Intelligent child health monitoring system and health care application thereof

Abstract

The invention discloses an intelligent child health monitoring system and health care application thereof, and particularly relates to the technical field of child health detection.The intelligent child health monitoring system comprises a wearable sensing unit which collects body temperature, heart rate, blood oxygen and motion data in real time; the parent mobile terminal receives the data and gives an alarm; the cloud service platform stores data and is internally provided with a child growth evaluation model and a pediatric knowledge base; the clinical health care application module is in butt joint with a hospital system, and growth curve analysis, vaccination reminding, allergen association and medication safety monitoring are achieved. The dynamic monitoring precision is improved through a motion artifact filtering algorithm, a growth percentile curve is generated based on a WHO standard, a medicine bar code is scanned to be matched with a weight dose library to verify medication safety, massage guidance animation is generated by integrating traditional Chinese medicine constitution identification, and compliance is improved in combination with a gamification interface. And a monitoring-evaluation-intervention closed-loop child health management system is formed.

Description

Technical Field

[0001] This invention relates to the field of children's health monitoring technology, and more specifically, to an intelligent children's health monitoring system and its health care applications. Background Technology

[0002] Currently, China's pediatric medical resources face severe challenges: statistics show that there are only 0.63 pediatricians for every 1,000 children, and waiting times at pediatric outpatient clinics in primary hospitals often exceed 3 hours. Furthermore, children's limited expressive abilities lead to a 34.7% inaccurate description rate of their symptoms (China Pediatric Resources White Paper 2023). Meanwhile, smart wearable devices are experiencing rapid growth in the consumer market, with annual shipments of children's smartwatches exceeding 20 million units. However, their health monitoring functions are mostly limited to basic heart rate monitoring, lacking clinical-grade data interpretation capabilities. Driven by the "Internet + Healthcare" policy, the Chinese Medical Association's Pediatrics Branch has clearly proposed the urgent need to build a three-tiered intelligent children's health management system linking families, communities, and hospitals, using technological means to alleviate the pressure on pediatric diagnosis and treatment and improve the efficiency of healthcare coverage. Existing technologies for monitoring children's health have significant shortcomings: Data fragmentation: Although mainstream wearable devices on the market (such as the Xiaotiancai Z9 watch) can monitor heart rate and steps, the data is stored in the manufacturer's private cloud and cannot be connected to the hospital information system. Pediatricians cannot obtain continuous physiological parameters to assist in diagnosis. Clinical disconnect: A certain brand of temperature patch (such as FeverScout) only provides fever alarms and does not integrate clinical knowledge bases such as WHO growth standards and immunization program timelines, which makes it impossible for parents to determine the priority of medical treatment after receiving the alarm; Lack of child-friendly design: Traditional PPG sensors have a false alarm rate of over 40% in children's motion scenarios (IEEE JBHI paper Vol.31), because their filtering algorithms are not optimized for high-frequency movements such as running and crying; Intervention gap: The existing vaccination reminder function of the app (such as Yuxueyuan) is not linked to the contraindication verification process, and the medication dosage recommendation still relies on manually entering weight, resulting in medication errors accounting for 28% of pediatric medical accidents (China Drug Surveillance 2024). Therefore, an intelligent children's health monitoring system and its health care applications are proposed to address the above issues. Summary of the Invention

[0003] In order to overcome the above-mentioned defects of the prior art, embodiments of the present invention provide an intelligent children's health monitoring system and its health care application to solve the problems mentioned in the background art.

[0004] To achieve the above objectives, the present invention provides the following technical solution: an intelligent children's health monitoring system, comprising: a wearable sensing unit that collects children's body temperature, heart rate, blood oxygen saturation, and motion acceleration data in real time; a parent's mobile terminal that receives and displays physiological parameters via Bluetooth or WiFi communication module and has an abnormal threshold alarm function; a cloud service platform that stores historical health data and has a built-in children's growth and development assessment model and pediatric clinical knowledge base; and a clinical healthcare application module that connects to the hospital's pediatric information system and outputs growth curve analysis, vaccination reminders, allergen association analysis, and medication safety monitoring functions; wherein the growth curve analysis automatically generates height and weight percentile curves based on WHO children's growth standards; the vaccination reminder pushes vaccination times and contraindication checklists based on the regional immunization program schedule; the allergen association analysis integrates environmental sensor data and symptom records to generate suspected allergen reports; and the medication safety monitoring alerts the risk of overdose by scanning drug barcodes and matching them with a children's weight and dosage database.

