Infant body temperature real-time monitoring and early warning method and system

Abstract

The invention relates to the technical field of health monitoring, and discloses an infant body temperature real-time monitoring and early warning method and system, and the method comprises the steps: collecting the body temperature of a user and the environment temperature at fixed time intervals; calculating an abnormal degree according to the user body temperature and historical user body temperatures; the abnormal degree is adjusted according to the environment temperature, and the collection interval duration is shortened according to the final abnormal degree; acquiring user body temperature fluctuation data after the acquisition interval duration is shortened in a preset duration, judging whether the user body temperature is abnormal or not again according to the user body temperature fluctuation data, calculating a body temperature difference value between a maximum value and a minimum value of the user body temperature in the preset duration, and calculating an adjacent acquired user body temperature fluctuation value; calculating a user body temperature abnormal value according to the body temperature difference value and the maximum value of the user body temperature fluctuation value; and obtaining a body temperature abnormal level according to the body temperature abnormal value of the user, and performing body temperature abnormal level early warning. According to the invention, comprehensive analysis and dynamic adjustment are realized, and the early warning accuracy of abnormal body temperature is improved.

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 infant body temperature. Background Art

[0002] Temperature monitoring for infants and young children is an important means to ensure their healthy growth. Since the temperature regulation function of infants and young children is not fully developed, their body temperature is easily affected by factors such as environmental temperature and disease, resulting in abnormal fluctuations.

[0003] Traditional body temperature monitoring methods mainly rely on manual measurement by parents or medical staff, which has problems such as low measurement frequency, discontinuous data, and easy omission of abnormalities, making it 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 equipment has gradually been applied to the field of infant health management. However, existing technologies mostly focus on the collection and transmission of body temperature data, and lack the ability to conduct comprehensive analysis and dynamic adjustment of abnormal body temperature. For example, when the ambient temperature changes greatly, misjudgment is prone to occur. In addition, the existing methods are relatively simple in analyzing body temperature fluctuations 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 infant body temperature to solve the problems of lack of comprehensive analysis and dynamic adjustment in the existing technology and inaccurate abnormal temperature warning. 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 infant body temperature, aiming to solve the problem that the prior art lacks comprehensive analysis and dynamic adjustment, and the abnormal temperature early warning is inaccurate.

[0006] On the one hand, the present invention provides a method for real-time monitoring and early warning of infant body temperature, comprising: 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.

[0007] Further, the preliminarily determining whether the user's body temperature is abnormal based on the user's body temperature and the 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.

[0008] Furthermore, if the preliminary determination result is that an abnormality occurs, the degree of abnormality is calculated based on the user's body temperature and historical user body temperatures, including: The abnormality degree is calculated by the following formula: Y = (H-Zmax) / Zmax; In the above formula, Y represents the degree of abnormality, H represents the sum of the safety threshold and the user's historical maximum normal body temperature, and Zmax represents the user's historical maximum normal body temperature.

[0009] Further, judging 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.

[0010] Furthermore, 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.

[0011] Further, shortening 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.

[0012] Further, judging 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.

[0013] Furthermore, the calculation of the temperature difference between the maximum and minimum values ​​of the user's body temperature within a preset time period, and the calculation of the user's body temperature fluctuation values ​​collected adjacently, and the calculation of 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 include: The body temperature difference is calculated by the following formula: ; 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: ; In the above formula, ΔTj represents the temperature fluctuation value of the jth user, j=1, 2, 3, …, n; Ti is the user's body temperature collected for the i-th time, For the The user's body temperature collected this 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 body 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.

[0014] Furthermore, 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.

[0015] Compared with the prior art, the beneficial effect of the present invention is that: by collecting the user's body temperature and the ambient temperature at fixed intervals, the temperature changes of infants and young children can be monitored in real time, and a comprehensive analysis is performed in combination with the ambient temperature, thereby improving the accuracy of the data. Secondly, the abnormal body temperature is preliminarily judged by the historical body temperature data, and the abnormal degree is dynamically adjusted in combination with the ambient temperature, which can effectively avoid the misjudgment caused by the change of the ambient temperature and improve the accuracy of the early warning. In addition, the collection interval is shortened according to the final abnormal degree, and 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 and sensitivity of the monitoring. Finally, by calculating the body temperature difference and the adjacent collected body temperature fluctuation values, comprehensively evaluating the abnormal body temperature value, and dividing the abnormal body temperature level according to the abnormal value, it can provide clear early warning information for parents or medical staff, so as to facilitate 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.

