Long-time, low-power-consumption, intelligent and continuous wearable body temperature monitoring and early warning equipment

Abstract

The invention discloses long-time, low-power-consumption, intelligent and continuous wearable body temperature monitoring and early warning equipment which comprises an equipment body, a temperature sensor, an information processor, a flexible adhesive layer and a power supply. On one hand, the temperature measuring face based on the temperature sensor can synchronously deform along with the flexible adhesive layer to be attached to the armpit or forehead skin curve so that body temperature information can be accurately obtained, once the body temperature is abnormal, the device can send alarm information to a guardian, algorithm analysis can be conducted according to the monitored body temperature data, and the monitoring accuracy is improved. Scientific processing suggestions are provided for guardians, and intelligent early warning is provided, so that the guardians can take countermeasures in time. On the other hand, the size is small, the foreign body sensation of wearing is weak, the device is suitable for long-time wearing, the device can be directly attached to the armpit for long-time and continuous body temperature monitoring, daily behaviors of the device cannot be affected, parents and caregivers are effectively helped to better know the health state of infants, and the intelligent and efficient child rearing auxiliary function is provided.

Description

Technical Field

[0001] The present invention belongs to the field of medical devices, and in particular relates to a long-term, low-power, intelligent, continuous wearable body temperature monitoring and early warning device. Background Art

[0002] The health of infants and young children is an important concern in family parenting, and body temperature is one of the key indicators for assessing the health of infants and young children. Because their immune systems are not yet fully mature and their ability to regulate body temperature is poor, changes in body temperature may indicate changes in their health. Therefore, it is crucial for parents and guardians to monitor changes in infants and young children's body temperature in a timely manner. Infants and young children's body temperature changes are sensitive and easily affected by the environment. Small fluctuations in body temperature may indicate potential health risks, such as colds, infections, fever, etc.

[0003] At present, the mainstream infant temperature monitoring technologies in the industry mainly include traditional mercury thermometers, smart bracelets, ear thermometers and infrared thermometers, but there are still some problems in the use process. Among them, traditional mercury thermometers need to be used with clamping thermometers when measuring temperature. When infants and young children do not cooperate with temperature measurement, it is often difficult to operate and cannot achieve real-time monitoring; most smart bracelets and other temperature measurement equipment are designed for adults and fail to meet the physiological characteristics of infants and young children. Due to the limitation of the measurement site, the temperature measurement accuracy is low, and the wearing comfort and endurance need to be improved; ear thermometers are complicated to operate, and improper operation will lead to measurement errors, especially when infants and young children have low cooperation. It is difficult to measure, and it is easily affected by the cleanliness of the ear canal and the position of the probe, which is not suitable for long-term and continuous monitoring; although infrared thermometers are non-contact, the measurement accuracy is greatly affected by the environment, and it lacks the function of recording the trend of temperature changes. Therefore, traditional temperature measurement tools (such as mercury thermometers and electronic thermometers) require manual operation, and can only obtain temperature values ​​in a single measurement, which cannot meet the needs of long-term, continuous, wearable monitoring and real-time warning. In addition, infants and young children often increase the difficulty of measurement due to lack of cooperation or discomfort, further reducing the practicality of traditional measurement methods.

[0004] At the same time, with the development of wearable smart devices, some smart body temperature devices for health monitoring have begun to appear on the market, such as: CN113273971B, a wearable smart body temperature monitoring device; CN110558953A, a wearable wireless smart temperature recorder. The functions of both are simple temperature monitoring and early warning, and due to the poor battery life, they cannot perform long-term continuous monitoring. At the same time, the former uses an infrared temperature sensor, and the wearable method is mainly necklace lanyard type and belt type. The temperature measurement accuracy is insufficient, and the temperature measurement position does not have a unified medical reference standard. In addition, the device is large in size, and the foreign body sensation caused by the wearing method is strong, which is not suitable for long-term temperature monitoring of infants and young children; the latter still uses an infrared temperature sensor. Although the overall size of the device is smaller than the former, the wristband type is not suitable for long-term wearing by infants and young children, and is greatly affected by environmental changes and activities. There are still deficiencies in the temperature measurement position and temperature measurement accuracy, and it also cannot meet the scientific monitoring of infants and young children's body temperature. Therefore, most devices have high power consumption and are limited by the size of the device. The battery life is often poor and cannot meet the long-term monitoring needs; most wearable devices use infrared temperature sensors, and the temperature sensor has insufficient temperature measurement accuracy and cannot effectively capture subtle changes in body temperature; at the same time, existing devices usually only have conventional high temperature alarm functions, and cannot provide accurate and intelligent disease warnings based on the speed or trend of body temperature changes (such as influenza and other diseases with typical periodic body temperature changes).