[0005] Preferably, the wearable sensing unit includes a flexible body temperature patch that uses a thermistor array to achieve multi-point temperature measurement on the body surface, a PPG optical sensor module that integrates a motion artifact filtering algorithm, and a detachable shell with a medical-grade anti-allergy silicone layer on its surface. The motion artifact filtering algorithm identifies the motion type through a triaxial accelerometer, separates noise frequency bands using adaptive weighted wavelet transform, and reconstructs a pure PPG signal based on an LSTM neural network.

[0006] Preferably, the cloud service platform includes a normalization processing module for correcting children's physiological parameters by age-segmented heart rate and blood oxygen baseline values, as well as a multi-source data fusion engine that correlates environmental temperature and humidity, PM2.5 concentration, and respiratory symptom records.

[0007] Preferably, the clinical healthcare application module further includes a nutrition assessment submodule and a developmental screening submodule. The nutrition assessment submodule generates a calcium, iron, and zinc deficiency risk index by recognizing dietary photos and comparing them with a nutrition database. The developmental screening submodule embeds the M-CHAT autism screening scale and triggers the abnormal behavior video recording function.

[0008] Preferably, the pediatric clinical knowledge base integrates a traditional Chinese medicine constitution identification model, generates constitution conditioning suggestions based on tongue coating image recognition and seasonal factors, and is associated with a massage acupoint animation guidance module.

[0009] Preferably, the parent's mobile terminal has a medical gamified interactive interface, which unlocks virtual rewards by completing health tasks, and integrates an AR module for alleviating children's medical fears, generating interactive comforting scenarios before vaccination.

[0010] A child health care method continuously collects physiological parameters through wearable sensing units. When the body temperature exceeds 37.8℃ for two consecutive hours or the blood oxygen saturation is below 95%, a pre-diagnosis report containing a symptom-disease probability matrix and tiered diagnosis and treatment suggestions is automatically generated and pushed to the parents and their contracted pediatricians. Based on the vaccination reminder unit, an appointment link is output and updated to the regional immunization program system simultaneously. Based on the medication safety monitoring unit, a QR code medication list with a drug dosage verification algorithm is generated for pharmacies to scan and verify. The symptom-disease probability matrix correlates the degree and duration of fever with common pediatric diseases, and the tiered diagnosis and treatment suggestions include a judgment logic that distinguishes between home observation, emergency, and outpatient priority.

[0011] A non-volatile storage medium storing a computer program, which, when executed by a processor, performs the following operations: continuously collecting data on a child's body temperature, heart rate, blood oxygen saturation, and acceleration of movement via a wearable sensing unit; triggering an abnormal alarm and generating a pre-diagnosis report containing a symptom-disease probability matrix and pushing it to the terminal when a body temperature is detected to be >37.8℃ for 2 consecutive hours or blood oxygen saturation is <95%; automatically generating a height and weight percentile curve based on WHO child growth standard data stored on a cloud service platform; calling the regional immunization program timeline to push vaccination reminders and contraindication checklists; outputting a suspected allergen report based on allergen association analysis results; performing medication safety verification by activating a child weight and dosage database by scanning drug barcodes; and outputting tongue coating analysis results and massage acupoint animation guidance resources based on a traditional Chinese medicine constitution identification model.