[0016] On the other hand, the present application also provides a real-time monitoring and early warning system for infant body temperature, comprising: 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.

[0017] It is understandable that the real-time monitoring and early warning method and system for infant body temperature provided in the present application have the same beneficial effects and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings: Figure 1 A flow chart of a method for real-time monitoring and early warning of infant body temperature provided by an embodiment of the present invention; Figure 2 This is a functional block diagram of a real-time monitoring and early warning system for infant body temperature provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0019] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features described in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0020] In some embodiments of the present application, see Figure 1 As shown, this embodiment provides a method for real-time monitoring and early warning of infant body temperature, including the following steps: S100, collecting user body temperature and ambient temperature at fixed intervals; S200, preliminarily determining whether the user's body temperature is abnormal based on the user's body temperature and historical user's body temperatures, and if the preliminary determination result is abnormal, calculating the degree of abnormality based on the user's body temperature and historical user's body temperatures; S300, judging whether to adjust the abnormality degree according to the ambient temperature, and if it is judged that adjustment is needed, adjusting the abnormality degree according to the ambient temperature to obtain a final abnormality degree, and shortening the collection interval according to the final abnormality degree; S400, obtaining the user's body temperature fluctuation data after shortening the collection interval within the preset time, and judging 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, calculating the body temperature difference between the maximum and minimum values ​​of the user's body temperature within the preset time, and calculating the user's body temperature fluctuation values ​​collected adjacently, 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; S500: Obtaining an abnormal body temperature level according to the abnormal body temperature value of the user, and issuing an abnormal body temperature level warning.

[0021] It is understandable that by collecting the user's body temperature and ambient temperature at fixed intervals, the temperature changes of infants and young children can be monitored in real time, and a comprehensive analysis can be performed in combination with the ambient temperature, thereby improving the accuracy of the data. Secondly, the abnormal body temperature can be preliminarily judged through historical body temperature data, and the degree of abnormality can be dynamically adjusted in combination with the ambient temperature, which can effectively avoid misjudgment caused by changes in ambient temperature and improve the accuracy of early warning. In addition, shortening the collection interval according to the final degree of abnormality can quickly respond to abnormal body temperature, obtain more detailed body temperature fluctuation data in time, and further enhance the real-time and sensitivity of monitoring. Finally, by calculating the body temperature difference and the adjacent collected body temperature fluctuation values, comprehensively evaluating the abnormal body temperature value, and dividing the abnormal body temperature level according to the abnormal value, it can provide parents or medical staff with clear early warning information, so as to facilitate the adoption of corresponding intervention measures. This method not only improves the intelligent level of infant temperature monitoring, but also provides a scientific basis for infant health management, and has important practical application value.

[0022] In some embodiments of the present application, when preliminarily determining whether the user's body temperature is abnormal based on the user's body temperature and historical user's body temperature, the process 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, it is preliminarily determined that the user's body temperature is normal; If the user's body temperature is greater than or equal to the sum, it is preliminarily determined that the user's body temperature is abnormal.

[0023] It is understandable that by calculating the sum of the safety threshold and the historical normal body temperature maximum value, the abnormal judgment standard can be dynamically adjusted to avoid misjudgment due to individual differences or environmental changes, thereby improving the accuracy of the judgment. Secondly, this method is simple and efficient. It only needs to compare the current body temperature with the preset sum to quickly determine whether it is abnormal, which is suitable for real-time monitoring scenarios. In addition, combined with historical data for analysis, it can better reflect the user's normal body temperature range, reduce overreaction to accidental fluctuations, and enhance judgment stability. This preliminary judgment method based on safety thresholds and historical data not only improves the reliability of abnormal body temperature detection, but also provides a reliable basis for subsequent detailed analysis and early warning, and has important practical application value.

[0024] In some embodiments of the present application, if the preliminary determination result is that an abnormality has occurred, the degree of abnormality is calculated based on the user's body temperature and the historical user's body temperature, including: The degree of abnormality is calculated by the following formula: Y = (H-Zmax) / Zmax; In the above formula, Y represents the degree of abnormality, H represents the sum of the safety threshold and the user's historical maximum normal body temperature, and Zmax represents the user's historical maximum normal body temperature.

[0025] It is understandable that by normalizing the deviation between the current body temperature and the highest historical normal body temperature, the degree of abnormal body temperature can be quantified, making the abnormal judgment more scientific and objective. Secondly, by combining the safety threshold and the sum of the highest historical normal body temperature, the calculation basis of the abnormal degree can be dynamically adjusted to avoid misjudgment due to individual differences or environmental changes, thereby improving the accuracy of the judgment.

