A method and system for processing children's health monitoring data

Abstract

The present invention relates to the field of health monitoring technology, and particularly to a method and system for processing child health monitoring data. The present invention obtains the movement behavior of the child's current heart rate by analyzing the differences between current body temperature data and current heart rate data and historical body temperature data and historical heart rate data, and judges whether the child's current body temperature data is normal; when the body temperature data is judged to be normal, the abnormality of the change amplitude and the duration of the abnormality of the current body temperature data are analyzed, and the regional influence of environmental factors is analyzed in combination with the current location data of multiple children to obtain the environmental abnormality degree of the current body temperature data, and then obtain the comprehensive abnormality degree of the child's current body temperature data; the present invention eliminates the influence of movement behavior and environmental factors on the monitored body temperature data, determines the optimal time interval between the transmission time of the child's current body temperature data and the transmission time of the next body temperature data, thereby achieving more optimized transmission of the child's body temperature data.

Description

Technical Field

[0001] The present invention relates to the technical field of health monitoring, and in particular to a method and system for processing child health monitoring data. Background Art

[0002] Changes in a child's body temperature are often a key indicator of their health, making temperature monitoring crucial. This allows parents and healthcare professionals to identify potential health issues in children. Nowadays, with the help of devices like smart bracelets, children's temperature data can be efficiently transmitted to parents and healthcare professionals, enabling real-time monitoring. This immediate feedback helps them quickly assess a child's health and respond promptly when needed.

[0003] For children's temperature data collected by devices like smart bracelets, the typical approach to optimizing transmission is: when the temperature is normal, the system can extend the data transmission interval to reduce the amount of data transmitted due to minimal temperature fluctuations. When the temperature is abnormal, the system needs to shorten the transmission interval and transmit data more frequently due to significant temperature fluctuations to ensure timely detection of potential issues. This approach effectively reduces the communication burden under normal circumstances while enabling faster acquisition of more data in abnormal situations, enabling timely responses to potential health risks.

[0004] In existing technologies, abnormal child temperatures obtained do not necessarily represent a true abnormality in the child's body temperature. For example, if a child engages in physical activity, their body temperature may briefly rise after strenuous activity or play, resulting in a falsely abnormal temperature. Furthermore, changes in ambient temperature can directly affect temperature measurements. If a child is in an overheated environment or exposed to cold, the temperature monitored by the device may not reflect the child's true body temperature, but rather be affected by environmental factors. Therefore, further optimization of the method for optimizing the transmission of child body temperatures is needed. 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 child health monitoring data.

[0006] According to a first aspect of an embodiment of the present invention, a method for processing child health monitoring data is provided, and the technical solution adopted is as follows:

[0007] Obtain the child's location, body temperature, and heart rate data, where the child's location refers to the location of the smart bracelet worn by the child in space;

[0008] 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, obtain the exercise behavior of the child's current heart rate, and determine whether the child's current body temperature data is normal;

[0009] If yes, based on the current body temperature data and the 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 a single abnormality degree of the child's current body temperature data;

[0010] Based on the current location data of multiple children, combined with the single abnormality degree, the regional impact of environmental factors is analyzed to obtain the environmental abnormality degree of the current body temperature data;

[0011] Obtaining a comprehensive abnormality degree of the child's current body temperature data based on the movement behavior and the environmental abnormality degree;

[0012] According to the comprehensive abnormality degree and in combination with the current temperature data change, an optimized time interval between the transmission time of the current temperature data and the transmission time of the next temperature data is obtained;

[0013] Get the child's current heart rate and exercise behavior, including:

[0014] Calculate the normalized difference between the current body temperature data and the historical body temperature data, and calculate the normalized difference between the current heart rate data and the historical heart rate data;

[0015] The exercise behavior of the child's current heart rate is obtained according to the normalized body temperature difference and the normalized heart rate difference.

[0016] In some embodiments of the present invention, the method further comprises: analyzing the volatility of the historical body temperature data and the historical heart rate data between two consecutive moments to obtain the true availability of the historical body temperature data and the historical heart rate data pair;

[0017] The movement behavior is weightedly modified according to the real availability to obtain the modified movement behavior of the child's current heart rate.

[0018] In some embodiments of the present invention, determining whether the child's current body temperature data is normal includes:

[0019] Setting a motion behavior threshold, and determining whether the modified motion behavior is less than or equal to the motion behavior threshold;

[0020] If yes, the child’s current body temperature data is normal;

[0021] If not, the child's current body temperature data is abnormal.

