Child health monitoring data processing method and system

Abstract

The invention relates to the technical field of health monitoring, in particular to a child health monitoring data processing method and system.The movement behavior of the current heart rate of a child is obtained by analyzing the difference between the current body temperature data and historical body temperature data and the difference between the current heart rate data and historical heart rate data; judging whether the current body temperature data of the child is normal; under the condition that the body temperature data is judged to be normal, analyzing variation amplitude anomaly and anomaly duration of the current body temperature data, analyzing regional influence of environmental factors in combination with the current position data of the multiple children, obtaining environmental anomaly of the current body temperature data, and further obtaining comprehensive anomaly of the current body temperature data of the children; according to the invention, by eliminating the influence of motion behaviors and environmental factors on the monitored body temperature data, the optimized time interval between the transmission time of the current body temperature data of the child and the transmission time of the next body temperature data of the child is determined, so that more optimized transmission of the body temperature data of the child is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of health monitoring, and particularly to a method and system for processing children's health monitoring data. Background Art

[0002] The change of a child's body temperature is usually an important indicator of health status. Therefore, monitoring a child's body temperature is crucial. Through body temperature monitoring, parents or medical staff can timely detect potential health problems of children. Nowadays, with the help of devices such as smart bracelets, the body temperature data of children can be efficiently transmitted to parents or medical staff for real-time monitoring. Such timely feedback can help them quickly assess the health status of children and make timely responses when necessary.

[0003] For the body temperature data of children collected by devices such as smart bracelets, the general way to achieve optimized transmission is as follows: when the body temperature is normal, since the body temperature change is small, the system can extend the data transmission interval, thereby reducing the amount of data transmitted; when the body temperature is abnormal, since the body temperature change is large, the system needs to shorten the transmission interval and transmit data more frequently to ensure timely detection of potential problems. This method effectively reduces the communication burden under normal circumstances and can quickly obtain more data in abnormal situations, so as to respond to potential health risks in a timely manner.

[0004] In the prior art, the obtained abnormal body temperature of children does not necessarily truly represent the abnormal body temperature of children. Suppose a child has a sports behavior. After the child has strenuous activities or plays, the body temperature may rise briefly, showing a false abnormal body temperature. In addition, the change of environmental temperature will also directly affect the body temperature measurement result. If a child is in an overheated environment or exposed to a cold environment, the body temperature monitored by the device may not reflect the true body temperature inside the child, but is affected by environmental factors. Therefore, it is necessary to further optimize the method for optimizing the transmission of children's body temperature. Summary of the Invention

[0005] In order to solve the above technical problems, the purpose of the present invention is to provide a method and system for processing children's health monitoring data.

[0006] According to the first aspect of the embodiments of the present invention, a method for processing children's health monitoring data is provided, and the technical solution adopted is specifically as follows: Obtain the position, body temperature and heart rate data of a child, where the position of the child is the position of the smart bracelet worn by the child in space; Analyze the differences between the current body temperature data and the current heart rate data and the historical body temperature data and the historical heart rate data respectively, obtain the exercise behavior property of the child's current heart rate, and judge whether the current body temperature data of the child is normal; If so, based on the current body temperature data and historical body temperature data, analyze the abnormality of the change range of the current body temperature data and the duration of the abnormality to obtain the single abnormality degree of the current body temperature data of the child; Based on the current location data of multiple children, combined with the single abnormality degree, analyze the regional influence of environmental factors to obtain the environmental abnormality degree of the current body temperature data; According to the exercise behavior and the environmental abnormality degree, obtain the comprehensive abnormality degree of the current body temperature data of the child; According to the comprehensive abnormality degree, combined with the change of the current body temperature data, obtain the optimized time interval between the transmission time of the current body temperature data and the transmission time of the next body temperature data; Obtain the exercise behavior of the current heart rate of the child, including: Calculate the normalized difference in body temperature between the current body temperature data and the historical body temperature data, and calculate the normalized difference in heart rate between the current heart rate data and the historical heart rate data; According to the normalized difference in body temperature and the normalized difference in heart rate, obtain the exercise behavior of the current heart rate of the child.

[0007] In some embodiments of the present invention, the method further includes: analyzing the volatility between two consecutive moments of the historical body temperature data and the historical heart rate data to obtain the true availability of the historical body temperature data and the historical heart rate data pair; Perform weighted correction on the exercise behavior through the true availability to obtain the corrected exercise behavior of the current heart rate of the child.

[0008] In some embodiments of the present invention, determining whether the current body temperature data of the child is normal includes: Set an exercise behavior threshold, and determine whether the corrected exercise behavior is less than or equal to the exercise behavior threshold; If so, the current body temperature data of the child is normal; If not, the current body temperature data of the child is abnormal.

[0009] In some embodiments of the present invention, based on the current body temperature data and the historical body temperature data, analyze the abnormality of the change range of the current body temperature data and the duration of the abnormality to obtain the single abnormality degree of the current body temperature data of the child, including: Calculate the ratio of the difference between the current body temperature data and the body temperature data at the adjacent monitoring time to the average difference between all adjacent historical body temperature data, and combine the corrected exercise behavior to obtain the abnormality of the change range of the current body temperature data of the child; Calculate the difference between the abnormality of the change range of the current body temperature data and the abnormality of the change range of the historical body temperature data, and combine the time weight to obtain the duration of the abnormality of the current body temperature data; Based on the abnormality of the change range and the duration of the abnormality, a single abnormality degree of the current body temperature data of the child is obtained.