[0012] The technical effects and advantages of this invention are as follows: This invention achieves clinical-level vital sign monitoring of children under dynamic activity by leveraging the synergistic effect of a wearable sensor unit's multimodal physiological parameter acquisition module and an adaptive motion artifact filtering algorithm. It utilizes a child growth and development assessment model embedded in a cloud service platform to transform raw data into WHO standard growth percentile curves and generates an intelligent checklist of contraindications for vaccination by combining it with regional immunization program timelines, thus establishing a two-way interactive channel between family monitoring data and hospital pediatric information systems. The clinical healthcare application module activates a real-time matching mechanism for the child's weight and dosage database through barcode scanning, constructing a closed-loop intervention link from drug identification to safe medication verification. Simultaneously, it provides non-drug healthcare solutions based on a traditional Chinese medicine constitution identification model and an animated massage acupoint guidance module. The gamified medical interface and AR fear-relief function integrated into the parent's mobile terminal significantly improve the compliance and comfort of children's health management, ultimately forming a comprehensive intelligent children's health management system encompassing "monitoring-assessment-intervention-feedback." Attached Figure Description

[0013] Figure 1 This is a system hardware architecture diagram of the present invention.

[0014] Figure 2 This is a flowchart of the motion artifact filtering algorithm of the present invention.

[0015] Figure 3 This is a flowchart of the child health care method of the present invention.

[0016] Figure 4 This is a program execution chain diagram for the storage medium of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Example 1 As attached Figure 1-4 As shown: (1) An intelligent children's health monitoring system, including: a wearable sensing unit to collect children's body temperature, heart rate, blood oxygen saturation and exercise acceleration data in real time; a parent's mobile terminal to receive and display physiological parameters through Bluetooth or WiFi communication module and to have an abnormal threshold alarm function; a cloud service platform to store historical health data and to have a built-in children's growth and development assessment model and pediatric clinical knowledge base; a clinical health care application module to connect to the hospital's pediatric information system and output growth curve analysis, vaccination reminder, allergen association analysis and medication safety monitoring functions; wherein the growth curve analysis automatically generates height and weight percentile curves based on WHO children's growth standards; the vaccination reminder pushes the vaccination time and contraindication checklist in the relevant regional immunization program schedule; the allergen association analysis integrates environmental sensor data and symptom records to generate a suspected allergen report; and the medication safety monitoring... The system detects and alerts parents of children's overdose risks by scanning drug barcodes and matching them with a children's weight and dosage database. The intelligent children's health monitoring system continuously collects data on children's body temperature, heart rate, blood oxygen saturation, and acceleration via wearable sensors. This data is transmitted via Bluetooth / WiFi to parents' mobile devices for real-time display and triggers preset abnormal threshold alarms (e.g., a flashing red light if body temperature > 38℃). The cloud service platform stores historical data and uses the built-in WHO children's growth standard database to generate height and weight percentile curves. It also connects to the regional immunization program system to push vaccination schedules and electronic checklists for contraindications. The clinical healthcare application module integrates environmental sensor data (PM2.5 / temperature and humidity) and symptom data, generates suspected allergen reports using a Bayesian probability model, and automatically matches the children's weight and dosage database to generate a medication risk warning pop-up after scanning the drug barcode.

[0019] (2) The wearable sensing unit includes a flexible body temperature patch that uses a thermistor array to achieve multi-point temperature measurement on the body surface, a PPG optical sensor module that integrates a motion artifact filtering algorithm, and a detachable shell covered with a medical-grade anti-allergy silicone layer. The motion artifact filtering algorithm identifies the type of motion through a triaxial accelerometer, separates the noise frequency band using adaptive weighted wavelet transform, and reconstructs a clean PPG signal based on an LSTM neural network. The wearable sensing unit uses a 0.5mm thick flexible body temperature patch, and its thermistor array is distributed in a 0.5cm×0.5cm grid to achieve multi-point temperature measurement under the armpit / forehead. The PPG optical sensor embeds a motion artifact filtering algorithm. When the triaxial accelerometer detects running (>3m / s), the PPG optical sensor can detect the motion artifact filtering algorithm. 2 When the adaptive weighted wavelet transform is initiated, the noise frequency band of 0.5-5Hz is separated and then input into the pre-trained LSTM neural network (containing 128 hidden units) to reconstruct the PPG signal; the detachable shell is covered with a medical-grade anti-allergy silicone layer and can be repeatedly installed and used after being sterilized with ethylene oxide.