[0022] In some embodiments of the present invention, based on the current body temperature data and the historical body temperature data, the abnormality of the change amplitude of the current body temperature data and the duration of the abnormality are analyzed to obtain a single abnormality degree of the child's current body temperature data, including:

[0023] Calculate the ratio of the difference between the current body temperature data and the body temperature data of the adjacent monitoring time to the average difference between all adjacent historical body temperature data, and combine the corrected movement behavior to obtain the abnormality of the change amplitude of the child's current body temperature data;

[0024] Calculate the difference between the abnormality of the change amplitude of the current body temperature data and the abnormality of the change amplitude of the historical body temperature data, and combine it with the time weight to obtain the abnormal duration of the current body temperature data;

[0025] A single abnormality degree of the child's current body temperature data is obtained according to the abnormality of the change amplitude and the duration of the abnormality.

[0026] In some embodiments of the present invention, based on the current location data of multiple children, combined with the single abnormality degree, the regional impact of environmental factors is analyzed to obtain the environmental abnormality degree of the current body temperature data, including:

[0027] 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;

[0028] According to the regionality and in combination with the single abnormality, the regional influence of environmental factors is analyzed to obtain the environmental abnormality of the current body temperature data.

[0029] In some embodiments of the present invention, obtaining the comprehensive abnormality of the child's current body temperature data based on the movement behavior and the environmental abnormality includes:

[0030] When the child's current body temperature data is normal, the comprehensive abnormality of the child's current body temperature data is the corrected movement behavior;

[0031] When the child's current body temperature data is abnormal, the comprehensive abnormality degree of the child's current body temperature data is the environmental abnormality degree.

[0032] In some embodiments of the present invention, obtaining an 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, combined with the change of the current body temperature data and the last transmission time interval, includes:

[0033] According to the current body temperature data, the body temperature data transmitted last time and the body temperature data transmitted last time, the degree of change of the current body temperature data is obtained;

[0034] Obtain the last transmission time interval according to the time interval between the last transmission time of the body temperature data and the transmission time of the previous body temperature data;

[0035] Obtaining a general 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 degree of change of the current body temperature data and the time interval of the last transmission;

[0036] 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.

[0037] According to a second aspect of an embodiment of the present invention, a child health monitoring data processing system is provided, comprising: a memory and a processor, wherein:

[0038] The memory is used to store program code;

[0039] The processor is configured to read the program code stored in the memory and execute the method described in the first aspect of the embodiment of the present invention.

[0040] In some embodiments of the present invention, the processor includes:

[0041] Children's health data collection module, used to obtain children's location, body temperature and heart rate data;

[0042] The exercise behavior analysis module is used 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, obtain the exercise behavior of the child's current heart rate, and determine whether the child's current body temperature data is normal;

[0043] An environmental abnormality analysis module is configured to, if the child's current body temperature data is normal, analyze the abnormality of the change amplitude and duration of the current body temperature data based on the current body temperature data and historical body temperature data to obtain a single abnormality degree of the child's current body temperature data; and analyze the regional impact of environmental factors based on the current location data of multiple children and the single abnormality degree to obtain an environmental abnormality degree of the current body temperature data;

[0044] The time interval optimization module is used to obtain the comprehensive abnormality of the child's current body temperature data based on the movement behavior and the environmental abnormality; and according to the comprehensive abnormality, combined with the current body temperature data change, 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.

[0045] Compared with the existing technology, the child health monitoring data processing method and system provided by the present invention has the following beneficial effects:

[0046] For abnormal body temperature caused by exercise behavior, which is usually accompanied by a more obvious trend of heart rate changes, the present invention first analyzes the difference between the current body temperature data and the current heart rate data and the historical body temperature data and the historical heart rate data, obtains the exercise behavior of the child's current heart rate, and determines whether the child's current body temperature data is normal; if the exercise behavior determines that the body temperature data is normal, environmental factors may still cause abnormal body temperature. The present invention then analyzes the abnormality of the change amplitude and duration of the current body temperature data, and analyzes the regional influence of environmental factors based on the current location data of multiple children to obtain the environmental abnormality degree of the current body temperature data; finally, the comprehensive abnormality degree of the child's current body temperature data is obtained, and the transmission time interval is optimized. That is, when the comprehensive abnormality degree is high, it can be determined that it is not caused by real body temperature changes. Even if the body temperature changes are large, the system can still maintain a large transmission time interval, reducing unnecessary communication burden, thereby achieving optimal transmission efficiency. The present invention eliminates the influence of exercise behavior and environmental factors on the monitored body temperature data, determines the optimized time interval between the transmission time of the child's current body temperature data and the transmission time of the next body temperature data, thereby achieving more optimized transmission of the child's body temperature data. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0048] Figure 1 A schematic diagram of the basic flow of a method for processing child health monitoring data provided by one embodiment of the present invention;