[0026] In some embodiments of the present application, judging whether to adjust the abnormality degree according to the ambient temperature includes: Set the maximum value of the ambient temperature. If the ambient temperature is higher than the maximum value, it is determined that the abnormality needs to be adjusted. If the ambient temperature is lower than or equal to the maximum ambient temperature, it is determined that there is no need to adjust the abnormality level.

[0027] In some embodiments of the present application, if it is determined that adjustment is required, the abnormality degree is adjusted according to the ambient temperature to obtain the final abnormality degree, including: Calculate the difference between the ambient temperature and the maximum ambient temperature, set a first difference and a second difference, and the first difference is smaller than the second difference; If the difference is less than the first difference, the degree of abnormality is adjusted by the 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 degree of abnormality is adjusted by the second adjustment coefficient; If the difference is greater than the second difference, the degree of abnormality is adjusted 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.

[0028] It is understandable that by setting the maximum value of the ambient temperature and calculating the difference between it and the ambient temperature, the influence of the ambient temperature on the judgment of abnormal body temperature can be effectively identified, and misjudgment caused by high temperature environment can be avoided, thereby improving accuracy. Secondly, by adopting a segmented adjustment strategy and selecting different adjustment coefficients according to the size of the difference, the influence of the ambient 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 abnormal judgment result can be dynamically corrected to enhance adaptability and robustness. This method not only improves the accuracy of abnormal body temperature judgment, but also provides more reliable data support for subsequent early warning and intervention, and has important practical application value.

[0029] In some embodiments of the present application, shortening the collection interval according to the final abnormality level includes: Setting a first abnormality degree limit and a second abnormality degree limit, wherein the first abnormality degree limit is smaller than the second abnormality degree limit; If the final abnormality level is less than the first abnormality level limit, the collection interval length is adjusted by the 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, the collection interval duration is adjusted by the second shortening coefficient; If the final abnormality level is greater than the second abnormality level limit, the collection interval length is adjusted by the third shortening factor; 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.

[0030] It is understandable that by setting the first abnormality limit and the second abnormality limit, and adopting a segmented adjustment strategy, the collection frequency can be flexibly adjusted according to the severity of the abnormality, ensuring that a low collection frequency is maintained when the temperature abnormality is mild to save resources, and quickly increasing the collection frequency when the abnormality is high to obtain more detailed temperature data, thereby improving the efficiency and accuracy of monitoring. Secondly, the setting of the shortening coefficient makes the adjustment of the collection interval more refined, and the data collection strategy can be dynamically optimized according to changes in the degree of abnormality. In addition, by shortening the collection interval, more subtle temperature fluctuations can be captured in time when the temperature is abnormal, providing more comprehensive data support for subsequent abnormal judgments and early warnings. This method not only improves the real-time and sensitivity of monitoring, but also optimizes resource utilization efficiency.

[0031] In some embodiments of the present application, when determining again whether the user's body temperature is abnormal based on the user's body temperature fluctuation data, the process 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.

[0032] In some embodiments of the present application, the temperature difference between the maximum and minimum values ​​of the user's body temperature within a preset time period is calculated, and the user's body temperature fluctuation values ​​collected adjacently are calculated. When the user's body temperature abnormality value is calculated according to the maximum value of the temperature difference and the user's body temperature fluctuation value, the method includes: The temperature difference is calculated by the following formula: ; 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: ; 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, For the The user's body temperature collected this 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 body 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.

[0033] It is understandable that by calculating the difference between the maximum and minimum body temperature within a preset time, the overall range of body temperature changes can be reflected, thereby capturing the abnormal fluctuation trend of body temperature. Secondly, by calculating the adjacent collected temperature fluctuation values ​​and extracting their maximum values, the instantaneous fluctuation of body temperature can be further identified, and the sensitivity to abnormal signals can be enhanced. Finally, by calculating the user's abnormal temperature value by combining the temperature difference and the maximum temperature fluctuation value, the degree of abnormality of body temperature can be comprehensively evaluated to avoid misjudgment that may be caused by a single indicator. This method not only improves the accuracy and reliability of abnormal temperature judgment, but also provides a scientific basis for the subsequent abnormal temperature classification and early warning, and has important practical application value. At the same time, by judging whether the user's body temperature is abnormal again, the preliminary judgment results can be further verified, and the robustness and intelligence level of the judgment can be enhanced.