[0005] In short, the existing infant temperature monitoring technology mainly relies on traditional thermometers, such as ear thermometers, axillary thermometers and oral thermometers. Although these devices can accurately measure body temperature, they require physical contact within a certain period of time, and cannot provide real-time monitoring of body temperature changes, and cannot help parents understand the temperature health status of infants and young children in real time or for a long time. Although some intelligent body temperature monitoring devices, such as temperature monitoring patches and smart thermometers, have gradually appeared on the market in recent years, some devices can transmit body temperature data to mobile phones via Bluetooth or Wi-Fi, and display and record them in real time through apps. However, these devices often have inaccurate temperature sensors, especially in complex environments (such as when infants and young children are active), which may lead to deviations in body temperature data; the sensors and communication modules used have high power consumption, which affects the long-term continuous wear monitoring of the equipment; and some existing devices are not perfect in the alarm mechanism, with only a simple body temperature alarm function, which cannot provide accurate and scientific disease warning reminders based on multiple factors such as the speed and characteristics of body temperature changes. At the same time, the existing infant disease detection technology is mostly passive diagnosis, which is often carried out only after the symptoms are obvious, missing the best time for early intervention. Detection technologies also rely heavily on methods such as blood tests and test kit tests, which are usually expensive, complicated and require the participation of medical institutions, prolonging the diagnosis time. In addition, detection methods such as blood tests and throat swab sampling usually cause fear and discomfort in infants and young children, increasing the difficulty of detection. Summary of the invention

[0006] The technical problem to be solved by the present invention is to overcome the deficiencies of the prior art and provide an improved long-term, low-power, intelligent, continuous wearable body temperature monitoring and early warning device.

[0007] In order to solve the above technical problems, the technical solution adopted by the present invention is as follows:

[0008] A long-term, low-power, intelligent, continuous wearable body temperature monitoring and early warning device, comprising a device body, a temperature sensor, an information processor, a flexible adhesive layer, and a power supply, wherein the flexible adhesive layer is attached to the temperature measuring surface of the temperature sensor, the information processor comprises an information receiving end connected to the temperature sensor, a data processing unit, and a signal releasing end, in particular, the temperature measuring surface of the temperature sensor can be deformed synchronously with the flexible adhesive layer to fit the skin curve of the armpit or forehead; the data processing unit comprises a data preprocessing module, a feature extraction module, a curve matching module, an analysis and prediction module, and an early warning and notification module, wherein in the curve matching stage, a dynamic time warping algorithm is used to compare the real-time body temperature curve with the reference body temperature change curve stored in the database, and the matching degree is calculated, and the algorithm and processing steps are as follows:

[0009] 1) Construct the cost matrix. For two temperature time series X = [x_1, x_2, ..., x_n] and Y = [y_1, y_2, ..., y_m], create an n × m matrix D, where each element D[i][j] represents the path difference between x_i and y_j;

[0010] 2) Cumulative cost calculation, initialize the cumulative cost matrix C, where C[0][0] = D[0][0], then, for each subsequent element C[i][j], it is equal to D[i][j] plus the minimum cumulative cost of its three possible predecessor positions: C[i-1][j], from the top; C[i][j-1], from the left; C[i-1][j-1], from the top left;

[0011] 3) Path backtracking, starting from the last element of the cumulative cost matrix, and tracing backwards to find the path with the minimum cumulative cost;

[0012] 4) Result interpretation: The final path represents the optimal alignment of the two temperature time series, and the sum of all costs on the path is the distance between the two sequences. The smaller the distance, the higher the similarity, and the larger the distance, the greater the difference. If the matching degree is higher than the set threshold or the temperature change rate is abnormal, the signal release end will send a warning signal to the user terminal.

