Wearable body temperature monitoring and early warning system based on flexible attachment

Abstract

The invention discloses a wearable body temperature monitoring and early warning system based on flexible attachment. The wearable body temperature monitoring and early warning system comprises a monitoring body, a temperature sensor, an information processor, a flexible attachment layer and a power source. On one hand, the temperature measuring face based on the temperature sensor can synchronously deform along with the flexible attaching 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 particularly relates to a wearable body temperature monitoring and warning system based on flexible attachment. Background Art

[0002] The health status of infants and young children is an important concern in family parenting, and body temperature is one of the key indicators for evaluating the health of infants and young children. Since the immune system is not yet fully mature and the body temperature regulation ability is poor, changes in body temperature may indicate changes in health status. Therefore, it is crucial for parents and guardians to monitor the body temperature changes of infants and young children in a timely manner. The body temperature of infants and young children is sensitive to changes and easily affected by the environment. Minor fluctuations in body temperature may indicate potential health risks, such as colds, infections, fevers, etc.

[0003] Currently, the mainstream body temperature monitoring technologies for infants and young children in the industry mainly include traditional mercury thermometers, smart bracelets, ear thermometers, and infrared thermometers. However, there are still some problems in the process of use. Among them, when using a traditional mercury thermometer to measure body temperature, it is necessary to cooperate with clamping the thermometer, which is often difficult to operate when the infant or young child does not cooperate with the body temperature measurement and real-time monitoring cannot be achieved; most temperature measurement devices such as smart bracelets are designed for adults and do not meet the physiological characteristics of infants and young children. Due to the limitation of the measurement site, the temperature measurement accuracy is relatively low, and the wearing comfort and battery life also need to be improved; the operation of an ear thermometer is complex, and improper operation will lead to measurement errors. Especially when the cooperation of infants and young children is low, 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 the infrared thermometer is non-contact, the measurement accuracy is greatly affected by the environment, and it also lacks the function of recording the trend of body temperature changes. Therefore, traditional body temperature measurement tools (such as mercury thermometers and electronic thermometers) require manual operation and can only obtain body temperature values during single measurements, which cannot meet the needs of long-term, continuous, wearable monitoring and real-time warning. In addition, infants and young children often increase the measurement difficulty due to non-cooperation or discomfort, further reducing the practicality of traditional measurement methods.

[0004] Meanwhile, with the development of wearable intelligent devices, some intelligent body temperature devices for health monitoring have emerged on the market. For example: CN113273971B, a wearable intelligent body temperature monitoring device; CN110558953A, a wearable wireless intelligent temperature recorder. The functions of both are simple temperature monitoring and early warning. Moreover, due to poor battery life, they cannot perform long-term continuous monitoring. At the same time, the former uses an infrared temperature sensor. In terms of wearing methods, it is mainly in the form of necklace hanging cords and waistbands. The temperature measurement accuracy is insufficient, and the temperature measurement site does not have a unified medical reference standard. In addition, the device is relatively large in size, and the foreign body sensation brought by the wearing method is strong, which is not suitable for long-term body temperature monitoring of infants and young children; the latter still uses an infrared temperature sensor. Although the overall volume of the device is smaller than the former, the wristband wearing method is not suitable for long-term wearing by infants and young children, and it is greatly affected by environmental changes and activities. There are still deficiencies in the temperature measurement site and accuracy, and it also cannot meet the scientific monitoring of the body temperature of infants and young children. Therefore, most devices have high power consumption. Limited by the size of the device, the battery life is often poor, and the long-term monitoring requirement cannot be achieved; most wearable devices use infrared temperature sensors, and the temperature measurement accuracy of the temperature sensor is insufficient, and it cannot effectively capture subtle body temperature changes; at the same time, existing devices usually only have the function of conventional high-temperature alarms and cannot provide accurate and intelligent disease early warnings according to the speed or trend of body temperature changes (such as diseases with typical periodic body temperature change rules like influenza).