[0049] Figure 2 The following is a schematic diagram of the basic composition of a child health monitoring data processing system provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0050] In order to further illustrate the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail a method and system for processing child health monitoring data according to the present invention, its specific implementation, structure, features and effects. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics of one or more embodiments may be combined in any suitable form.

[0051] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this invention pertains. Terms such as "comprises," "comprising," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a circuit structure, article, or device comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such article or device. In the absence of further limitations, the phrase "comprising a ..." to define an element does not preclude the presence of other identical elements in the article or device comprising the element.

[0052] The following describes in detail a method for processing child health monitoring data provided by the present invention with reference to the accompanying drawings.

[0053] See also Figure 1 , which shows the basic process of a child health monitoring data processing method provided by an embodiment of the present invention.

[0054] like Figure 1 As shown, an embodiment of the present invention provides a method for processing child health monitoring data, specifically comprising:

[0055] S100: Acquire the child's location, body temperature, and heart rate data.

[0056] A smart bracelet is a small electronic device worn on a child's wrist. It is usually equipped with multiple sensors. Among them, the position sensor (GPS) is used to obtain the child's (wearer's) location in real time, that is, the position of the smart bracelet in space is used as the child's location. The heart rate sensor (photoplethysmography) is used to monitor the child's (wearer's) heart rate in real time, and the body temperature sensor (thermocouple) is used to measure the child's (wearer's) skin surface temperature in real time.

[0057] 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 in the memory of the smart bracelet, which can save the position, body temperature and heart rate data of multiple moments in the history. 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 position, body temperature and heart rate data obtained in this way include the current position data, current body temperature data and current heart rate data as well as The historical location data, historical body temperature data and historical heart rate data at each moment, among which, The value of can be all the historical records stored in the smart bracelet. When the number of historical records stored in the smart bracelet is large, a certain number of historical records can also be taken, such as wait.

[0058] S200: 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, obtain the exercise behavior of the child's current heart rate, and determine whether the child's current body temperature data is normal.

[0059] Exercise increases muscle metabolic activity, leading to energy expenditure and heat production. Meanwhile, metabolic products (such as carbon dioxide and lactic acid) must be rapidly transported through the bloodstream to the lungs and kidneys for excretion. Because muscles demand more oxygen and nutrients, the heart beats faster to enhance circulation, ensuring a timely supply of oxygen and nutrients to the muscles while effectively excreting metabolic waste. Simultaneously, exercise raises body temperature, and the body accelerates heat dissipation through increased blood flow, helping to maintain a stable body temperature. The increased heart rate helps draw heat to the surface of the skin, cooling the body through heat dissipation mechanisms.

[0060] In contrast, increases in body temperature caused by other factors (such as changes in ambient body temperature or illness) do not usually create such urgent demands for oxygen, nutrients, and waste removal, and therefore the heart rate changes are smaller. Therefore, the increase in body temperature caused by exercise is usually accompanied by a significant increase in heart rate.

[0061] Based on the above analysis, in an embodiment 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.

[0062] Among them, 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 are analyzed to obtain the movement behavior of the child's current heart rate. The specific implementation method is: 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, the movement behavior of the child's current heart rate is obtained. Furthermore, the heart rate movement behavior of the child's current heart rate data compared with the historical heart rate data is constructed:

[0063]

[0064] Where, Indicates the child’s current heart rate data and the Heart rate exercise behavior compared with heart rate data at historical moments; Represents the maximum and minimum normalization function (comparing the monitoring data at the current moment with the monitoring data at other historical moments); Indicates the child’s current heart rate data; Indicates children's Heart rate data at historical moments; Indicates the child’s current body temperature data; Indicates children's Temperature data at historical moments.