[0013] According to a specific implementation and preferred aspect of the present invention, the dynamic time warping algorithm is used to measure the similarity between two time series, when the series are different in time or speed, by "stretching" or "compressing" one time series to align it with another time series to obtain the minimum distance path between the two. That is, in this application, the sequence is the temperature change curve over time between different individuals, that is, the temperature time series, and the minimum distance path is used as the similarity criterion.

[0014] According to another specific implementation and preferred aspect of the present invention, data collection is performed in real time based on the information receiving end, and the temperature measurement surface has multiple temperature measurement points. Based on multi-point temperature measurement, not only more data can be obtained, but also the body temperature change rate can be obtained more accurately, which is more conducive to model establishment.

[0015] Preferably, based on the collected body temperature, the data preprocessing module uses a filtering algorithm to eliminate noise and detect and correct abnormal data. For example, temperature values ​​that exceed the physical limit can be removed to improve modeling accuracy.

[0016] According to another specific implementation and preferred aspect of the present invention, the key features extracted by the feature extraction module include temperature change trend, temperature change rate and whether it exceeds a set threshold. Based on the mutual verification of multiple features, the accuracy of real-time body temperature acquisition can be more accurately reflected.

[0017] In some specific embodiments, the data processing unit further includes a feedback and optimization module, wherein the feedback and optimization module can perform self-learning and optimization to update the model and early warning algorithm. The historical data is learned and optimized, and the model and early warning algorithm are continuously updated to improve the prediction accuracy and robustness.

[0018] Preferably, the self-learning method is SVM, random forest or LSTM. Random Forest, Support Vector Machine (SVM) and Long Short-Term Memory Network (LSTM) are very common machine learning algorithms.

[0019] According to another specific implementation and preferred aspect of the present invention, the flexible adhesive layer has two layers and is located on the front and back of the device body. When used under the armpit, it fits the skin more stably to avoid loosening or falling off due to the movement of infants and young children.

[0020] In addition, the signal release end is connected to the user terminal via wire or wireless. The device body is made of a flexible gel shell. It has a weak sense of foreign body when worn, and is suitable for infants and young children to wear for a long time. It can be directly attached to the infant's armpit for long-term and continuous temperature monitoring without affecting their daily behavior.

[0021] Due to the implementation of the above technical solution, the present invention has the following advantages compared with the prior art:

[0022] Existing infant temperature monitoring technology mainly relies on traditional thermometers, such as ear thermometers, axillary thermometers and oral thermometers. Although these devices can accurately measure body temperature, they require physical contact within a certain period of time and cannot provide real-time monitoring of body temperature changes, and cannot help parents understand the temperature health status of infants and young children in real time or for a long time. Although some intelligent body temperature monitoring devices, such as temperature monitoring patches and smart thermometers, have gradually appeared on the market in recent years, some devices can transmit body temperature data to mobile phones via Bluetooth or Wi-Fi, and display and record them in real time through apps. However, these devices often have inaccurate temperature sensors, especially in complex environments (such as when infants and young children are active), which may lead to deviations in body temperature data; the sensors and communication modules used have high power consumption, which affects the long-term continuous wear monitoring of the equipment; and some existing devices are not perfect in alarm mechanism, with only a simple body temperature alarm function, which cannot provide accurate and scientific disease warning reminders based on multiple factors such as the speed and characteristics of body temperature changes. At the same time, existing infant disease detection technologies are mostly passive diagnostic methods, which are often carried out only after the symptoms are obvious, missing the best time for early intervention.Detection technology also relies heavily on methods such as blood tests and test kits, which are usually expensive, complicated, and require the participation of medical institutions, which prolongs the diagnosis time. In addition, detection methods such as blood tests and throat swab sampling usually cause fear and discomfort in infants and young children, increase the difficulty of detection, and so on. The present invention designs the structure of the temperature monitoring and early warning device as a whole, and cleverly solves the various shortcomings of the existing structure. After using the temperature monitoring and early warning device, first, the entire device is attached to the armpit or forehead through a flexible adhesive layer so that the temperature measuring surface fits the skin in the same shape; then, the device is paired with a pre-bound mobile terminal (such as a mobile phone) through the built-in signal release end of the device, and the device enters the working state and starts to monitor the temperature data; finally, based on the real-time collection of temperature information, denoising is performed to extract the required features, and then curve matching calculations are performed based on the extracted features. The final path represents the optimal alignment of the two temperature time series, and all costs on the path The sum is the distance between the two sequences. The smaller the distance, the higher the similarity. The larger the distance, the greater the difference. If the matching degree is higher than the set threshold or the temperature change rate is abnormal, the signal release end sends a warning signal to the user terminal. Therefore, on the one hand, the temperature measuring surface of the temperature sensor of the present invention can be deformed synchronously with the flexible adhesive layer to fit the skin curve of the armpit or forehead, so as to accurately and effectively obtain body temperature information. Once the body temperature is abnormal, the device will not only send an alarm message to the guardian, but also provide scientific processing suggestions and intelligent warnings to the guardian based on the algorithm analysis of the monitored body temperature data, so that the guardian can take timely countermeasures. On the other hand, the device is small in size and adopts a flexible gel shell. It has a weak foreign body sensation when worn, and is suitable for infants and young children to wear for a long time. It can be directly attached to the infant's armpit for long-term and continuous temperature monitoring, which will not affect their daily behavior, but also effectively help parents and caregivers better understand the health status of infants and young children, and provide intelligent and efficient parenting assistance functions. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 This is a module schematic diagram of the wearable body temperature monitoring and early warning device of the present invention;