[0010] In some embodiments of the present invention, based on the current location data of multiple children, combined with the single abnormality degree, the regional influence of environmental factors is analyzed to obtain the environmental abnormality degree of the current body temperature data, including: Based on the current location data of multiple children, the distance relationship between the current child and other children is analyzed to obtain the regionality between the current child and other children; According to the regionality, combined with the single abnormality degree, the regional influence of environmental factors is analyzed to obtain the environmental abnormality degree of the current body temperature data.

[0011] In some embodiments of the present invention, according to the motor behavior and the environmental abnormality degree, the comprehensive abnormality degree of the current body temperature data of the child is obtained, including: When the current body temperature data of the child is normal, the comprehensive abnormality degree of the current body temperature data of the child is the corrected motor behavior; When the current body temperature data of the child is abnormal, the comprehensive abnormality degree of the current body temperature data of the child is the environmental abnormality degree.

[0012] In some embodiments of the present invention, according to the comprehensive abnormality degree, combined with the change of the current body temperature data and the previous transmission time interval, the optimized time interval between the transmission time of the current body temperature data and the transmission time of the next body temperature data is obtained, including: According to the current body temperature data, the body temperature data transmitted last time, and the body temperature data transmitted the time before last, the change degree of the current body temperature data is obtained; According to the time interval between the transmission time of the previous body temperature data and the transmission time of the body temperature data transmitted the time before last, the previous transmission time interval is obtained; According to the change degree of the current body temperature data and the previous transmission time interval, the general time interval between the transmission time of the current body temperature data and the transmission time of the next body temperature data is obtained; According to the comprehensive abnormality degree, the general time interval is optimized to obtain the optimized time interval between the transmission time of the current body temperature data and the transmission time of the next body temperature data.

[0013] According to the second aspect of the embodiments of the present invention, a child health monitoring data processing system is provided, including: a memory and a processor, wherein: The memory is used to store program codes; The processor is used to read the program codes stored in the memory and execute the method described in the first aspect of the embodiments of the present invention.

[0014] In some embodiments of the present invention, the processor includes: A children's health data collection module for obtaining the location, body temperature, and heart rate data of children; A motion behavior analysis module for analyzing the differences between the current body temperature data and the current heart rate data and the historical body temperature data and the historical heart rate data respectively, obtaining the motion behavior of the current heart rate of the child, and determining whether the current body temperature data of the child is normal; An environmental abnormality analysis module for, if the current body temperature data of the child is normal, analyzing the abnormality of the change amplitude and the duration of the abnormality of the current body temperature data based on the current body temperature data and the historical body temperature data, obtaining the single abnormality of the current body temperature data of the child; and analyzing the regional impact of environmental factors based on the current location data of multiple children and combining the single abnormality to obtain the environmental abnormality of the current body temperature data; A time interval optimization module for obtaining the comprehensive abnormality of the current body temperature data of the child according to the motion behavior and the environmental abnormality; and obtaining the optimized time interval between the transmission time of the current body temperature data and the transmission time of the next body temperature data according to the comprehensive abnormality and combining the change of the current body temperature data.

[0015] Compared with the prior art, a children's health monitoring data processing method and system provided by the present invention have the following beneficial effects: Regarding the body temperature abnormality caused by motion behavior, which is usually accompanied by an obvious change in heart rate, the present invention first analyzes the differences between the current body temperature data and the current heart rate data and the historical body temperature data and the historical heart rate data respectively, obtains the motion behavior of the current heart rate of the child, and determines whether the current body temperature data of the child is normal; when the motion behavior determines that the body temperature data is normal, environmental factors may still cause body temperature abnormality. Then, the present invention analyzes the abnormality of the change amplitude and the duration of the abnormality of the current body temperature data, and combines the current location data of multiple children to analyze the regional impact of environmental factors to obtain the environmental abnormality of the current body temperature data; finally, the comprehensive abnormality of the current body temperature data of the child is obtained, and the transmission time interval is optimized, that is, when the comprehensive abnormality is high, it can be determined that it is not caused by the real change in body temperature. Even if the body temperature changes greatly, the system can still maintain a large transmission time interval, reducing the unnecessary communication burden, thereby achieving the optimal transmission efficiency. The present invention eliminates the influence of motion behavior and environmental factors on the monitored body temperature data, determines the optimized time interval between the transmission time of the current body temperature data of the child and the transmission time of the next body temperature data, thereby realizing the more optimized transmission of the children's body temperature data. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0017] Figure 1 Schematic diagram of the basic process of a method for processing children's health monitoring data provided by an embodiment of the present invention; Figure 2 Schematic diagram of the basic composition of a system for processing children's health monitoring data provided by an embodiment of the present invention. Detailed implementation manners

[0018] To further elaborate on the technical means and effects adopted by the present invention to achieve the intended invention purpose, the following, in combination with the drawings and preferred embodiments, details the specific implementation manners, structures, features, and effects of a method and system for processing children's health monitoring data proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs. Terms such as "including", "comprising", or any other variant thereof are intended to cover non-exclusive inclusion, so that a circuit structure, article, or device including a series of elements not only includes those elements but also includes other elements not explicitly listed, or further includes elements inherent to such article or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of another identical element in the article or device including the element.