[0065] The logic of the formula is that if the child is currently in motion, the child's current heart rate data increases relative to the historical heart rate data. The current temperature data of the child will also increase relative to the historical temperature data. However, since the temperature changes relatively slowly relative to the heart rate, it is usually The increase will be less than The increase in If the child's temperature rises due to external environment or illness, is larger, while the child's current heart rate data remains unchanged or changes slightly, that is, The value is small, so The increase will be greater than The increase in The value is small.

[0066] Similarly, the heart rate movement behavior of the child's current heart rate data can be determined by comparing it with the heart rate data of each monitoring stored in history.

[0067] Having determined the heart rate-motor behavior of the child's current heart rate data compared to each historically stored heart rate data, we will next use all historically stored data to evaluate the child's current heart rate-motor behavior. That is, based on the heart rate-motor behavior of the current heart rate data compared to each historically stored heart rate data, we can obtain the child's current heart rate-motor behavior, namely:

[0068]

[0069] Where, Indicates the exercise behavior of the child's current heart rate; Indicates the child’s current heart rate data and the Heart rate exercise behavior compared with heart rate data at historical moments; Indicates the total number of historical moments obtained; represents the linear normalization function.

[0070] For the stored historical body temperature data and historical heart rate data pairs, not every temperature-heart rate data pair monitored at every historical moment is truly usable; if the smart bracelet is worn improperly or too loosely, the sensor cannot fit closely to the skin, resulting in inaccurate body temperature and heart rate data; if there is strenuous exercise or vibration, the smart bracelet may also be offset, which will also affect the stability of the sensor and thus lead to inaccurate body temperature and heart rate data; in addition, clothing obstruction will also affect the contact between the sensor and the skin, reducing the accuracy of body temperature and heart rate data.

[0071] Then, it is determined whether the child's current body temperature data is normal, including: setting a motion behavior threshold value, the threshold value can be 0.7, and determining whether the corrected motion behavior is less than or equal to the motion behavior threshold value; if so, , 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 disturbed by exercise. The temperature increase at this time is 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 is currently exercising. At this time, the child's body temperature rise is not due to pathological reasons and needs to be monitored. At this time, the comprehensive abnormality of the child's current body temperature data is .

[0072] The human body possesses powerful self-regulatory abilities (such as regulating body temperature and heart rate). When heart rate or body temperature changes, the body responds through the autonomic nervous system to maintain a stable physiological state. Changes in heart rate and body temperature over a short period of time are typically gradual. Even when caused by exercise or emotional fluctuations, these fluctuations typically occur gradually rather than suddenly. Therefore, under normal circumstances, the change between two consecutive moments is not very drastic. However, changes in body temperature and heart rate data caused by improper wear, for example, are often sudden and volatile.

[0073] 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 true 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 the adjacent moments, and analyzing the difference between the historical heart rate data and the historical heart rate data corresponding to the 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 true availability of the historical body temperature data and historical heart rate data pair. Construct the first The formula for calculating the true availability of the historical temperature data and historical heart rate data at a historical moment is:

[0074]

[0075] Where, Indicates the The actual availability of historical body temperature data and historical heart rate data at each historical moment; Indicates the Historical heart rate data at historical moments; Indicates the Historical heart rate data at historical moments; Indicates the Historical body temperature data at historical moments; Indicates the Historical body temperature data at historical moments; Expressed as a natural constant An exponential function with base .

[0076] Similarly, the true availability of body temperature and heart rate data pairs corresponding to all historical moments can be determined.

[0077] 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:

[0078]

[0079] Where, Indicates the corrected motor behavior of the child's current heart rate; Indicates the total number of historical moments obtained; Indicates the The actual availability of historical body temperature data and historical heart rate data at each historical moment; Indicates the child’s current heart rate data and the Heart rate exercise behavior compared with heart rate data at historical moments; represents the linear normalization function.

[0080] Indicates the The actual availability of historical temperature data and historical heart rate data at each historical moment is different from that of all The ratio of the actual availability corresponding to the historical moment, that is, The relative size of the real availability corresponding to the historical moment. The historical moment with larger real availability has a better control effect on the current heart rate exercise behavior. right Weighted to obtain the corrected exercise behavior of the child's current heart rate.