[0024] Figure 2 for Figure 1 Schematic diagram of wearing;

[0025] Figure 3 It is a structural schematic diagram of the wearable body temperature monitoring and early warning device of the present invention;

[0026] Figure 4 It is a logical schematic diagram of the algorithm in the present invention;

[0027] Among them: 1. Equipment body; 2. Temperature sensor; 3. Information processor; 30. Information receiving end; 31. Data processing unit; 32. Signal release end; 4. Flexible adhesive layer; 5. Power source (battery or electronic); 6. User terminal. DETAILED DESCRIPTION

[0028] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without violating the connotation of the present invention, so the present invention is not limited by the specific embodiments disclosed below.

[0029] In the description of the present invention, it is to be understood that the terms “center”, “longitudinal”, “lateral”, “length”, “width”, “thickness”, “up”, “down”, “front”, “back”, “left”, “right”, “vertical”, “horizontal”, “top”, “bottom”, “inside”, “outside”, “clockwise”, “counterclockwise”, “axial”, “radial”, “circumferential”, etc., indicating orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0030] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0031] In the present invention, unless otherwise clearly defined and specified, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be directly connected, or indirectly connected through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements, unless otherwise clearly defined. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0032] In the present invention, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may mean that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Moreover, a first feature being "above", "above" or "above" a second feature may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. A first feature being "below", "below" or "below" a second feature may mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is lower in level than the second feature.

[0033] It should be noted that when an element is referred to as being "fixed to" or "disposed on" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "upper", "lower", "left", "right" and similar expressions used herein are for illustrative purposes only and do not represent the only implementation method.

[0034] like Figures 1 to 4 As shown, the long-term, low-power, intelligent, continuous wearable body temperature monitoring and early warning device involved in this embodiment includes a device body 1, a temperature sensor 2, an information processor 3, a flexible adhesive layer 4, a power supply 5, and a user terminal 6, wherein the flexible adhesive layer 4 is attached to the temperature measuring surface of the temperature sensor 2 (that is, arranged on the front of the device body 1), the power supply 5 is respectively connected to the temperature sensor 2 and the information processor 3 circuits, and the flexible adhesive layer 4 is also arranged on the back of the device body 1; the temperature measuring surface of the temperature sensor 2 can be deformed synchronously with the flexible adhesive layer 4 to fit the skin curve of the armpit or forehead.

[0035] Specifically, the information processor 3 includes an information receiving terminal 30 connected to the temperature sensor 2, a data processing unit 31, and a signal release terminal 32. The data processing unit 31 includes a data preprocessing module, a feature extraction module, a curve matching module, an analysis and prediction module, an early warning and notification module, and a feedback and optimization module.