[0020] The following specifically describes the specific solution of a method for processing children's health monitoring data provided by the present invention in combination with the drawings.

[0021] Please refer to Figure 1 , which shows the basic process of a method for processing children's health monitoring data provided by an embodiment of the present invention.

[0022] As Figure 1 shown, a method for processing children's health monitoring data provided by an embodiment of the present invention specifically includes: S100: Obtain the location, body temperature, and heart rate data of the child.

[0023] The smart bracelet is a small electronic device worn on a child's wrist, usually equipped with multiple sensors. Among them, the position sensor (GPS) is used to obtain the position of the child (wearer) in real time, that is, the position of the smart bracelet in space is regarded as the position of the child. The heart rate sensor (photoplethysmography) is used to monitor the heart rate of the child (wearer) in real time, and the body temperature sensor (thermocouple) is used to measure the skin surface temperature of the child (wearer) in real time.

[0024] The smart bracelet collects the position, body temperature, and heart rate data of the child (wearer) in real time at a frequency of once per minute, and then stores the position, body temperature, and heart rate data through the memory of the smart bracelet. It can save the position, body temperature, and heart rate data at multiple moments in the historical record. Therefore, the position, body temperature, and heart rate data of the child are obtained in real time from the memory of the smart bracelet. The obtained position, body temperature, and heart rate data include the current position data, current body temperature data, current heart rate data, and historical position data, historical body temperature data, and historical heart rate data at multiple moments. Among them, can take all the historical records stored in the smart bracelet. When the number of historical record data stored in the smart bracelet is large, a certain number of historical records can also be taken, such as etc.

[0025] S200: Analyze the differences between the current body temperature data and current heart rate data and the historical body temperature data and historical heart rate data respectively to obtain the exercise behavior of the child's current heart rate, and judge whether the current body temperature data of the child is normal.

[0026] Exercise increases the metabolic activity of muscles, resulting in energy consumption and heat production. At the same time, the metabolic products (such as carbon dioxide and lactic acid) produced need to be quickly transported to the lungs and kidneys through the blood for excretion. Due to the increased demand for oxygen and nutrients by muscles, the heart beats faster to enhance blood circulation, ensuring the timely supply of oxygen and nutrients to muscles and effectively discharging metabolic wastes out of the body. At the same time, exercise causes the body temperature to rise, and the body accelerates heat dissipation by increasing blood flow to help maintain body temperature stability. The increased heart rate helps to bring heat to the skin surface and reduce body temperature through the heat dissipation mechanism.

[0027] In contrast, the increase in body temperature caused by other factors (such as environmental temperature changes or diseases) usually does not generate such urgent demands for oxygen and nutrient supply and waste excretion at the same time, so the heart rate changes less. Therefore, the increase in body temperature caused by exercise is usually accompanied by a significant increase in heart rate.

[0028] Based on the above analysis, in the embodiments of the present invention, by analyzing the differences between the current body temperature data and the current heart rate data and the historical body temperature data and the historical heart rate data respectively, the exercise behavior of the child's current heart rate is obtained, and then it is determined whether the child's current body temperature data is normal.

[0029] Among them, analyzing the differences between the current body temperature data and the current heart rate data and the historical body temperature data and the historical heart rate data respectively, and obtaining the exercise behavior of the child's current heart rate. The specific implementation method is: calculating the normalized difference in body temperature between the current body temperature data and the historical body temperature data, and calculating the normalized difference in heart rate between the current heart rate data and the historical heart rate data; obtaining the exercise behavior of the child's current heart rate according to the normalized difference in body temperature and the normalized difference in heart rate. Further, a heart rate exercise behavior is constructed by comparing the child's current heart rate data with the historical heart rate data: In the formula, represents the heart rate exercise behavior of the child's heart rate data at the current moment compared with the heart rate data at the th historical moment; represents the maximum-minimum normalization function (the monitoring data at the current moment is compared with the monitoring data at other historical moments); represents the child's current heart rate data; represents the th historical moment's heart rate data of the child; represents the child's current body temperature data; represents the th historical moment's body temperature data of the child.

[0030] The formula logic is that if the child is in a moving state at the current moment, the child's current heart rate data increases relative to the historical heart rate data. At this time, is larger, and at the same time, the child's current body temperature data also increases relative to the historical body temperature data. However, since the body temperature changes relatively slowly compared to the heart rate changes, usually 's increase amplitude will be less than 's increase amplitude, that is, at this time the value is larger; if the child's current body temperature data increases due to the external environment or disease, then is larger, and at this time the child's current heart rate data remains unchanged or changes little, that is, the value is smaller. Therefore, 's increase amplitude will be greater than 's increase amplitude, that is, at this time the value is smaller.