[0081] Then, it is determined whether the child's current body temperature data is normal, including: setting a motion behavior threshold value, the threshold value can be 0.7, and determining whether the corrected motion behavior is less than or equal to the motion behavior threshold value; if so, , 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 disturbed 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 is currently exercising. At this time, the child's body temperature rise is not due to pathological reasons and needs to be monitored. At this time, the comprehensive abnormality of the child's current body temperature data is .

[0082] S300: If yes, based on the current body temperature data and the 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 a single abnormality degree of the child's current body temperature data.

[0083] When the child's current heart rate is or modifying motor behavior When it is greater than the motion behavior threshold, the comprehensive abnormality of the current body temperature data has been obtained as or However, when the child's current heart rate is low in terms of exercise behavior or modified exercise behavior, 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 will also cause abnormal changes in the measured body surface temperature without affecting the heart rate and exercise behavior. Therefore, under the premise of initially judging that the child's currently measured body temperature is normal ( ), it is necessary to further judge the abnormality of the child’s current body temperature in combination with environmental factors.

[0084] On the premise that the child's current body temperature data is initially judged to be normal, that is, the child's current heart rate and exercise behavior are relatively small, or Under the premise of greater uncertainty, since the temperature sensor of the smart bracelet is usually located at the wrist, the temperature of this part is particularly sensitive to changes in external temperature. When the environment changes drastically, these sensors can quickly perceive this change, resulting in rapid fluctuations in the body temperature measurement data. Therefore, if the degree of change between the child's current measured body temperature data and the body temperature data measured at the previous moment is greater than the average temperature measured at all adjacent historical moments, it proves that environmental factors may have affected the currently monitored body temperature data.

[0085] Temperature changes in children caused by environmental factors are not only accompanied by abnormal temperature amplitudes but can also manifest as rapid temperature fluctuations. For example, when a child is suddenly exposed to high or low temperatures, their surface temperature can change rapidly. However, as environmental conditions return to normal or the body's regulatory mechanisms kick in, the temperature quickly returns to normal. Therefore, environmentally induced temperature changes are typically short-lived. In contrast, pathological factors (such as viral infections, inflammation, and endocrine disorders) are often long-lasting and persistent, affecting the immune system and metabolic processes in the body, leading to long-term abnormal temperature changes.

[0086] 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 temperature change at a more distant historical moment, that is, the abnormality lasts for a long time, then it is more likely to be caused by environmental factors. Therefore, in an embodiment 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, the abnormality of the change amplitude of the current body temperature data and the duration of the abnormality are analyzed to obtain a single abnormality degree of the child's current body temperature data. Further, including:

[0087] First, by calculating the ratio of the difference between the current temperature data and the temperature data of the adjacent monitoring time to the average difference between all adjacent historical temperature data, combined with the correction of movement behavior, the abnormality of the change amplitude of the child's current temperature data is obtained. The calculation formula for the abnormality of the change amplitude of the child's current temperature data is constructed as follows:

[0088]

[0089] Where, Indicates the abnormality of the change in the child's current body temperature data; Indicates the child’s current body temperature data; Indicates the child's body temperature data at the moment before the current moment; Indicates the Temperature data of children at historical moments; Indicates the Temperature data of children at historical moments; Indicates the total number of historical moments obtained; Indicates the corrected motor behavior of the child's current heart rate; Expressed as a natural constant An exponential function with base ; represents the linear normalization function.

[0090] It should be noted that the abnormality of the change amplitude of the child's current body temperature data can also be obtained by combining the movement behavior, that is, Replace with .

[0091] Indicates the difference between the child's body temperature data measured at the current moment and the previous historical moment. Represents the average difference between all adjacent historical temperature data, through the ratio of the two Get the change range of the child’s current body temperature data, If it is larger, it means that the child’s current body temperature data suddenly increases, which means that the change range of the child’s current body temperature data is abnormally large.

[0092] Then, the difference between the abnormality of the change amplitude of the current body temperature data and the abnormality of the change amplitude of the historical body temperature data is calculated, and combined with the time weight, the abnormality duration of the current body temperature data is obtained.

[0093] Finally, based on the abnormality of the change amplitude and the duration of the abnormality, the single abnormality degree of the child's current body temperature data is obtained. The calculation formula for the single abnormality degree of the child's current body temperature data is constructed as follows:

[0094]

[0095] Where, Indicates the single abnormality of the child's current body temperature data; Indicates the total number of historical moments obtained; Indicates the abnormality of the change in the child's current body temperature data; Indicates the The abnormality of the change range of children's body temperature data at each historical moment; Indicates the The closer the historical moment is to the current moment, the smaller the serial number is, that is, the moment before the current moment is the first historical moment; represents the linear normalization function.

