Small desktop type intelligent health monitoring equipment

Abstract

The invention provides a small desktop type intelligent health monitoring device, which comprises a core hardware architecture, and is characterized in that the core hardware architecture comprises a base, a main body cabinet body and a mirror surface area arranged on the front surface of the main body cabinet body; the plurality of health monitoring modules are used for collecting multi-dimensional health index data of the user; the identity verification and data security module is used for user identity verification and encryption of collected health data, and comprises a multi-mode verification unit and a national secret encryption unit; and the intelligent health management system is used for processing and analyzing the encrypted health data. The problem of function fragmentation of existing equipment is solved, integrated collection of multi-dimensional health indexes such as blood pressure, blood sugar, heart rate / blood oxygen, respiratory rate, skin moisture / oil content and tongue pictures is achieved, and the equipment is adaptive to a small desktop scene; meanwhile, the problem that the health management function is weak is solved, the functions of health scheme generation, trend prediction, health science popularization and emotion connection are newly added, and a closed loop of collection-analysis-management-care is formed.

Description

Technical Field

[0001] This invention relates to the field of health monitoring technology, and more specifically, to a small desktop intelligent health monitoring device. Background Technology

[0002] Smart mirror products: such as smart makeup mirrors, mostly use brightness adjustment and high-definition light source technology to display realistic skin details, but lack health management functions; Home health monitoring devices: such as the Omron home blood pressure monitor (model HEM-7136), only support single blood pressure measurement, use the oscillometric method, require manual data recording, cannot be linked with other health indicators for analysis, lack AI analysis, health education and other professional health functions, and data transmission mostly uses ordinary encryption, which is not secure enough; Health management APP devices: although some health management APPs support data recording, they require manual input or binding to a single device, and lack integrated hardware data collection functions; Smart bracelet devices can only store basic exercise data, lack medical-grade health indicator (blood pressure, blood sugar) measurement functions, and have rudimentary health management functions, lacking emotional connection and professional consultation modules.

[0003] In existing technologies, during the use of health monitoring: (i) Existing devices are mostly single-function (such as measuring blood pressure only or serving as a dressing mirror only). Users need to use multiple devices and multiple apps to complete the "collection-analysis-management" process, which is cumbersome and the data cannot be linked. (ii) Existing equipment data transmission mostly uses non-national cryptographic encryption algorithms such as AES and SSL, which do not comply with domestic data security standards and pose a risk of privacy leakage; (iii) Weak health management functions: It can only store basic data and lacks functions such as personalized health plan generation, long-term trend prediction, health popularization and emotional care (such as psychological counseling for users with chronic diseases); Therefore, we have made improvements to this and proposed a small desktop intelligent health monitoring device. Summary of the Invention

[0004] The purpose of this invention is to address the problems of fragmented functions and weak health management capabilities in current health monitoring devices.

[0005] To achieve the above-mentioned objectives, the present invention provides the following technical solution: Small, desktop smart health monitoring devices to improve the above problems.

[0006] The application is as follows: Small desktop smart health monitoring devices, including: The core hardware architecture includes a base, a main cabinet, and a mirrored area on the front of the main cabinet. The mirrored area is tilted and integrates a fingertip placement area, a blood glucose test strip detection area, and an interactive module below it. Multiple health monitoring modules are integrated on the core hardware architecture to collect multi-dimensional health indicator data of users. The health monitoring modules include at least a blood pressure measurement module, a blood glucose measurement module, a heart rate and blood oxygen measurement module, a skin moisture and oil measurement module, and an AI magic mirror module. The AI ​​magic mirror module includes at least a camera and a dynamic light source component. The authentication and data security module is used for user authentication and encryption of collected health data. It includes a multimodal authentication unit and a national cryptographic encryption unit. The intelligent health management system is used to process and analyze encrypted health data. It includes a data recording unit, a health plan generation unit, a health trend prediction unit, a health science popularization unit, and an emotional connection unit. Among them, the data collected by multiple health monitoring modules are encrypted by the identity verification and data security modules before being transmitted to the intelligent health management system for processing, forming a closed loop of health management from data collection, analysis, management to care.

[0007] As a preferred technical solution in this application, the main cabinet has a layered structure, including: The upper monitoring module area is used to store the cuff of the blood pressure measurement module and the lancing device of the blood glucose measurement module. The middle-layer verification module area is used to set up authentication and data security modules; The lower extension drawer is used to store user-supplied health monitoring supplies.

[0008] As a preferred technical solution of this application, the dynamic light source component includes multiple sets of high color rendering index LED beads, an ambient light sensor, and a driving module; the dynamic light source component is activated only when performing facial recognition or AI face diagnosis through a camera, and dynamically adjusts the lighting brightness and color temperature according to the detection results of the ambient light sensor.

[0009] As a preferred technical solution of this application, in the identity verification and data security module, the national cryptographic encryption unit uses the SM2 asymmetric encryption algorithm to encrypt the transmitted data and the SM4 symmetric encryption algorithm to encrypt the stored data.