[0036] In some specific embodiments, data collection is performed in real time based on the information receiving end 30, and the temperature measurement surface has multiple temperature measurement points. Based on multi-point temperature measurement, not only more data can be obtained, but also the temperature change rate can be obtained more accurately, and it is more conducive to model building. Preprocessing is performed based on the collected body temperature, and the data preprocessing module uses a filtering algorithm to eliminate noise, and detects and corrects abnormal data at the same time. For example, temperature values ​​that exceed the physical limit can be removed to improve the accuracy of modeling. The key features extracted by the feature extraction module include temperature change trend, temperature change rate and whether it exceeds the set threshold. Based on the mutual confirmation of multiple features, the accuracy of real-time body temperature acquisition can be more accurately reflected. The feedback and optimization module can perform self-learning and optimization to update the model and early warning algorithm. Learn and optimize historical data, continuously update the model and early warning algorithm, and improve the prediction accuracy and robustness. The self-learning method is SVM, random forest or LSTM. Random Forest (RandomForest), Support Vector Machine (Support Vector Machine, SVM) and Long Short-Term Memory Network (LSTM) are very common machine learning algorithms.

[0037] In this example, in the curve matching stage, the dynamic time warping algorithm is used to compare the real-time body temperature curve with the reference body temperature change curve stored in the database to calculate the matching degree, and the algorithm and processing steps are as follows:

[0038] 1) Construct the cost matrix. For two temperature time series X = [x_1, x_2, ..., x_n] and Y = [y_1, y_2, ..., y_m], create an n × m matrix D, where each element D[i][j] represents the path difference between x_i and y_j;

[0039] 2) Cumulative cost calculation, initialize the cumulative cost matrix C, where C[0][0] = D[0][0], then, for each subsequent element C[i][j], it is equal to D[i][j] plus the minimum cumulative cost of its three possible predecessor positions: C[i-1][j], from the top; C[i][j-1], from the left; C[i-1][j-1], from the top left;

[0040] 3) Path backtracking, starting from the last element of the cumulative cost matrix, and tracing backwards to find the path with the minimum cumulative cost;

[0041] 4) Result interpretation: The final path represents the optimal alignment of the two temperature time series, and the sum of all costs on the path is the distance between the two sequences. The smaller the distance, the higher the similarity, and the larger the distance, the greater the difference. If the matching degree is higher than the set threshold or the temperature change rate is abnormal, the signal release end will send a warning signal to the user terminal.

[0042] Furthermore, the dynamic time warping algorithm is used to measure the similarity between two time series. When the sequences differ in time or speed, one time series is "stretched" or "compressed" to align it with another time series to obtain the minimum distance path between the two. That is, in the present application, the sequence is the temperature change curve over time between different individuals, that is, the temperature time series, and the minimum distance path is used as the similarity criterion. In addition, the signal release end is connected to the user terminal via wired or wireless. The material of the device body is a flexible gel material shell. It has a weak sense of foreign body when worn, and is suitable for infants and young children to wear for a long time. It can be directly attached to the infant's armpit for long-term and continuous body temperature monitoring without affecting their daily behavior.

[0043] In short, the temperature monitoring and early warning device of the present application consists of the following main modules: temperature sensor, signal integration processing module, Bluetooth module, battery power module and mobile terminal. The modules are interconnected through circuit boards and communication interfaces to form a complete temperature monitoring and early warning system. In view of the special needs of infant temperature monitoring, it provides accurate temperature monitoring, influenza prediction, real-time alarm function, personalized processing suggestions, and adopts low power consumption and comfortable design, which greatly improves the effect and convenience of infant health monitoring. Temperature sensor: installed in the skin-tight part of the device, in full contact with the skin of the infant's armpit, to ensure the accuracy of temperature monitoring, and collect the temperature data of the infant's armpit. The collected analog or digital signal is transmitted to the signal processing module through electrical connection. Signal processing module: one end is connected to the temperature sensor and the other end is connected to the Bluetooth module. The signal transmitted by the temperature sensor is processed, including signal filtering, data format conversion and analysis. The processed temperature data is used to determine whether the warning threshold is reached, and the processing results are transmitted to the Bluetooth module. Low-power Bluetooth module: integrated with the signal processor module in the same circuit board, receives temperature data from the signal integrated processor, and is responsible for transmitting the processed temperature data to the mobile terminal via wireless communication. Battery module: optimized to support long-term wearable operation of the device, providing a stable power supply to each module through the power line, and supporting the operation of the temperature sensor, signal integrated processor and Bluetooth module. Mobile terminal: such as smart phones, tablets, etc. receive temperature data transmitted by the device via Bluetooth, and display, analyze and alarm on the supporting App. At the same time, based on the data analysis results and combined with the large database of typical temperature changes of influenza, compare the temperature data, identify potential disease risks, and help parents achieve early detection and intervention of diseases and provide scientific treatment suggestions.