[0096] Indicates the difference between the abnormality of the change amplitude of the child's current body temperature data and the abnormality of the change amplitude of the child's body temperature data at a historical moment. The larger the value, the greater the abnormality of the change amplitude of the current body temperature data, and The larger the value, the greater the difference between the abnormality of the change amplitude of the current body temperature data and the abnormality of the change amplitude of the body temperature data at a more distant historical moment; Indicates the time weight. The larger the value, the older the historical moment, the greater the time weight. Assign greater weight.

[0097] S400: Based on the current location data of multiple children and combined with the single abnormality, the regional impact of environmental factors is analyzed to obtain the environmental abnormality of the current body temperature data.

[0098] Since environmental factors usually show consistency within a specific area, when the temperature in an area fluctuates drastically, this change will synchronously affect all individuals in the area. In other words, abnormal body temperatures caused by the environment are usually widespread in the same area. Therefore, within the range that children's current Bluetooth can monitor, the abnormal body temperatures of all smart bracelet monitoring points will be relatively high.

[0099] Further assume that within the monitoring range of the current children's smart bracelet, there are The presence of multiple 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 of the body temperature measured by these bracelets, the higher the abnormality of the child's current measured temperature data.

[0100] Based on the above analysis, in an embodiment of the present invention, based on the current location data of multiple children, combined with a single abnormality, the regional influence of environmental factors is analyzed to obtain the environmental abnormality of the current body temperature data. The specific implementation method is as follows: 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 a single abnormality, the regional influence of environmental factors is analyzed to obtain the environmental abnormality of the current body temperature data. The calculation formula for the environmental abnormality of the current body temperature data of the current child is constructed as follows:

[0101]

[0102] Where, Indicates the environmental abnormality of the current body temperature data of the current child; Indicates that there are a total of A smart bracelet; Indicates the current child and other children The Euclidean distance of Indicates other children The single abnormality of the current body temperature data; Indicates the natural base An exponential function with base .

[0103] Other children The single abnormality of the current body temperature data The larger the value is, the higher the environmental abnormality of the child's current body temperature data is; Indicates the distance between the current child and other children. The larger the value, the closer other children are to the current child. The closer the distance to the current child, the right Weighted, that is, other children The closer the distance to the current child, the more other children The more abnormal the single degree of the current body temperature data is, the more it can reflect the environmental abnormality of the current child's current body temperature data.

[0104] S500: Obtaining the comprehensive abnormality of the child's current body temperature data based on the movement behavior and the environmental abnormality.

[0105] Based on the movement behavior and environmental abnormality, the comprehensive abnormality of the child's current body temperature data is obtained. That is, when the child's current body temperature data is normal, the comprehensive abnormality of the child's current body temperature data is the environmental abnormality; when the child's current body temperature data is abnormal, the comprehensive abnormality of the child's current body temperature data is the corrected movement behavior (or movement behavior). That is:

[0106]

[0107] Where, Indicates the comprehensive abnormality of the child’s current body temperature data; Indicates the corrected motor behavior of the child's current heart rate; Indicates the exercise behavior of the child's current heart rate; Indicates the environmental abnormality of the current child's current body temperature data.

[0108] S600: According to the comprehensive abnormality degree and in combination with the change of the current body temperature data, 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.

[0109] Generally speaking, when a child's body temperature fluctuates significantly, the time interval between temperature data transmissions should be shortened to allow for faster acquisition of more data when the temperature is abnormal, allowing for timely response to potential health risks. Specifically, if the change in the current temperature relative to the last transmission moment is greater than the change in the last transmission moment relative to the previous transmission moment, the time interval should be shortened. Conversely, if the change in the current temperature relative to the last transmission moment is less than the change in the last transmission moment relative to the previous transmission moment, the time interval should be increased.

[0110] However, if the current change in body temperature is caused by exercise behavior or environmental factors, that is, If the temperature is high, then even if the body temperature changes, the system does not need to shorten the transmission time interval, and the time interval can still be kept large to avoid unnecessary frequent data transmission.