[0020] (3) The cloud service platform includes a normalization processing module for age-segmented correction of children's physiological parameters, specifically for heart rate and blood oxygen baseline values, and a multi-source data fusion engine that correlates environmental temperature and humidity, PM2.5 concentration, and respiratory symptom records. Specifically, the cloud service platform performs age-segmented correction on the received physiological parameters: the heart rate baseline for children aged 1-3 years is set to 90-150 bpm (blood oxygen > 94%), and for children aged 4-6 years, it is adjusted to 80-130 bpm (blood oxygen > 95%). The multi-source data fusion engine correlates temperature and humidity data and PM2.5 data collected by home IoT devices with records of cough / runny nose symptoms entered by parents. When PM2.5 > 75 μg / m³, the data is normalized. 3 Furthermore, if respiratory symptoms appear for three consecutive days, an "Indoor Air Quality Warning" will be generated and pushed to the mobile terminal.

[0021] (4) The clinical health care application module further includes a nutrition assessment submodule and a developmental screening submodule. The nutrition assessment submodule generates a calcium, iron and zinc deficiency risk index by recognizing dietary photos and comparing them with a nutrition database. The developmental screening submodule embeds the M-CHAT autism screening scale and triggers the abnormal behavior video recording function. The nutrition assessment submodule identifies the types of food in the dietary photos through the MobileNetV3 convolutional neural network, compares them with the Chinese Dietary Reference Intakes (DRIs) database, and calculates the difference between the actual intake of calcium, iron and zinc and the recommended intake to generate a deficiency risk index (e.g., calcium intake <300mg / day triggers an orange warning). The developmental screening submodule embeds a modified version of the M-CHAT autism screening scale. When the "abnormal eye contact" option is checked, the terminal camera automatically starts recording a 10-minute game interaction video for the doctor to review.

[0022] (5) The pediatric clinical knowledge base integrates a TCM constitution identification model, generates constitution conditioning suggestions based on tongue coating image recognition and seasonal factors, and associates them with a massage acupoint animation guidance module. After receiving the tongue coating image, the TCM constitution identification model of the pediatric clinical knowledge base: ① segments the tongue area through the HSV color space; ② extracts the characteristics of coating color (white / yellow / gray) and thickness (thin coating with a penetration rate of >70%); ③ outputs the constitution type (such as stagnation syndrome) in combination with seasonal factors (probability of damp-heat constitution in summer); the massage acupoint animation guidance module calls a three-dimensional human body model based on the constitution results, and dynamically demonstrates the circular kneading technique of Zusanli acupoint (located 3 cun below the patella) with a frequency prompt of 200 times / minute.

[0023] (6) The parent mobile terminal is equipped with a medical gamified interactive interface, which unlocks virtual rewards by completing health tasks and integrates a children's medical fear relief AR module to generate an interactive soothing scene before vaccination. The medical gamified interactive interface of the parent mobile terminal sets up a toothbrush challenge task: the toothbrush movement trajectory is monitored by the accelerometer, and a virtual badge is unlocked after completing 2 minutes of effective brushing. Before vaccination, the AR fear relief module is activated, which calls the device camera to overlay virtual animated characters (such as a talking panda), tracks the position of the child's arm through gesture recognition, and generates an ice-feeling special effect animation at the injection site to divert attention.

[0024] (7) A method for children's health care, which continuously collects physiological parameters through a wearable sensing unit. When the body temperature exceeds 37.8℃ for 2 consecutive hours or the blood oxygen saturation is below 95%, a pre-diagnosis report containing a symptom-disease probability matrix and a hierarchical diagnosis and treatment suggestion is automatically generated and pushed to the parents and the contracted pediatrician. According to the vaccination reminder unit, an appointment link is output and updated to the regional immunization planning system. Based on the medication safety monitoring unit, a QR code medication list with a drug dosage verification algorithm is generated for pharmacies to scan and verify. The symptom-disease probability matrix is ​​associated with the degree of fever, duration and common pediatric diseases. The hierarchical diagnosis and treatment suggestion includes the judgment logic of distinguishing between home observation, emergency and outpatient priority. The execution process of the children's health care method is as follows: 1) The sensing unit uploads body temperature data to the cloud platform every 5 minutes. When the temperature exceeds 37.8℃ for 2 consecutive hours, a pre-diagnosis report is generated; 2) The report contains a symptom-disease probability matrix (e.g., fever + sore throat → probability of streptococcal pharyngitis 68%) and a hierarchical diagnosis and treatment suggestion (outpatient priority level B); 3) The vaccination module calls the immunization program API to send a registration request containing the child's ID to the community hospital appointment system; 4) Medication safety monitoring generates a QR code list, and the pharmacy scans the code to activate the dosage verification algorithm (e.g., a single dose of ibuprofen for a 10kg child is <100mg).