[0031] Similarly, the heart rate exercise behavior of the child's current heart rate data compared with the heart rate data monitored each time stored in history can be determined.

[0032] The heart rate movement behavior of the child's current heart rate data compared with the heart rate data stored historically at each monitoring has been determined. Next, all the data at the historically stored moments will be used to evaluate the heart rate movement behavior of the child's current heart rate. That is, based on the heart rate movement behavior of the current heart rate data compared with the heart rate data stored historically at each monitoring, the heart rate movement behavior of the child's current heart rate is obtained, that is: In the formula, represents the heart rate movement behavior of the child's current heart rate; represents the heart rate movement behavior of the heart rate data at the child's current moment compared with the heart rate data at the th historical moment; represents the total number of historical moments obtained; represents the linear normalization function.

[0033] For the stored historical body temperature data and historical heart rate data pairs, not every body temperature-heart rate data pair monitored at each historical moment is truly available; if the smart bracelet is worn improperly or too loosely, the sensor cannot fit tightly against the skin, which will cause inaccurate body temperature and heart rate data; if there is strenuous exercise or vibration, it may also cause the smart bracelet to shift, which will also affect the stability of the sensor, and thus lead to inaccurate body temperature and heart rate data; in addition, clothing occlusion will also affect the contact between the sensor and the skin, reducing the accuracy of body temperature and heart rate data.

[0034] Then, it is judged whether the child's current body temperature data is normal, including: setting a movement behavior threshold, the threshold value can be 0.7, and judging whether the corrected movement behavior is less than or equal to the movement behavior threshold; if so, that is , then the child's current body temperature data is normal. It should be noted that the normal here means that the monitored body temperature is not interfered by exercise, and the increase in body temperature at this time is very likely to be caused by pathological reasons; if not, that is , then the child's current body temperature data is abnormal, that is, it is judged that the child has a current movement behavior. At this time, the increase in the child's body temperature is not due to the increase in body temperature that needs to be monitored for pathological reasons. At this time, the comprehensive abnormality degree of the child's current body temperature data is .

[0035] The human body has a strong ability to self-regulate (such as regulating body temperature and heart rate). When the heart rate or body temperature changes, the body will adjust through the autonomic nervous system to maintain a stable physiological state. Changes in heart rate and body temperature in a short period of time are usually gradual. Even if changes are caused by exercise or emotional fluctuations, the fluctuations in heart rate and body temperature usually occur gradually rather than suddenly. Therefore, under normal circumstances, the changes between two consecutive moments will not be very drastic; changes in body temperature and heart rate data caused by improper wearing are usually sudden and volatile.

[0036] Therefore, in some embodiments of the present invention, by analyzing the volatility of historical body temperature data and historical heart rate data between two consecutive moments, the real availability of the historical body temperature data and historical heart rate data pair is obtained. The specific implementation method is: analyzing the difference between the historical body temperature data and the historical body temperature data corresponding to its adjacent moments, and analyzing the difference between the historical heart rate data and the historical heart rate data corresponding to its adjacent moments, to obtain the volatility of the historical body temperature data and the historical heart rate data between two consecutive moments, and then to obtain the real availability of the historical body temperature data and historical heart rate data pair. Construct the first The actual availability calculation formula of the historical temperature data and historical heart rate data at a historical moment is: In the formula, Indicates The real availability of historical temperature data and historical heart rate data at each historical moment; Indicates Historical heart rate data at historical moments; Indicates Historical heart rate data at historical moments; Indicates Historical temperature data at historical moments; Indicates Historical temperature data at historical moments; Indicated by natural constant An exponential function with base .

[0037] Similarly, the true availability of body temperature and heart rate data pairs corresponding to all historical moments can be determined.

[0038] The real available historical moments have a better comparison effect on the motor behavior of the current heart rate data, while the unreal available historical moments have a weaker comparison effect. Therefore, in some embodiments of the present invention, the motor behavior is weighted and corrected by the real availability to obtain the corrected motor behavior of the child's current heart rate. The calculation formula for constructing the corrected motor behavior of the child's current heart rate is: In the formula, Represents the corrected exercise behavior of the child's current heart rate; Represents the total number of historical moments obtained; Represents the true usability of the historical body temperature data and historical heart rate data pair of the th historical moment; Represents the heart rate exercise behavior of the child's current heart rate data compared with the heart rate data of the th historical moment;

[0039] Represents the th historical moment; the ratio of the true usability of the historical body temperature data and historical heart rate data pair to the true usability corresponding to all historical moments, that is, the relative size of the true usability corresponding to the th historical moment. Historical moments with greater true usability have a better control effect on the exercise behavior of the current heart rate. Therefore, by weighting , the corrected exercise behavior of the child's current heart rate is obtained.

[0040] Then, it is judged whether the child's current body temperature data is normal, including: setting an exercise behavior threshold, the threshold value can be 0.7, and judging whether the corrected exercise behavior is less than or equal to the exercise behavior threshold; if so, that is , then the child's current body temperature data is normal. It should be noted that "normal" here means that the monitored body temperature is not interfered by exercise, not that the body temperature is within the normal range; if not, that is , then the child's current body temperature data is abnormal, that is, it is judged that the child has current exercise behavior. At this time, the increase in the child's body temperature is not due to the increase in body temperature that needs to be monitored for pathological reasons. At this time, the comprehensive abnormality of the child's current body temperature data is .