[0005] In summary, the existing infant temperature monitoring technologies mainly rely on traditional thermometers, such as ear thermometers, axillary thermometers, and oral thermometers. Although these devices can accurately measure body temperature, they require physical contact for a certain period of time and cannot provide real-time monitoring of body temperature changes, thus failing to help parents understand the body temperature health status of infants in real time or over a long term. Although some intelligent temperature monitoring devices have gradually emerged on the market in recent years, such as temperature monitoring patches and intelligent thermometers, some of these devices can transmit body temperature data to a mobile phone via Bluetooth or Wi-Fi and display and record it in real time through an App. However, these devices often have inaccurate temperature sensors, especially in complex environments (such as when infants are more active), which may lead to deviations in body temperature data; the sensors and communication modules used have high power consumption, affecting the long-term continuous wearable monitoring of the devices; and some existing devices have an imperfect alarm mechanism, with only a simple body temperature alarm function and unable to 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 technologies are mostly passive diagnostic methods, often carried out after obvious symptoms appear, missing the best opportunity for early intervention. The detection technologies also mostly rely on methods such as blood tests and kit detections, usually with high costs, complex processes, and the need for the participation of medical institutions, prolonging the diagnosis time, and detection methods such as blood tests and throat swab samplings usually cause fear and discomfort in infants, increasing the detection difficulty. 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 flexible attachment-based wearable body temperature monitoring and warning system.

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

[0008] A flexible attachment-based wearable body temperature monitoring and warning system, which includes a monitoring body, a temperature sensor, an information processor, a flexible attachment layer, and a power source. The flexible attachment layer is attached to the temperature measurement surface of the temperature sensor and is in direct contact with the skin. The information processor includes an information receiving end connected to the temperature sensor, a data processing unit, and a signal releasing end. In particular, the temperature measurement surface of the temperature sensor can deform synchronously with the flexible attachment layer to fit the skin curve of the armpit or forehead, where the skin curve is composed of multiple different planar points and different points are selected based on different users to obtain the skin curve; the data processing unit includes a data preprocessing module, a feature extraction module, a curve matching module, an analysis and prediction module, and a warning and notification module. 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 and calculate the matching degree, and the algorithm and processing steps are as follows:

[0009] 1) Construct a 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 among its three possible predecessor positions: C[i - 1][j], from above; C[i][j - 1], from the left; C[i - 1][j - 1], from the upper left;

[0011] 3) Path backtracking. Start from the last element of the cumulative cost matrix and trace back inversely to find the minimum cumulative cost path;

[0012] 4) Result interpretation. The finally obtained path represents the best 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; the larger the distance, the greater the difference. And if the matching degree is higher than the set threshold or the body temperature change rate is abnormal, the signal sending end sends 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 sequences are different in time or speed, one time series is stretched or compressed to align it with the other time series to obtain the minimum distance path between them. That is, in this application, the sequence is the temperature change curve over time, i.e., the temperature time series, between different individuals, 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 is collected 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 can more data be obtained, but also the body temperature change rate can be obtained more accurately, which is more conducive to model establishment. Specifically, some or all of the multiple temperature measurement points work to obtain temperature information, that is, the skin curve is composed of multiple different plane points, and different points are selected based on different users to obtain the skin curve.

[0015] Preferably, preprocessing is performed based on the collected body temperature. The data preprocessing module uses a filtering algorithm to eliminate noise and simultaneously detects and corrects abnormal data. For example: temperature values exceeding the physical limit can be removed to improve the modeling accuracy.

[0016] According to yet another specific implementation and preferred aspect of the present invention, the key features extracted by the feature extraction module include the temperature change trend, the temperature change rate, and whether it exceeds the 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 the warning algorithm. Learn and optimize historical data, continuously update the model and the warning algorithm, and 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 yet another specific implementation and preferred aspect of the present invention, the flexible attachment layer has two layers and is located on the front and back of the monitoring body. When used under the armpit, it fits the skin more stably to avoid loosening or falling off caused by the movement of infants.

[0020] In addition, the signal release end is connected to the user terminal through wired or wireless means. The material of the monitoring body is a flexible gel material shell. It has a weak foreign body sensation when worn, is suitable for long-term wear by infants, can be directly attached to the armpit of infants for long-term and continuous body temperature monitoring, and will not affect their daily behaviors.