[0025] (8) A non-volatile storage medium storing a computer program, wherein the program, when executed by a processor, performs the following operations: continuously collecting data on a child's body temperature, heart rate, blood oxygen saturation, and acceleration of movement through a wearable sensing unit; triggering an abnormal alarm and generating a pre-diagnosis report containing a symptom-disease probability matrix and pushing it to the terminal when a body temperature is detected to be >37.8℃ for 2 consecutive hours or blood oxygen saturation is <95%; automatically generating a height and weight percentile curve based on WHO child growth standard data stored on a cloud service platform; calling the regional immunization program timeline to push vaccination reminders and contraindication checklists; outputting a report of suspected allergens based on the results of allergen association analysis; performing medication safety verification by activating the child's weight and dosage database by scanning the drug barcode; and outputting tongue coating analysis results and massage acupoint animation guidance resources based on a traditional Chinese medicine constitution identification model. When the computer program stored in the embedded eMMC chip is executed by the processor, it acquires real-time data streams of body temperature, heart rate, and blood oxygen saturation collected by the wearable sensing unit via the Bluetooth 4.0 protocol stack. When the body temperature data is detected to be >37.8℃ for 24 consecutive sampling cycles (sampling interval of 5 minutes) or the blood oxygen saturation is <95%, the phone's vibration module and LED alarm protocol stack are immediately invoked to trigger a three-level red light flashing. Simultaneously, the WHO child growth standard table in the cloud platform's MySQL database is accessed, and height and weight percentiles are calculated by age (e.g., a 3-year-old child with a height of 92cm corresponds to the P50 percentile) and rendered as an SVG vector curve for output to the parent's terminal. The regional immunization program system API (taking the Shanghai immunization program system V2.3 interface as an example) is periodically polled to match the child's date of birth field. When the vaccination time window is reached (e.g., the second dose of MMR vaccine), the system will trigger the corresponding time frame. When the child is 18-24 months old, a push notification is generated containing an electronic checklist for contraindications (epilepsy history / antibiotic allergy checkboxes); after the drug's national drug approval number (format H + 8 digits) is entered into the barcode scanner, a real-time verification is performed by querying the child's weight field and dosage knowledge base (if the single dose of ibuprofen suspension is greater than the child's weight in kg × 10 mg, an "overdose risk" pop-up is returned); at the same time, the tongue coating image is segmented using the HSV color space of the OpenCV library (0-50 for hue H channel threshold determines white coating, 50-100 for yellow coating), and feature vectors with lightness L value > 70 and chroma b* value > 15 are extracted by LAB color gamut conversion, outputting the conclusion of "damp-heat constitution" and calling the Unity engine to generate a circular kneading animation of the three-dimensional coordinates (x=32.4, y=108.7, z=0) of the Zusanli acupoint (frequency 200 times / minute, pressure depth 1.2cm prompt).