[0041] S300: If so, based on the current body temperature data and historical body temperature data, analyze the abnormality of the change amplitude and the duration of the abnormality of the current body temperature data to obtain the single abnormality of the child's current body temperature data.

[0042] When the exercise behavior of the child's current heart rate or the corrected exercise behavior is greater than the exercise behavior threshold, the comprehensive abnormality of the current body temperature data has been obtained as or . However, when the exercise behavior of the child's current heart rate or the corrected exercise behavior is low, that is or In this case, it does not mean that the currently measured body temperature is the normal body temperature that needs to be monitored. At this time, environmental factors can also cause abnormal changes in the measured body surface temperature without affecting heart rate movement behavior. Therefore, on the premise that it is initially judged that the currently measured body temperature of the child is normal ( ), it is necessary to further combine environmental factors to judge the abnormality of the child's current body temperature.

[0043] On the premise that it is initially judged that the current body temperature data of the child is normal, that is, the current heart rate movement behavior of the child is small, or on the premise that it is large. Since the temperature sensor of the smart bracelet is usually located on the wrist, the temperature of this part is particularly sensitive to changes in the external temperature. When the environment changes violently, these sensors can quickly sense this change, resulting in relatively rapid fluctuations in the body temperature measurement data. Therefore, if the degree of change in the currently measured body temperature data of the child compared to the body temperature data measured at the previous moment is larger than the average change in the body temperature measured at all adjacent historical moments, it proves that environmental factors may have affected the currently monitored body temperature data.

[0044] For the body temperature change of children caused by environmental factors, it is not only accompanied by abnormalities in the body temperature amplitude, but may also be manifested as rapid fluctuations in the body temperature. For example, when a child suddenly enters a high-temperature or low-temperature environment, the body surface temperature will change rapidly. However, as the environmental conditions return to normal or the body's regulatory mechanism is activated, the body temperature will quickly return to the normal range. Therefore, the body temperature change caused by the environment usually lasts for a short time. In contrast, pathological factors (such as viral infections, inflammations, endocrine disorders, etc.) are usually long-term and persistent. They will affect the body's immune system and metabolic processes, resulting in long-term abnormal changes in body temperature.

[0045] Based on this, if the change amplitude of the child's current body temperature data is abnormal, and the abnormality is significantly different from the body temperature changes at more distant historical moments, that is, the duration of the abnormality is relatively long, then it is more likely to be caused by environmental factors. Therefore, in the embodiments of the present invention, if the child's current body temperature data is normal, based on the current body temperature data and historical body temperature data, analyze the abnormality of the change amplitude of the current body temperature data and the duration of the abnormality to obtain the single abnormality degree of the child's current body temperature data. Further, it includes: First, by calculating the ratio of the difference between the current body temperature data and the body temperature data at the adjacent monitoring time to the average difference between all adjacent historical body temperature data, combined with the corrected movement behavior, the abnormality of the change amplitude of the child's current body temperature data is obtained. The formula for constructing the abnormality of the change amplitude of the child's current body temperature data is: In the formula, represents the abnormality of the change amplitude of the child's current body temperature data; Represents the current body temperature data of the child; Represents the body temperature data at the previous moment of the current moment of the child; Represents the th historical moment of the child's body temperature data; Represents the th historical moment of the child's body temperature data; Represents the total number of historical moments obtained; Represents the corrected exercise behavior of the child's current heart rate; Represents the exponential function with the natural constant as the base; Represents the linear normalization function.

[0046] It should be noted that the change amplitude abnormality of the child's current body temperature data can also be obtained by combining the exercise behavior, that is, replacing in the above formula with .

[0047] Represents the difference between the body temperature data measured at the current moment of the child and the previous historical moment, Represents the average difference between all adjacent historical body temperature data, and the change amplitude of the child's current body temperature data is obtained through the ratio of the two , A larger value indicates that the child's current body temperature data has suddenly increased, indicating a larger change amplitude abnormality of the child's current body temperature data.

[0048] Then, calculate the difference between the change amplitude abnormality of the current body temperature data and the change amplitude abnormality of the historical body temperature data, and combine the time weight to obtain the duration of the abnormality of the current body temperature data.

[0049] Finally, according to the change amplitude abnormality and the duration of the abnormality, obtain the single abnormality degree of the child's current body temperature data. The formula for constructing the single abnormality degree of the child's current body temperature data is: In the formula, Represents the single abnormality degree of the child's current body temperature data; Represents the total number of historical moments obtained; Represents the change amplitude abnormality of the child's current body temperature data; Represents the th historical moment of the change amplitude abnormality of the child's body temperature data; Represents the th historical moment. The historical moment with a closer distance to the current moment has a smaller serial number, that is, the moment before the current moment is the 1st historical moment; Represents the linear normalization function.