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

[0022] Existing infant temperature monitoring technologies mainly rely on traditional thermometers, such as ear thermometers, axillary thermometers, and oral thermometers. Although these devices can accurately measure body temperature, they require physical contact for a certain period of time and cannot provide real-time monitoring of body temperature changes, making it impossible for parents to understand the body temperature health status of infants in real time or over a long period. Although in recent years, some intelligent temperature monitoring devices have gradually emerged on the market, such as temperature monitoring patches and intelligent thermometers. Some devices can transmit body temperature data to mobile phones via Bluetooth or Wi-Fi and display and record it in real time through an App. However, these devices often have inaccurate temperature sensors, especially in complex environments (such as when infants are more active), which may lead to deviations in body temperature data; the sensors and communication modules used have high power consumption, affecting the long-term continuous wear monitoring of the device; and some existing devices have an imperfect alarm mechanism, with only a simple body temperature alarm function and unable to 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, often carried out after obvious symptoms appear, missing the best opportunity for early intervention.Detection technologies also mostly rely on methods such as blood tests and kit detections. Usually, they are costly, have complex processes, and require the participation of medical institutions, which prolongs the diagnosis time. Moreover, detection methods such as blood tests and throat swab samplings usually cause fear and discomfort in infants and young children, increasing the detection difficulty, etc. However, the present invention conducts an overall design on the structure of the body temperature monitoring and warning device, cleverly solving various deficiencies of the existing structure. After adopting this body temperature monitoring and warning device, first, the entire device is attached to the armpit or forehead through the flexible attachment layer, so that the temperature measurement surface fits the skin in the same shape; then, the signal release end built into the device is paired with a pre-bound mobile terminal (such as a mobile phone), and the device enters the working state and starts monitoring body temperature data; finally, based on the real-time collected body temperature information, noise reduction processing is performed to extract the required features, and then curve matching calculations are performed based on the extracted features. The finally obtained path represents the best alignment method of the two temperature time series, and the sum of all costs on the path is the distance between the two series. The smaller the distance, the higher the similarity; the larger the distance, the greater the difference. And when the matching degree is higher than the set threshold or the body temperature change rate is abnormal, the signal release end sends a warning signal to the user terminal. Therefore, on the one hand, based on the temperature measurement surface of the temperature sensor, it can deform synchronously with the flexible attachment layer to fit the armpit or forehead skin curve, accurately and timely 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 treatment suggestions to the guardian based on the algorithm analysis of the monitored body temperature data, providing intelligent early warning so that the guardian can take corresponding measures in time; on the other hand, the device is small in size, uses a flexible gel material shell, has a weak foreign body sensation when worn, is suitable for long-term wearing by infants and young children, can be directly attached to the armpit of infants and young children for long-term and continuous body temperature monitoring, will not affect their daily behaviors, and effectively helps parents and caregivers better understand the health status of infants and young children, providing intelligent and efficient parenting assistance functions. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0024] Figure 2 is Figure 1 a wearing schematic diagram of

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

[0026] Figure 4 It is an algorithm logic schematic diagram in the present invention;

[0027] Wherein: 1. Monitoring body; 2. Temperature sensor; 3. Information processor; 30. Information receiving end; 31. Data processing unit; 32. Signal releasing end; 4. Flexible attachment layer; 5. Power supply (battery or electronics); 6. User terminal. Specific embodiments

[0028] To make the above objects, features, and advantages of the present invention more obvious and understandable, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. Many specific details are set forth in the following description in order to fully understand 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 departing from the connotation of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed below.

[0029] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc. indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings. These are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of the present invention.

[0030] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include at least one of these features. In the description of the present invention, "a plurality" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0031] In the present invention, unless otherwise clearly specified and defined, the terms "mounted", "connected", "connected", "fixed", etc. should be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or integrated; it may be directly connected, or indirectly connected through an intermediate medium. It may be the internal communication of two elements or the interaction relationship between two elements, unless otherwise clearly defined. For those of ordinary skill in the art, 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 or limited, the first feature being "on" or "under" the second feature may mean that the first and second features are in direct contact, or the first and second features are indirectly in contact through an intermediate medium. Moreover, the first feature being "above", "over" and "on top of" the second feature may mean that the first feature is directly above or obliquely above the second feature, or merely indicates that the horizontal height of the first feature is higher than that of the second feature. The first feature being "under", "beneath" and "underneath" the second feature may mean that the first feature is directly below or obliquely below the second feature, or merely indicates that the horizontal height of the first feature is lower than that of 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 can be directly on the other element or there may also be an intermediate element. When an element is considered to be "connected to" another element, it can be directly connected to the other element or there may be an intermediate element at the same time. The terms "vertical", "horizontal", "upper", "lower", "left", "right" and similar expressions used herein are only for the purpose of illustration and do not represent the only implementation.

[0034] As Figures 1 to 4 shown, the wearable body temperature monitoring and warning system based on flexible attachment according to this embodiment includes a monitoring body 1, a temperature sensor 2, an information processor 3, a flexible attachment layer 4, a power supply 5, and a user terminal 6. The flexible attachment layer 4 is attached to the temperature measurement surface of the temperature sensor 2 (i.e., arranged on the front of the monitoring body 1). The power supply 5 is electrically connected to the temperature sensor 2 and the information processor 3 respectively, and the flexible attachment layer 4 is also arranged on the back of the monitoring body 1. The temperature measurement surface of the temperature sensor 2 can deform synchronously with the flexible attachment layer 4 to conform to the skin curve of the armpit or forehead, where the skin curve is composed of multiple different plane points and different points are selected based on different users to obtain the skin curve.