[0026] Example 2: Early warning and intervention for respiratory infections (simulated based on a real-life intervention scenario of acute respiratory infection in a 3-year-old child) Step 1: Test Environment Data The patient (male, 3 years and 2 months old, weighing 15.2 kg) wore a smart monitoring bracelet in the morning, which activated the wearable sensor unit. Body temperature monitoring: A flexible patch under the armpit (0.5cm×0.5mm thermistor grid) uploads data every 5 minutes. From 9:00 to 11:00, the temperature was recorded as rising from 37.5℃ to 38.6℃ (>37.8℃ for 120 minutes). Cardiopulmonary function: The PPG sensor detected a heart rate of 142 bpm (exceeding the upper limit of 130 bpm for a 3-year-old), blood oxygen 93% (<95% threshold), and the accelerometer captured characteristic chest vibrations during coughing (3.2 Hz frequency, amplitude >0.4G). Environmental correlation: Home IoT synchronously transmits bedroom data (PM2.5 concentration 79μg / m³). 3 >75μg / m 3 Warning line, humidity 88% Step Two: A three-level alarm will pop up on the parent's mobile device in real time (flashing red light + continuous vibration). Clicking the alarm icon will trigger the following: 1. The cloud service platform performs multi-source analysis: It calls the age correction module to set the heart rate threshold to 90-130 bpm (currently 142 bpm = abnormal); the fusion engine correlates environmental data with symptom tags (parents select "cough" and "shortness of breath"); the growth curve module retrieves the WHO standard database and compares the height (96.5cm, P75 percentile) and weight (15.2kg, P60 percentile). 2. The clinical healthcare application module outputs a pre-diagnosis report: Symptom-disease matrix: Fever (38.6℃) + wet cough + high humidity environment → 81.3% probability of acute bronchitis (67.5% bacterial / 13.8% viral) Tiered medical care recommendations: Outpatient priority level A (requires treatment within 24 hours; based on historical data from the hospital's pediatric information system: similar cases that do not seek medical attention within 48 hours have a pneumonia conversion rate of 22%). Immediate intervention instructions: ① Set the bedroom air purifier to Level III (high-efficiency mode, PM2.5 < 35 μg / m³) 3 (Meets the standard); ② Water intake ≥ 200 ml / h; ③ Do not lie on your back (raise the head of the bed 30°). Step 3: At 11:15, the parent initiates a video consultation through the contracted doctor's portal on the terminal. The doctor retrieves: Allergen association report: Excluded highly allergenic foods recently (system records no shrimp or crab intake in the past 72 hours). Medication safety verification: Scan the barcode (National Drug Approval Number H20058921) of "Azithromycin Dry Suspension" in your home medicine cabinet. The dosage database matches your weight and returns: "Single dose limit 152mg - Prescription recommendation 150mg (safe)". Traditional Chinese Medicine Decision Support: Tongue coating image segmented by HSV (hue H=53 → yellow coating), LAB color gamut analysis (b*=18.7>15), outputting the conclusion of "damp-heat in the lung meridian", and pushing massage animation: finger kneading method at Tian Tu acupoint (suprasternal notch depression), pressure 0.8kgf, frequency 120 times / minute. Step 4: At 12:00, parents bring the electronic prescription to the community pharmacy, where the pharmacist scans the QR code to create a medication list. The system automatically verifies the prescription number by calling the regional drug database. Secondary dosage confirmation: After entering the child's weight as 15.2 kg, execute the following steps: if (150 mg ≤ 15.2 × 10 mg) → "Dosage Compliant" Medication reminder settings: Generate medication-taking game tasks by linking the device - play cartoon animal animations after the AR camera recognizes the medicine cup. Step 5: Treatment Effectiveness Tracking Six hours after taking the medication (17:00): body temperature dropped to 37.9℃, and blood oxygen saturation rose to 95%; The cloud platform updated the pre-diagnosis report: "The probability of bacterial bronchitis has risen to 89.2%, and it is recommended to have a follow-up visit tomorrow for sputum culture." Unlock the "Little Warrior Medal" in the gamified interface (by taking medicine on time 3 times in total).

[0027] Finally, the following points should be noted: First, in the description of this application, it should be noted that, unless otherwise specified and limited, the terms "installation", "connection", and "linkage" should be interpreted broadly, and can be mechanical or electrical connections, or internal connections between two components, or direct connections. "Up", "down", "left", "right", etc. are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may change. Secondly: The accompanying drawings of the embodiments disclosed in this invention only involve the structures involved in the embodiments disclosed in this invention. Other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of this invention can be combined with each other. In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An intelligent children's health monitoring system, characterized in that, include: Wearable sensing units collect real-time data on children's body temperature, heart rate, blood oxygen saturation, and acceleration. Parents' mobile terminals receive and display physiological parameters via Bluetooth or WiFi communication modules and have an abnormal threshold alarm function. The cloud service platform stores historical health data and has a built-in child growth and development assessment model and pediatric clinical knowledge base. The clinical healthcare application module connects to the hospital's pediatric information system and outputs growth curve analysis, vaccination reminders, allergen association analysis, and medication safety monitoring functions. Among them, the growth curve analysis automatically generates height and weight percentile curves based on WHO child growth standards; the vaccination reminders are linked to the regional immunization program schedule to push vaccination times and contraindication checklists; the allergen association analysis integrates environmental sensor data and symptom records to generate suspected allergen reports; and the medication safety monitoring uses scanning drug barcodes to match the child's weight and dosage database to warn of overdose risks.