[0050] Indicates the difference between the abnormality of the change range of the current body temperature data of a child and the abnormality of the change range of the body temperature data of the child at a historical moment. The larger this value, the greater the abnormality of the change range of the current body temperature data, and the larger the value, the greater the difference between the abnormality of the change range of the current body temperature data and the abnormality of the change range of the body temperature data at a more distant historical moment; Indicates the time weight. The larger this value, the more distant the historical moment, and the greater the time weight, that is, a larger weight is assigned to the corresponding historical moment that is far away in time.

[0051] S400: Based on the current location data of multiple children, combined with a single abnormality degree, analyze the regional impact of environmental factors to obtain the environmental abnormality degree of the current body temperature data.

[0052] Since environmental factors usually show consistency within a specific region, when the temperature in a region fluctuates violently, this change will synchronously affect all individuals within the region. In other words, body temperature abnormalities caused by the environment usually exist widely within the same region. Therefore, within the range that the current Bluetooth of the child can monitor, the abnormality of the body temperature at all smart bracelet monitoring points will be relatively high.

[0053] Further assume that within the monitoring range of the current children's smart bracelet, there are smart bracelets. And the closer these bracelets are to the current bracelet, the more they can reflect the common characteristics of the regional environment. At this time, the higher the single abnormality degree of the body temperature measured by these bracelets, the higher the abnormality of the current body temperature data measured by the child.

[0054] Based on the above analysis, in the embodiment of the present invention, based on the current location data of multiple children, combined with a single abnormality degree, analyze the regional impact of environmental factors to obtain the environmental abnormality degree of the current body temperature data. The specific implementation method is: based on the current location data of multiple children, analyze the distance relationship between the current child and other children to obtain the regionality between the current child and other children; according to the regionality, combined with a single abnormality degree, analyze the regional impact of environmental factors to obtain the environmental abnormality degree of the current body temperature data. The formula for constructing the environmental abnormality degree of the current body temperature data of the current child is: In the formula, represents the environmental abnormality degree of the current body temperature data of the current child; represents that there are a total of smart bracelets within the current Bluetooth range of the child; represents the Euclidean distance between the current child and other children ; Indicates other children The single abnormality degree of the current body temperature data; Indicates the exponential function with the natural base as the base.

[0055] Other children The single abnormality degree of the current body temperature data of The larger it is, the higher the environmental abnormality degree of the current body temperature data of the current child; Indicates the distance relationship between the current child and other children. The larger this value is, the closer the other children are to the current child. Through weighting, that is, when the distance between other children and the current child is closer, the single abnormality degree of the current body temperature data of other children can better reflect the environmental abnormality degree of the current body temperature data of the current child.

[0056] S500: Obtain the comprehensive abnormality degree of the current body temperature data of the child according to the exercise behavior and environmental abnormality degree.

[0057] Obtain the comprehensive abnormality degree of the current body temperature data of the child according to the exercise behavior and environmental abnormality degree. That is, when the current body temperature data of the child is normal, the comprehensive abnormality degree of the current body temperature data of the child is the corrected exercise behavior (or exercise behavior); when the current body temperature data of the child is abnormal, the comprehensive abnormality degree of the current body temperature data of the child is the environmental abnormality degree. That is: In the formula, represents the comprehensive abnormality degree of the current body temperature data of the child; represents the corrected exercise behavior of the current heart rate of the child; represents the exercise behavior of the current heart rate of the child; represents the environmental abnormality degree of the current body temperature data of the current child.

[0058] S600: According to the comprehensive abnormality degree, combined with the change of the current body temperature data, obtain the optimized time interval between the transmission time of the current body temperature data and the transmission time of the next body temperature data.

[0059] ​Generally speaking, when there are significant changes in a child's body temperature, the time interval for transmitting body temperature data should be reduced so that more data can be obtained more quickly in case of abnormal body temperature, thus enabling a timely response to potential health risks. Specifically, if the change in the current body temperature relative to the body temperature at the previous transmission moment is greater than the change in the body temperature at the previous transmission moment relative to the body temperature at the moment before the previous transmission moment, then the time interval should be reduced; conversely, if the change in the current body temperature relative to the body temperature at the previous transmission moment is less than the change in the body temperature at the previous transmission moment relative to the body temperature at the moment before the previous transmission moment, then the time interval should be increased.

[0060] However, if the change in the current body temperature is caused by exercise behavior or environmental factors, that is relatively high, then even if the body temperature changes, the system does not need to reduce the transmission time interval, and the time interval can still remain large to avoid unnecessary frequent data transmission.

[0061] Based on the above analysis, in an embodiment of the present invention, an optimized time interval between the transmission time of the current body temperature data and the transmission time of the next body temperature data is obtained according to the comprehensive abnormality degree in combination with the change in the current body temperature data. The specific implementation method is as follows: according to the current body temperature data, the body temperature data transmitted last time, and the body temperature data transmitted the time before the last time, the degree of change in the current body temperature data is obtained; according to the time interval between the transmission time of the last body temperature data and the transmission time of the body temperature data before the last time, the last transmission time interval is obtained; according to the degree of change in the current body temperature data and the last transmission time interval, a general time interval between the transmission time of the current body temperature data and the transmission time of the next body temperature data is obtained; according to the comprehensive abnormality degree, the general time interval is optimized to obtain an optimized time interval between the transmission time of the current body temperature data and the transmission time of the next body temperature data. The calculation formula for constructing the optimized time interval between the transmission time of the current body temperature data and the transmission time of the next body temperature data is: In the formula, represents the optimized time interval between the transmission time of the current body temperature data of the child and the transmission time of the next body temperature data; represents the comprehensive abnormality degree of the current body temperature data of the child; represents the body temperature data transmitted last time, represents the body temperature data transmitted the time before the last time; represents the current body temperature data; represents the time interval between the transmission time of the last body temperature data and the transmission time of the body temperature data before the last time, that is, the last transmission time interval.