[0111] Based on the above analysis, in an embodiment of the present invention, according to the comprehensive abnormality, combined with the change of the current body temperature data, 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. The specific implementation method is: according to the current body temperature data, the body temperature data transmitted last time and the body temperature data transmitted last time, the degree of change of 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 last body temperature data, the last transmission time interval is obtained; according to the degree of change of the current body temperature data and the last 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, 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. 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:

[0112]

[0113] Where, Indicates the optimized time interval between the transmission time of the child's current body temperature data and the transmission time of the next body temperature data; Indicates the comprehensive abnormality of the child’s current body temperature data; Indicates the last transmitted body temperature data. Indicates the last transmitted body temperature data; Indicates current body temperature data; Indicates the time interval between the last temperature data transmission time and the previous temperature data transmission time, that is, the last transmission time interval.

[0114] Indicates the general time interval between the transmission time of the child's current body temperature data and the transmission time of the next body temperature data obtained under normal circumstances, through Optimize the general time interval of transmission, The larger the value, the more the currently monitored body temperature data is affected by exercise behavior or the external environment. At this time, the body temperature change cannot be used as a basis for adjusting the transmission time interval, and the general time interval needs to be optimized.

[0115] After determining the optimal time interval between the current child's temperature data transmission and the next temperature data transmission, the system will transmit the child's real-time temperature data via the IoT at the next moment after the current interval ends, and update that moment as the new current time. This process repeats continuously. In this way, the system can increase the transmission frequency only when there is a significant change in body temperature, after eliminating the influence of physical activity and environmental factors, thereby reducing unnecessary communication burden and achieving optimal transmission efficiency.

[0116] Based on the same inventive concept as the above method, this embodiment also provides a child health monitoring data processing system.

[0117] See also Figure 2 , which shows the basic composition of a child health monitoring data processing system provided by an embodiment of the present invention.

[0118] like Figure 2 As shown, a child health monitoring data processing system includes: a memory 10 and a processor 20, wherein:

[0119] Memory 10, for storing program code;

[0120] The processor 20 is used to read the program code stored in the memory 10 and execute it to obtain the child's position, body temperature and heart rate data; 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 movement behavior of the child's current heart rate, and judge 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 amplitude of the current body temperature data and the duration of the abnormality to obtain the single abnormality of the child's current body temperature data; based on the current position 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; according to the movement behavior and environmental abnormality, obtain the comprehensive abnormality of the child's current body temperature data; 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.

[0121] Furthermore, the processor 20 includes: a child health data collection module 21, a movement behavior analysis module 22, an environment abnormality analysis module 23 and a time interval optimization module 24. Among them:

[0122] The child health data collection module 21 is used to obtain the child's location, body temperature and heart rate data;

[0123] The movement behavior analysis module 22 is used 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, obtain the movement behavior of the child's current heart rate, and determine whether the child's current body temperature data is normal;

[0124] The environmental abnormality analysis module 23 is configured to, if the child's current body temperature data is normal, analyze the abnormality of the change amplitude and duration of the current body temperature data based on the current body temperature data and historical body temperature data to obtain a single abnormality degree of the child's current body temperature data; and analyze the regional impact of environmental factors based on the current location data of multiple children and the single abnormality degrees to obtain an environmental abnormality degree of the current body temperature data;

[0125] The time interval optimization module 24 is used to obtain the comprehensive abnormality of the child's current body temperature data based on the movement behavior and environmental abnormality; and based on the comprehensive abnormality and combined with the current body temperature data changes, 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.