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

[0036] In some specific embodiments, data is collected 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 can more data be obtained, but also the rate of change of body temperature can be obtained more accurately, which is more conducive to model establishment. Based on the collected body temperature, preprocessing is performed. The data preprocessing module uses a filtering algorithm to eliminate noise and simultaneously detects and corrects abnormal data. For example, temperature values exceeding physical limits can be removed to improve the accuracy of modeling. The key features extracted by the feature extraction module include the trend of temperature change, the rate of temperature change, and whether the set threshold is exceeded. Based on the mutual verification 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 warning algorithm. Learn from and optimize historical data, continuously update the model and warning algorithm, and improve prediction accuracy and robustness. 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.

[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, calculate the matching degree, and the algorithm and processing steps are as follows:

[0038] 1) Construct a 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 among its three possible predecessor positions: C[i - 1][j], from above; C[i][j - 1], from the left; C[i - 1][j - 1], from the upper left;

[0040] 3) Path backtracking. Start from the last element of the cumulative cost matrix and trace back in reverse to find the path with the minimum cumulative cost;

[0041] 4) Result interpretation. The finally obtained path represents the best alignment method of the two temperature time series, and the sum of all costs on the path is the distance between the two series. The smaller the distance, the higher the similarity; the larger the distance, the greater the difference. And if the matching degree is higher than the set threshold or the rate of change of body temperature is abnormal, the signal release end sends 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 the other time series to obtain the minimum distance path between them. That is, in this application, the sequence is the temperature-time curve of different individuals over time, i.e., the temperature time series, and the minimum distance path serves as the similarity criterion. In addition, the signal release end is connected to the user terminal via wire or wirelessly. The material of the monitoring body is a flexible gel material shell. It has a weak foreign body sensation when worn, is suitable for long-term wear by infants and young children, can be directly attached to the armpits of infants and young children for long-term and continuous body temperature monitoring, and will not affect their daily behaviors.

[0043] In short, the body temperature monitoring and warning device of this application consists of the following main modules: a temperature sensor, a signal integration and processing module, a Bluetooth module, a battery power supply module, and a mobile terminal. Each module is interconnected through a circuit board and a communication interface to form a complete temperature monitoring and warning system. To meet the special requirements of infant body temperature monitoring, it provides accurate body temperature monitoring, influenza prediction, real-time alarm functions, personalized treatment suggestions, and adopts a low-power and comfortable design, greatly improving the effectiveness and convenience of infant health monitoring. Temperature sensor: Installed on the skin-contact part of the device, it makes full contact with the skin under the armpits of infants and young children to ensure the accuracy of temperature monitoring and collect the temperature data under the armpits of infants and young children. At the same time, some or all of the multiple temperature measurement points work to obtain temperature information, that is, the skin curve is composed of multiple different plane points, and different points are selected based on different users to obtain this skin curve. The analog or digital signals collected are 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. It processes the signals transmitted by the temperature sensor, 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 result is transmitted to the Bluetooth module. Low-power Bluetooth module: Integrated with the signal processor module on the same circuit board, it receives the temperature data from the signal integration processor and is responsible for wirelessly transmitting the processed temperature data to the mobile terminal. Battery module: Optimized to support long-term wearable operation of the device, it provides stable power supply to each module through a power line for the system, supporting the operation of the temperature sensor, signal integration processor, and Bluetooth module. Mobile terminal: Such as smartphones, tablets, etc., receive the temperature data transmitted by the device via Bluetooth, display, analyze, and alarm process it on the supporting App. At the same time, based on the data analysis results and combined with the large database of typical body temperature changes in influenza, it compares the body temperature data to identify potential disease risks and provides scientific treatment suggestions to help parents achieve early detection and intervention of diseases.