[0062] Indicates the general time interval between the transmission time of the current body temperature data obtained by a child under normal circumstances and the transmission time of the next body temperature data. By optimizing the general transmission time interval, The larger the value, the greater the influence of the currently monitored body temperature data by factors such as exercise behavior or the external environment. At this time, the change in body temperature is less likely to be used as a basis for adjusting the transmission time interval, and it is more necessary to optimize the general time interval.

[0063] After determining the optimized time interval between the transmission time of the current child's body temperature data and the transmission time of the next body temperature data, at the next moment after the end of the current time interval, the system will transmit the real-time monitored child's body temperature data through the Internet of Things, and update this moment as the new current moment. This process will continue to cycle. In this way, the system can, after excluding the influence of exercise behavior and environmental factors, only increase the transmission frequency when the body temperature changes significantly, thereby reducing unnecessary communication burdens and achieving optimal transmission efficiency.

[0064] Based on the same inventive concept as the above method, this embodiment also provides a child health monitoring data processing system.

[0065] Please refer to Figure 2 , which shows the basic composition of a child health monitoring data processing system provided by an embodiment of the present invention.

[0066] As Figure 2 shown, a child health monitoring data processing system includes: a memory 10 and a processor 20, where: The memory 10 is used to store program codes; The processor 20 is used to read the program codes stored in the memory 10 and execute obtaining the location, body temperature, and heart rate data of a child; analyzing the differences between the current body temperature data and the current heart rate data and the historical body temperature data and historical heart rate data respectively to obtain the exercise behavior of the child's current heart rate, and judging whether the current body temperature data of the child is normal; if so, based on the current body temperature data and the historical body temperature data, analyzing the abnormality degree of the change range of the current body temperature data and the duration of the abnormality to obtain the single abnormality degree of the current body temperature data of the child; based on the current location data of multiple children, combining the single abnormality degree, analyzing the regional influence of environmental factors to obtain the environmental abnormality degree of the current body temperature data; obtaining the comprehensive abnormality degree of the current body temperature data of the child according to the exercise behavior and the environmental abnormality degree; and obtaining the optimized time interval between the transmission time of the current body temperature data and the transmission time of the next body temperature data according to the comprehensive abnormality degree and combining the change of the current body temperature data.

[0067] Further, the processor 20 includes: a child health data acquisition module 21, a motion behavior analysis module 22, an environmental abnormality analysis module 23, and a time interval optimization module 24. Among them: The child health data acquisition module 21 is configured to obtain the location, body temperature, and heart rate data of the child; The motion behavior analysis module 22 is configured to analyze the differences between the current body temperature data and the current heart rate data and the historical body temperature data and the historical heart rate data respectively, obtain the motion behavior of the child's current heart rate, and determine whether the current body temperature data of the child is normal; The environmental abnormality analysis module 23 is configured to, if the current body temperature data of the child is normal, analyze the abnormality of the change amplitude and the duration of the abnormality of the current body temperature data based on the current body temperature data and the historical body temperature data, and obtain the single abnormality of the current body temperature data of the child; and based on the current location data of multiple children, combined with the single abnormality, analyze the regional influence of environmental factors to obtain the environmental abnormality of the current body temperature data; The time interval optimization module 24 is configured to obtain the comprehensive abnormality of the current body temperature data of the child according to the motion behavior and the environmental abnormality; and according to the comprehensive abnormality, combined with the change of the current body temperature data, obtain the optimized time interval between the transmission time of the current body temperature data and the transmission time of the next body temperature data.

[0068] It should be noted that: the above-mentioned sequence of the embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0069] Each embodiment in this specification is described in a progressive manner. The same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. A method for processing children's health monitoring data, characterized in that, The method includes: Obtaining the location, body temperature, and heart rate data of a child, where the location of the child is the location of the smart bracelet worn by the child in space; Analyzing the differences between the current body temperature data and the current heart rate data and the historical body temperature data and the historical heart rate data respectively to obtain the exercise behavior of the child's current heart rate, and determining whether the child's current body temperature data is normal; If so, based on the current body temperature data and the historical body temperature data, analyze the abnormality of the change range and the duration of the abnormality of the current body temperature data to obtain the single abnormality degree of the child's current body temperature data; Based on the current location data of multiple children, combined with the single abnormality degree, analyze the regional influence of environmental factors to obtain the environmental abnormality degree of the current body temperature data; According to the exercise behavior and the environmental abnormality degree, obtain the comprehensive abnormality degree of the child's current body temperature data; According to the comprehensive abnormality degree, combined with the change of the current body temperature data, obtain the optimized time interval between the transmission time of the current body temperature data and the transmission time of the next body temperature data; Obtaining the exercise behavior of the child's current heart rate includes: Calculating the normalized temperature difference between the current body temperature data and the historical body temperature data, and calculating the normalized heart rate difference between the current heart rate data and the historical heart rate data; According to the normalized temperature difference and the normalized heart rate difference, obtain the exercise behavior of the child's current heart rate.