[0126] It should be noted that the order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0127] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. A method for processing child health monitoring data, characterized in that: The method comprises: Obtain the child's location, body temperature, and heart rate data, where the child's location refers to the location 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, obtain the exercise behavior of the child's current heart rate, and determine whether the child's current body temperature data is normal; If yes, based on the current body temperature data and the 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 a 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, the regional impact of environmental factors is analyzed to obtain the environmental abnormality degree of the current body temperature data; Obtaining a comprehensive abnormality degree of the child's current body temperature data based on the movement behavior and the environmental abnormality degree; According to the comprehensive abnormality degree and in combination with the current temperature data change, an optimized time interval between the transmission time of the current temperature data and the transmission time of the next temperature data is obtained; Get the child's current heart rate and exercise behavior, including: Calculate the normalized difference between the current body temperature data and the historical body temperature data, and calculate the normalized difference 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 body temperature difference and the normalized heart rate difference; The method further includes: analyzing the volatility of the historical body temperature data and the historical heart rate data between two consecutive moments to obtain the true availability of the historical body temperature data and the historical heart rate data; Performing weighted correction on the movement behavior according to the real availability to obtain a corrected movement behavior of the child's current heart rate; Determine whether the child's current body temperature data is normal, including: Setting a motion behavior threshold, and determining whether the modified motion behavior is less than or equal to the motion behavior threshold; If yes, the child’s current body temperature data is normal; If not, the child's current body temperature data is abnormal; Based on the current body temperature data and historical body temperature data, the abnormality of the change amplitude of the current body temperature data and the duration of the abnormality are analyzed to obtain the single abnormality degree of the child's current body temperature data, including: Calculate the ratio of the difference between the current body temperature data and the body temperature data of the adjacent monitoring time to the average difference between all adjacent historical body temperature data, and combine the corrected movement behavior to obtain the abnormality of the change amplitude of the child's current body temperature data; Calculate the difference between the abnormality of the change amplitude of the current body temperature data and the abnormality of the change amplitude of the historical body temperature data, and combine it with the time weight to obtain the abnormal duration of the current body temperature data; Obtaining a single abnormality degree of the child's current body temperature data according to the abnormality of the change amplitude and the duration of the abnormality; Based on the current location data of multiple children, combined with the single abnormality, the regional impact of environmental factors is analyzed to obtain the environmental abnormality 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, the regional impact of environmental factors is analyzed to obtain the environmental abnormality of the current body temperature data; According to the movement behavior and the environmental abnormality, a comprehensive abnormality of the child's current body temperature data is obtained, including: When the child's current body temperature data is normal, the comprehensive abnormality of the child's current body temperature data is the environmental abnormality; When the child's current body temperature data is abnormal, the comprehensive abnormality of the child's current body temperature data is the corrected movement behavior; The calculation formula for the heart rate exercise behavior of a child's current heart rate data compared with historical heart rate data is: Where, Indicates the child’s current heart rate data and the Heart rate exercise behavior compared with heart rate data at historical moments; represents the maximum and minimum normalization function; Indicates the child’s current heart rate data; Indicates children's Historical heart rate data at historical moments; Indicates the child’s current body temperature data; Indicates children's Historical body temperature data at historical moments; The calculation formula for the exercise behavior of the child's current heart rate is: Where, Indicates the exercise behavior of the child's current heart rate; Indicates the total number of historical moments obtained; represents the linear normalization function; No. The formula for calculating the true availability of the historical temperature data and historical heart rate data at a historical moment is: Where, Indicates the The actual availability of historical body temperature data and historical heart rate data at each historical moment; Indicates the Historical heart rate data at historical moments; Indicates the Historical body temperature data at historical moments; Expressed as a natural constant An exponential function with base .

2. The method for processing child health monitoring data according to claim 1, wherein: According to the comprehensive abnormality, combined with the current temperature data change and the last transmission time interval, the optimized time interval between the transmission time of the current temperature data and the transmission time of the next 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 last time, the degree of change of the current body temperature data is obtained; Obtain the last transmission time interval according to the time interval between the last transmission time of the body temperature data and the transmission time of the previous body temperature data; Obtaining a general 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 degree of change of the current body temperature data and the time interval of the last transmission; 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.

3. A child health monitoring data processing system, characterized in that: The system comprises: a memory and a processor, wherein: The memory is used to store program code; The processor is configured to read the program code stored in the memory and execute the method according to any one of claims 1 to 2.

4. The child health monitoring data processing system according to claim 3, characterized in that: The processor includes: Children's health data collection module, used to obtain children's location, body temperature and heart rate data; The exercise behavior analysis module is used 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, obtain the exercise behavior of the child's current heart rate, and determine whether the child's current body temperature data is normal; An environmental abnormality analysis module is configured to, if the child's current body temperature data is normal, analyze the abnormality of the change amplitude and duration of the current body temperature data based on the current body temperature data and historical body temperature data to obtain a single abnormality degree of the child's current body temperature data; and analyze the regional impact of environmental factors based on the current location data of multiple children and the single abnormality degree to obtain an environmental abnormality degree of the current body temperature data; The time interval optimization module is used to obtain the comprehensive abnormality of the child's current body temperature data based on the movement behavior and the environmental abnormality; and according to the comprehensive abnormality, combined with the current body temperature data change, 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.

Images