[0044] In summary, taking influenza detection as an example, the specific implementation process is as follows:

[0045] First, the temperature sensor is fixed to the armpit where the temperature needs to be measured by adhesive tape to ensure that the curved surface of the sensor is in close contact with the skin; then, the low-power Bluetooth module built into the device is automatically paired with the pre-bound mobile terminal (such as a mobile phone), the device enters the working state, and starts to monitor the body temperature data. The high-precision temperature sensor collects the armpit temperature of infants and young children in real time by contacting the skin. The temperature signal is converted into a digital signal inside the sensor, and the body temperature data is collected every 5 seconds by default (the sampling rate can be adjusted according to needs); the signal integrated circuit board receives the temperature data from the temperature sensor, filters and de-noises the signal, and the temperature data after signal processing is transmitted to the bound mobile terminal APP through the Bluetooth module. The system analyzes the body temperature data through algorithms, including: whether it exceeds the normal temperature range, whether the temperature change rate is too fast (detecting the trend of rapid temperature rise), and by comparing the change trend of the infant body temperature data recorded during the fever cycle with the typical body temperature change curve stored in the influenza virus infection, the degree of matching between the infant body temperature change and the influenza pattern is judged, which is used to achieve early warning of infant influenza and other diseases. If the temperature or temperature data change trend is abnormal, the alarm mechanism will be triggered, and different treatment suggestions will be provided according to different situations, reminding parents to take corresponding measures. If the body temperature is between 37.5℃ and 38℃, it is recommended to take physical cooling measures (such as reducing clothing and local cold compresses). If the body temperature exceeds 38℃, it is recommended to seek medical attention immediately. If the temperature change trend is highly matched with the flu pattern, it will prompt close observation, rapid flu testing, and timely medical treatment. When the temperature data is normal, it will be continuously monitored, and users can view the current temperature data at any time. All collected temperature data will be stored in the mobile phone application, which is convenient for viewing historical data and temperature change trends. The data can be generated by day, week, and month for user reference or doctor diagnosis. Finally, when it is necessary to stop monitoring, the guardian can directly remove the device and turn off the power on the APP, and clean the surface of the device for next use.

[0046] Therefore, the present invention aims to solve the deficiencies in the prior art and provide an intelligent, long-term, continuous temperature monitoring device that can accurately monitor changes in infants' body temperature, send alarms to guardians in a timely manner, and provide corresponding treatment suggestions. The device is compact and uses a flexible gel shell. It has a weak sense of foreign body when worn and is suitable for infants to wear for a long time. It can be directly attached to the infant's armpit for long-term, continuous temperature monitoring without affecting their daily behavior. When the body temperature is abnormal, the device will not only send an alarm message to the guardian, but also provide scientific treatment suggestions and intelligent influenza warnings based on algorithm analysis of the monitored body temperature data, so that the guardian can take timely countermeasures. The device will provide long-term, continuous, wearable body temperature monitoring, effectively helping parents and caregivers to better understand the health status of infants and young children, and provide intelligent and efficient parenting assistance functions. In addition, machine learning methods (such as SVM, random forest or LSTM) are used to learn and optimize historical data, continuously update influenza models and early warning algorithms, and improve prediction accuracy and robustness. Moreover, through the closed-loop design of this logic block diagram, the system realizes long-term, continuous, and low-power body temperature monitoring, providing efficient and intelligent disease warning services.