2. The method for processing children's health monitoring data according to claim 1, characterized in that, The method further includes: analyzing the volatility between the historical body temperature data and the historical heart rate data between two consecutive moments to obtain the true availability of the pair of historical body temperature data and historical heart rate data; Performing weighted correction on the exercise behavior through the true availability to obtain the corrected exercise behavior of the child's current heart rate.

3. The method for processing children's health monitoring data according to claim 2, characterized in that, Determining whether the child's current body temperature data is normal includes: Setting an exercise behavior threshold, and determining whether the corrected exercise behavior is less than or equal to the exercise behavior threshold; If so, the child's current body temperature data is normal; If not, the child's current body temperature data is abnormal.

4. The method for processing children's health monitoring data according to claim 2, characterized in that, Based on the current body temperature data and the historical body temperature data, analyzing the abnormality of the change range and the duration of the abnormality of the current body temperature data to obtain the single abnormality degree of the child's current body temperature data, including: Calculating the ratio of the difference between the current body temperature data and the body temperature data at the adjacent monitoring time to the average difference between all adjacent historical body temperature data, and combining the corrected exercise behavior to obtain the abnormality of the change range of the child's current body temperature data; Calculating the difference between the abnormality of the change range of the current body temperature data and the abnormality of the change range of the historical body temperature data, and combining the time weight to obtain the duration of the abnormality of the current body temperature data; According to the abnormality of the change range and the duration of the abnormality, obtain the single abnormality degree of the child's current body temperature data.

5. The method for processing children's health monitoring data according to claim 1, characterized in that, Based on the current location data of multiple children, combined with the single abnormality degree, analyzing the regional influence of environmental factors to obtain the environmental abnormality degree of the current body temperature data, including: Based on the current location data of multiple children, analyzing the distance relationship between the current child and other children to obtain the regionality between the current child and other children; Based on the regionality and in combination with the single abnormality degree, analyze the regional influence of environmental factors to obtain the environmental abnormality degree of the current body temperature data.

6. The method for processing children's health monitoring data according to claim 3, characterized in that, Based on the motor behavior and the environmental abnormality degree, obtain the comprehensive abnormality degree of the current body temperature data of the child, including: When the current body temperature data of the child is normal, the comprehensive abnormality degree of the current body temperature data of the child is the corrected motor behavior. When the current body temperature data of the child is abnormal, the comprehensive abnormality degree of the current body temperature data of the child is the environmental abnormality degree.

7. The method for processing children's health monitoring data according to claim 1, characterized in that, Based on the comprehensive abnormality degree, in combination with the change of the current body temperature data and the previous transmission time interval, obtain the optimized time interval between the transmission time of the current body temperature data and the transmission time of the next body temperature data, including: Based on the current body temperature data, the previously transmitted body temperature data, and the body temperature data transmitted the time before that, obtain the degree of change of the current body temperature data. Based on the time interval between the transmission time of the previous body temperature data and the transmission time of the body temperature data transmitted the time before that, obtain the previous transmission time interval. Based on the degree of change of the current body temperature data and the previous transmission time interval, obtain the general time interval between the transmission time of the current body temperature data and the transmission time of the next body temperature data. Based on the comprehensive abnormality degree, optimize the general time interval to obtain the optimized time interval between the transmission time of the current body temperature data and the transmission time of the next body temperature data.

8. A children's health monitoring data processing system, characterized in that, The system includes: a memory and a processor, wherein: The memory is used for storing program codes. The processor is used for reading the program codes stored in the memory and executing the method according to any one of claims 1 to 7.

9. The children's health monitoring data processing system according to claim 8, characterized in that, The processor includes: A child health data acquisition module, which is used for acquiring the location, body temperature, and heart rate data of the child. A motor behavior analysis module, which is used for analyzing the differences between the current body temperature data and the current heart rate data and the historical body temperature data and the historical heart rate data respectively to obtain the motor behavior of the current heart rate of the child, and judging whether the current body temperature data of the child is normal. An environmental abnormality degree analysis module, which is used for, if the current body temperature data of the child is normal, based on the current body temperature data and the historical body temperature data, analyzing the abnormality of the change amplitude of the current body temperature data and the duration of the abnormality to obtain the single abnormality degree of the current body temperature data of the child; and based on the current location data of multiple children, in combination with the single abnormality degree, analyzing the regional influence of environmental factors to obtain the environmental abnormality degree of the current body temperature data. A time interval optimization module, which is used for obtaining the comprehensive abnormality degree of the current body temperature data of the child based on the motor behavior and the environmental abnormality degree; and obtaining the optimized time interval between the transmission time of the current body temperature data and the transmission time of the next body temperature data based on the comprehensive abnormality degree and in combination with the change of the current body temperature data.

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