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

[0045] First, fix the temperature sensor to the armpit where the temperature needs to be measured by sticking, ensuring that the curved surface of the sensor is in close contact with the skin; then, automatically pair with a pre-bound mobile terminal (such as a mobile phone) through the built-in low-power Bluetooth module of the device. The device enters the working state and starts monitoring body temperature data. The high-precision temperature sensor collects the armpit temperature of the infant 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 once every 5 seconds by default (the sampling rate can be adjusted according to requirements); the signal integrated circuit board receives the temperature data from the temperature sensor, filters and denoises the signal, and the processed temperature data 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 rate of temperature change is too fast (detecting a rapid warming trend), and by comparing the trend of the infant's body temperature data recorded during the fever cycle with the typical body temperature change curve stored for influenza virus infection, to judge the matching degree between the infant's body temperature change and the influenza pattern, for realizing early warning of diseases such as influenza in infants. If the temperature or the trend of body temperature data changes abnormally, the alarm mechanism will be triggered, and different handling suggestions will be provided according to different situations, reminding parents to take corresponding measures. For example, if the body temperature is between 37.5°C and 38°C, it is recommended to take physical cooling measures (such as reducing clothes, local cold compress). If the body temperature exceeds 38°C, it is prompted to seek medical attention immediately. If the trend of body temperature change highly matches the influenza pattern, it will be prompted to closely observe, conduct a rapid influenza test, and seek medical attention in a timely manner. When the temperature data is normal, continuous monitoring is carried out, and the user can view the current body temperature data at any time. All the collected temperature data will be stored in the mobile phone application for easy viewing of historical data and the trend of body temperature change. The data can generate reports by day, week, and month for users to refer to or for doctors to diagnose. 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 the next use.

[0046] Therefore, the present invention aims to address the deficiencies in the prior art and provide an intelligent, long-term, and continuous temperature monitoring device that can accurately monitor the body temperature changes of infants and toddlers, send alarms to guardians in a timely manner, and provide corresponding treatment suggestions. The device is small in size and uses a flexible gel material shell, with a weak foreign body sensation when worn, suitable for long-term wear by infants and toddlers. It can be directly attached to the armpit of infants and toddlers for long-term and continuous body temperature monitoring without affecting their daily behaviors. When the body temperature is abnormal, the device will not only send alarm information to the guardians, but also provide scientific treatment suggestions to the guardians by analyzing the monitored body temperature data through algorithms, and provide intelligent influenza warnings so that the guardians can take corresponding measures in a timely manner. The device will provide long-term, continuous, and wearable body temperature monitoring, effectively helping parents and caregivers better understand the health status of infants and toddlers and providing 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 the influenza model and warning algorithm, improve the prediction accuracy and robustness, and 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 has described the present invention in detail. The purpose is to enable those skilled in this field of technology to understand the content of the present invention and implement it. However, this should not limit the protection scope of the present invention. Any equivalent changes or modifications made according to the spirit and essence of the present invention should be covered within the protection scope of the present invention.

Claims

1. A wearable body temperature monitoring and early warning system based on flexible attachment, comprising a monitoring body, a temperature sensor, an information processor, a flexible attachment layer, and a power supply, wherein the flexible attachment layer is attached to the temperature measuring surface of the temperature sensor and directly contacts the skin, and the information processor comprises 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 attachment layer to fit the skin curve of the armpit or forehead, wherein the skin curve is composed of a plurality of different plane points, and different points are selected based on different users to obtain the skin curve; 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 temperature change curve between different individuals over time is the temperature time series, and the minimum distance path is used as the similarity criterion. The smaller the distance, the higher the similarity, the larger the distance, the greater the difference, and the matching degree is higher than the set threshold or the temperature change rate is abnormal, and the signal release end sends a warning signal to the user terminal.

2. The wearable body temperature monitoring and early warning system based on flexible attachment according to claim 1 is characterized in that: 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 wearable body temperature monitoring and early warning system based on flexible attachment according to claim 1 is characterized in that: Data collection is performed in real time based on the information receiving end, and the temperature measuring surface has a plurality of temperature measuring points, wherein some or all of the plurality of temperature measuring points work to obtain temperature information.

4. The wearable body temperature monitoring and early warning system based on flexible attachment according to claim 3 is characterized in that: 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 wearable body temperature monitoring and early warning system based on flexible attachment according to claim 1 is characterized in that: 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 wearable body temperature monitoring and early warning system based on flexible attachment according to claim 1 is characterized in that: 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 wearable body temperature monitoring and early warning system based on flexible attachment according to claim 6 is characterized in that: The self-learning method is SVM, random forest or LSTM.

8. The wearable body temperature monitoring and early warning system based on flexible attachment according to claim 1 is characterized in that: The flexible attachment layer has two layers and is located on the front and back sides of the monitoring body.

9. The wearable body temperature monitoring and early warning system based on flexible attachment according to claim 1 is characterized in that: The monitoring body is made of a flexible gel shell.

10. The wearable body temperature monitoring and early warning system based on flexible attachment according to claim 1 is characterized in that: The signal release end is connected to the user terminal via wire or wirelessly.

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