[0047] The above detailed description of the present invention is intended to enable persons familiar with the art to understand the contents of the present invention and implement them. It does not limit the protection scope of the present invention. Any equivalent changes or modifications made according to the spirit of the present invention should be included in the protection scope of the present invention.

Claims

1. A long-term, low-power, intelligent, continuous wearable body temperature monitoring and early warning device, which includes a device body, a temperature sensor, an information processor, a flexible adhesive layer, and a power supply, wherein the flexible adhesive layer is attached to the temperature measuring surface of the temperature sensor, and the information processor includes an information receiving end connected to the temperature sensor, a data processing unit, and a signal release end, characterized in that: The temperature measuring surface of the temperature sensor can be deformed synchronously with the flexible adhesive layer to fit the skin curve of the armpit or forehead; The data processing unit includes a data preprocessing module, a feature extraction module, a curve matching module, an analysis and prediction module, and an early warning and notification module. In the curve matching stage, a dynamic time warping algorithm is used to compare the real-time body temperature curve with the reference body temperature change curve stored in the database to calculate the matching degree. The algorithm and processing steps are as follows: 1) Construct the cost matrix. For two temperature time series X = [x_1, x_2, ..., x_n] and Y = [y_1, y_2, ..., y_m], create an n × m matrix D, where each element D[i][j] represents the path difference between x_i and y_j; 2) Cumulative cost calculation, initialize the cumulative cost matrix C, where C[0][0] = D[0][0], then, for each subsequent element C[i][j], it is equal to D[i][j] plus the minimum cumulative cost of its three possible predecessor positions: C[i-1][j], from the top; C[i][j-1], from the left; C[i-1][j-1], from the top left; 3) Path backtracking, starting from the last element of the cumulative cost matrix, and tracing backwards to find the path with the minimum cumulative cost; 4) Result interpretation: The final path represents the optimal alignment of the two temperature time series, and the sum of all costs on the path is the distance between the two sequences. The smaller the distance, the higher the similarity, and the larger the distance, the greater the difference. If the matching degree is higher than the set threshold or the temperature change rate is abnormal, the signal release end will send a warning signal to the user terminal.

2. The long-term, low-power, intelligent, continuous wearable body temperature monitoring and early warning device according to claim 1 is characterized by: The dynamic time warping algorithm is used to measure the similarity between two time series when the series differ in time or speed, by "stretching" or "compressing" one time series to align it with another time series to obtain the minimum distance path between the two.

3. The long-term, low-power, intelligent, continuous wearable body temperature monitoring and early warning device according to claim 1 is characterized by: Data collection is performed in real time based on the information receiving end, and the temperature measuring surface has multiple temperature measuring points.

4. The long-term, low-power, intelligent, continuous wearable body temperature monitoring and early warning device according to claim 3 is characterized by: Based on the collected body temperature, the data preprocessing module uses a filtering algorithm to eliminate noise and detect and correct abnormal data.

5. The long-term, low-power, intelligent, continuous wearable body temperature monitoring and early warning device according to claim 1 is characterized by: The key features extracted by the feature extraction module include temperature change trend, temperature change rate and whether it exceeds a set threshold.

6. The long-term, low-power, intelligent, continuous wearable body temperature monitoring and early warning device according to claim 1 is characterized by: The data processing unit also includes a feedback and optimization module, wherein the feedback and optimization module is capable of self-learning and optimization to update the model and early warning algorithm.

7. The long-term, low-power, intelligent, continuous wearable body temperature monitoring and early warning device according to claim 6 is characterized by: The self-learning method is SVM, random forest or LSTM.

8. The long-term, low-power, intelligent, continuous wearable body temperature monitoring and early warning device according to claim 1 is characterized by: The flexible adhesive layer has two layers and is located on the front and back sides of the device body.

9. The long-term, low-power, intelligent, continuous wearable body temperature monitoring and early warning device according to claim 1 is characterized by: The material of the device body is a flexible gel material shell.

10. The long-term, low-power, intelligent, continuous wearable body temperature monitoring and early warning device according to claim 1 is characterized by: The signal release end is connected to the user terminal via wire or wirelessly.

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