[0034] In some embodiments of the present application, when obtaining the abnormal temperature level according to the abnormal temperature value of the user and issuing an abnormal temperature level warning, it 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 user's temperature abnormality value is less than or equal to the first abnormality value, the temperature abnormality level is level one, and a level one temperature abnormality warning is issued; If the user's body temperature abnormality value is greater than the first abnormality value and less than or equal to the second abnormality value, the body temperature abnormality level is level 2, and a level 2 abnormal body temperature warning is issued; If the user's temperature abnormality value is greater than the second abnormality value, the temperature abnormality level is level three, and a level three temperature abnormality warning is issued; The abnormal body temperature levels from low to high are level one, level two and level three, and the warning levels from low to high are level one warning, level two warning and level three warning.

[0035] It is understandable that by dividing the first abnormal value and the second abnormal value, the degree of abnormal body temperature is refined into three levels, which can more accurately reflect the severity of abnormal body temperature and provide a clear reference for parents or medical staff. Secondly, triggering corresponding warnings according to different abnormal levels can achieve graded response, avoid overreaction to minor abnormalities, and ensure timely intervention measures for serious abnormalities, thereby improving the pertinence and practicality of the warning. In addition, this graded warning mechanism can effectively reduce the false alarm rate and enhance the reliability of the system and user experience. Through multi-level abnormality levels and warning design, this method not only improves the intelligence level of body temperature monitoring, but also provides scientific and flexible support for infant health management, and has important practical application value.

[0036] On the other hand, see Figure 2 As shown, the present application also provides a system for real-time monitoring and early warning of infant body temperature, which is used to apply the above-mentioned method for real-time monitoring and early warning of infant body temperature, including: 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. If the preliminary judgment result is abnormal, the abnormality degree is calculated based on the user's body temperature and the historical user's body temperature; An adjustment module is configured to determine whether to adjust the abnormality degree according to the ambient temperature. If it is determined that adjustment is required, the abnormality degree is adjusted according to the ambient temperature to obtain a final abnormality degree, and the collection interval is shortened according to the final abnormality degree; a second determination module, configured to obtain the user's body temperature fluctuation data after shortening the collection interval within a preset time period, and to determine again whether the user's body temperature is abnormal according to the user's body temperature fluctuation data; if the result of the second determination 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 the abnormal temperature level according to the abnormal temperature value of the user and to issue an abnormal temperature level early warning.

[0037] It can be understood that, first of all, the acquisition module can collect the user's body temperature and ambient temperature at fixed intervals to ensure the real-time and continuity of the data, 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, thereby improving the efficiency and accuracy of abnormality detection. The adjustment module dynamically adjusts the degree of abnormality according to the ambient temperature, avoiding misjudgment caused by changes in ambient 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 abnormal temperature value in combination with the body temperature difference and fluctuation value, ensuring the scientificity and comprehensiveness of the abnormal judgment. Finally, the early warning module divides the abnormal level according to the abnormal temperature value and triggers the corresponding early warning, realizing a graded response, avoiding overreaction to minor abnormalities, and taking timely intervention measures for serious abnormalities. Through the collaborative work of multiple modules, the system not only improves the accuracy and real-time performance of body temperature monitoring, but also provides intelligent and scientific support for infant health management, which has important practical application value.

[0038] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take 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 codes.

[0039] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0040] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1A function specified in one or more boxes.

[0041] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0042] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection 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: If the preliminary judgment result is that an abnormality occurs, the degree of abnormality is calculated based on the user's body temperature and the historical user's body temperature, including: The abnormality degree is calculated by the following formula: Y = (H-Zmax) / Zmax; In the above formula, Y represents the degree of abnormality, H represents the sum of the safety threshold and the user's historical maximum normal body temperature, and Zmax represents the user's historical maximum normal body temperature.

4. The method for real-time monitoring and early warning of infant body temperature according to claim 3, 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.

5. The method for real-time monitoring and early warning of infant body temperature according to claim 4, 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.

6. The method for real-time monitoring and early warning of infant body temperature according to claim 5, 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.

7. The method for real-time monitoring and early warning of infant body temperature according to claim 6, 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.

8. The method for real-time monitoring and early warning of infant body temperature according to claim 7, 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: ； 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: ； 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, For the The user's body temperature collected this 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 body 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.

9. The method for real-time monitoring and early warning of infant body temperature according to claim 8, 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.

10. 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 9, 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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