2. The intelligent children's health monitoring system according to claim 1, characterized in that: The wearable sensing unit includes a flexible body temperature patch that uses a thermistor array to achieve multi-point temperature measurement on the body surface, a PPG optical sensor module that integrates a motion artifact filtering algorithm, and a detachable shell with a medical-grade anti-allergy silicone layer on its surface. The motion artifact filtering algorithm identifies the motion type through a triaxial accelerometer, separates the noise frequency band using adaptive weighted wavelet transform, and reconstructs a pure PPG signal based on an LSTM neural network.

3. The intelligent children's health monitoring system according to claim 1, characterized in that: The cloud service platform includes a normalization processing module that corrects children's physiological parameters by age and blood oxygen baseline values, as well as a multi-source data fusion engine that correlates environmental temperature and humidity, PM2.5 concentration, and respiratory symptom records.

4. The intelligent child health monitoring system according to claim 1, characterized in that: The clinical healthcare application module further includes a nutrition assessment submodule and a developmental screening submodule. The nutrition assessment submodule generates a calcium, iron, and zinc deficiency risk index by recognizing dietary photos and comparing them with a nutrition database. The developmental screening submodule embeds the M-CHAT autism screening scale and triggers the abnormal behavior video recording function.

5. The intelligent child health monitoring system according to claim 1, characterized in that: The pediatric clinical knowledge base integrates a traditional Chinese medicine constitution identification model, generates constitution conditioning suggestions based on tongue coating image recognition and seasonal factors, and is associated with a massage acupoint animation guidance module.

6. The intelligent child health monitoring system according to claim 1, characterized in that: The parent's mobile terminal features a gamified medical interface that unlocks virtual rewards by completing health tasks and integrates an AR module to alleviate children's medical fears, generating interactive reassurance scenarios before vaccination.

7. A method for children's health care based on the system of any one of claims 1-6, characterized in that: Wearable sensing units continuously collect physiological parameters. When body temperature exceeds 37.8℃ for two consecutive hours or blood oxygen saturation is below 95%, a pre-diagnosis report containing a symptom-disease probability matrix and tiered diagnosis and treatment suggestions is automatically generated and pushed to parents and their contracted pediatricians. The vaccination reminder unit outputs an appointment link and updates it to the regional immunization program system simultaneously. Based on the medication safety monitoring unit, a QR code medication list with a drug dosage verification algorithm is generated for pharmacies to scan and verify. The symptom-disease probability matrix is ​​associated with the degree and duration of fever and common pediatric diseases, and the tiered diagnosis and treatment suggestions include a judgment logic that distinguishes between home observation, emergency and outpatient priorities.

8. A non-volatile storage medium storing a computer program, characterized in that, When the program is executed by the processor, it performs the following operations: continuously collects data on the child's body temperature, heart rate, blood oxygen saturation, and acceleration through the wearable sensing unit; when the body temperature is detected to be >37.8℃ for 2 consecutive hours or the blood oxygen saturation is <95%, an abnormal alarm is triggered and a pre-diagnosis report containing a symptom-disease probability matrix is ​​generated and pushed to the terminal. The height and weight percentile curves are automatically generated based on WHO child growth standard data stored on the cloud service platform. The system can push vaccination reminders and contraindication checklists by calling the regional immunization program schedule; output suspected allergen reports based on allergen association analysis results; perform medication safety verification by activating the children's weight and dosage database by scanning drug barcodes; and output tongue coating analysis results and massage acupoint animation guidance resources based on the traditional Chinese medicine constitution identification model.

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