, and calculate the sum of the safety threshold and the highest historical normal body temperature of the user; If the user's body temperature is lower than the sum value, it is preliminarily determined that the user's body temperature is not abnormal; If the user's body temperature is greater than or equal to the sum value, it is preliminarily determined that the user's body temperature is abnormal.

3. The method for real-time monitoring and early warning of infant body temperature according to claim 2, characterized in that: The determining whether to adjust the abnormality degree according to the ambient temperature includes: Setting a maximum value of the ambient temperature, if the ambient temperature is higher than the maximum value of the ambient temperature, determining that the abnormality level needs to be adjusted; If the ambient temperature is lower than or equal to the maximum ambient temperature value, it is determined that there is no need to adjust the abnormality degree.

4. The method for real-time monitoring and early warning of infant body temperature according to claim 3, characterized in that: If it is determined that adjustment is required, the abnormality degree is adjusted according to the ambient temperature to obtain a final abnormality degree, including: Calculate the difference between the ambient temperature and the maximum ambient temperature, set a first difference and a second difference, the first difference being smaller than the second difference; If the difference is smaller than the first difference, adjusting the abnormality level by a first adjustment coefficient; If the difference is greater than or equal to the first difference and less than or equal to the second difference, the abnormality degree is adjusted by a second adjustment coefficient; If the difference is greater than the second difference, adjusting the abnormality level by a third adjustment coefficient; The value range of the adjustment coefficient is 1>first adjustment coefficient>second adjustment coefficient>third adjustment coefficient>0, and the final abnormality degree is the product of the abnormality degree and the adjustment coefficient.

5. The method for real-time monitoring and early warning of infant body temperature according to claim 4, characterized in that: The shortening of the collection interval according to the final abnormality degree includes: Setting a first abnormality level limit and a second abnormality level limit, wherein the first abnormality level limit is smaller than the second abnormality level limit; If the final abnormality level is less than the first abnormality level limit, adjusting the collection interval length by a first shortening coefficient; If the final abnormality level is greater than or equal to the first abnormality level limit, and less than or equal to the second abnormality level limit, adjusting the collection interval duration by a second shortening coefficient; If the final abnormality level is greater than the second abnormality level limit, adjusting the collection interval length by a third shortening coefficient; The value range of the shortening coefficient is 1>first shortening coefficient>second shortening coefficient>third shortening coefficient>0; and the shortened collection interval is the product of the collection interval before shortening and the shortening coefficient.

6. The method for real-time monitoring and early warning of infant body temperature according to claim 5, characterized in that: The determining again whether the user's body temperature is abnormal according to the user's body temperature fluctuation data includes: If the user's body temperature data collected after shortening the collection interval within the preset time period are all lower than the user's highest historical normal body temperature, the result of the second judgment is that the user's body temperature is normal; Otherwise, the result of another determination is that the user's body temperature is abnormal.

7. The method for real-time monitoring and early warning of infant body temperature according to claim 6, characterized in that: The method of calculating the temperature difference between the maximum and minimum values ​​of the user's body temperature within a preset time period, calculating the user's body temperature fluctuation values ​​collected adjacently, and calculating the user's body temperature abnormality value according to the maximum value of the temperature difference and the user's body temperature fluctuation value includes: The body temperature difference is calculated by the following formula: ΔT = Tmax - Tmin; In the above formula, ΔT represents the body temperature difference, Tmax represents the maximum value of the user's body temperature within the preset time, and Tmin represents the minimum value of the user's body temperature within the preset time; The user's body temperature fluctuation value collected adjacently is calculated using the following formula: ΔTj=∣T i -T i-1 ∣; In the above formula, ΔTj represents the temperature fluctuation value of the jth user, j = 1, 2, 3, ..., n; T i is the user's body temperature collected for the i-th time, T i-1 The user's body temperature collected for the i-1th time; i = 2, 3, ..., n; The maximum value is extracted from all adjacent collected user temperature fluctuation values ​​using the following formula: ΔTmax=max(ΔT1, ΔT2, ΔT3,..., ΔTn); In the above formula, ΔTmax represents the maximum value of the user's body temperature fluctuation value, ΔTj represents the j-th user's body temperature fluctuation value, j=1, 2, 3, ..., n; The user's temperature abnormality value is calculated using the following formula: In the above formula, A represents the abnormal value of the user's body temperature, ΔT represents the body temperature difference, and ΔTmax represents the maximum value of the user's body temperature fluctuation.

8. The method for real-time monitoring and early warning of infant body temperature according to claim 7, characterized in that: The method of obtaining the abnormal temperature level according to the abnormal temperature value of the user and issuing an abnormal temperature level warning includes: Setting a first abnormal value and a second abnormal value, wherein the first abnormal value is smaller than the second abnormal value; If the abnormal body temperature value of the user is less than or equal to the first abnormal value, the abnormal body temperature level is level one, and a level one abnormal body temperature warning is issued; If the user's body temperature abnormal value is greater than the first abnormal value and less than or equal to the second abnormal value, the body temperature abnormal level is level 2, and a level 2 body temperature abnormality warning is issued; If the user's body temperature abnormal value is greater than the second abnormal value, the body temperature abnormal level is level three, and a level three body temperature abnormality warning is issued; The abnormal body temperature levels are level one, level two and level three from low to high, and the warning levels are level one warning, level two warning and level three warning from low to high.

9. A real-time monitoring and early warning system for infant body temperature, used for applying the real-time monitoring and early warning method for infant body temperature according to any one of claims 1 to 8, characterized in that: include: The collection module is configured to collect the user's body temperature and the ambient temperature at fixed intervals; A preliminary judgment module is configured to preliminarily judge whether the user's body temperature is abnormal based on the user's body temperature and the historical user's body temperature, and if the preliminary judgment result is abnormal, calculate the degree of abnormality based on the user's body temperature and the historical user's body temperature; an adjustment module, configured to determine whether to adjust the abnormality degree according to the ambient temperature, and if it is determined that adjustment is required, adjust the abnormality degree according to the ambient temperature to obtain a final abnormality degree, and shorten the collection interval according to the final abnormality degree; a second judgment module, configured to obtain the user's body temperature fluctuation data after shortening the collection interval within a preset time period, and judge again whether the user's body temperature is abnormal according to the user's body temperature fluctuation data; if the result of the second judgment is abnormal, the body temperature difference between the maximum and minimum values ​​of the user's body temperature within the preset time period is calculated, and the user's body temperature fluctuation values ​​collected adjacently are calculated, and the user's body temperature abnormality value is calculated according to the body temperature difference and the maximum value of the user's body temperature fluctuation value; The early warning module is configured to obtain an abnormal body temperature level according to the abnormal body temperature value of the user and to issue an abnormal body temperature level early warning.

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