[0010] As a preferred technical solution of this application, the health plan generation unit is configured to automatically generate a personalized health improvement plan based on the user's identity information determined through identity verification and their historical health data.

[0011] As a preferred technical solution of this application, the health trend prediction unit adopts an LSTM neural network model to predict the user's future health trend based on the user's historical health data.

[0012] As a preferred technical solution in this application, the authentication and data security module supports the creation of independent encrypted data partitions for multiple users, thereby achieving isolation and management of multi-user data.

[0013] As a preferred technical solution of this application, the emotional connection unit is configured to: provide AI-generated emotional feedback information based on the user's health data and monitoring behavior, and support family members to send messages to the device through associated applications.

[0014] As a preferred technical solution of this application, the device supports connection to external devices or cloud servers via Bluetooth or Wi-Fi.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: In the scheme of this application: 1. The device occupies only 1 / 4 of a normal desktop space, making it suitable for high-frequency home scenarios such as dressing tables and bedside tables. It integrates common health management modules to solve the problem of fragmented management of existing devices. 2. Adopting the SM2 / SM4 national standard encryption algorithm improves network data security supervision and reduces the risk of privacy leakage by more than 90%; 3. Extending from "data collection" to "solution generation - trend prediction - health education - emotional care", it covers the user's needs throughout the entire health cycle, and is especially suitable for long-term management of chronic diseases; 4. Supports multiple users to manage data in separate zones. Children, adults, and the elderly all have their own exclusive health thresholds and plans, completely solving the problem of data confusion. Attached Figure Description

[0016] Figure 1 A schematic diagram of the overall structure of the small desktop intelligent health monitoring device provided in this application; Figure 2 A structural diagram of the intelligent health management system APP for the small desktop intelligent health monitoring device provided in this application; Figure 3 A schematic diagram of the AI ​​Magic Mirror touchscreen interaction for the small desktop intelligent health monitoring device provided in this application; Figure 4 A diagram of the security verification interface for the small desktop intelligent health monitoring device provided in this application; Figure 5 A screenshot of the indicator acquisition homepage interface of the small desktop intelligent health monitoring device provided in this application; Figure 6A flowchart illustrating the health management logic of the small desktop intelligent health monitoring device provided in this application; Figure 7 A flowchart illustrating the personalized solution for the small desktop intelligent health monitoring device provided in this application.

[0017] The image shows: 1. Base; 2. Main cabinet; 21. Upper monitoring module area; 22. Middle verification module area; 23. Lower extension drawer; 3. Mirror area; 31. AI Magic Mirror module; 311. Camera; 312. Dynamic light source component; 4. Fingertip placement area; 5. Blood glucose test strip detection area; 6. Interactive module. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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.

[0019] Therefore, the following detailed description of the embodiments of the present invention is not intended to limit the scope of the claimed invention, but merely to illustrate some embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention. It should be noted that, unless otherwise specified, the embodiments, features, and technical solutions in the embodiments of the present invention can be combined with each other.

[0020] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0021] like Figure 1-7 As shown, this embodiment proposes a small desktop intelligent health monitoring device, including: The core hardware architecture includes a base 1, a main cabinet 2, and a mirror area 3 set on the front of the main cabinet 2. The mirror area 3 is set at an angle, and a fingertip placement area 4, a blood glucose test strip detection area 5, and an interactive module 6 are integrated below it. Specifically, the base 1 is made of ABS engineering plastic injection molding, with four round silicone anti-slip pads (friction coefficient ≥0.8) evenly pasted on the bottom. The pads are placed at the four corners of the base 1 to ensure that the device does not slide when placed on a dressing table or bedside table. The pressure sensor mounting position (adapted to the body fat sensor module) is reserved in the center of the interior of the base 1, and the power management module storage slot is reserved on the right side (for placing a 12V / 2A power adapter and battery compartment). A 1cm diameter cable hole is opened on the side of the slot for the power cord to be connected to the central processing unit.

[0022] Multiple health monitoring modules are integrated on the core hardware architecture to collect multi-dimensional health indicator data of users. The health monitoring modules include at least a blood pressure measurement module, a blood glucose measurement module, a heart rate and blood oxygen measurement module, a skin moisture and oil measurement module, and an AI magic mirror module 31. The AI ​​magic mirror module 31 includes at least a camera 311 and a dynamic light source component 312. The authentication and data security module is used for user authentication and encryption of collected health data. It includes a multimodal authentication unit and a national cryptographic encryption unit. The intelligent health management system is used to process and analyze encrypted health data. It includes a data recording unit, a health plan generation unit, a health trend prediction unit, a health science popularization unit, and an emotional connection unit. Among them, the data collected by multiple health monitoring modules are encrypted by the identity verification and data security modules before being transmitted to the intelligent health management system for processing, forming a closed loop of health management from data collection, analysis, management to care.

[0023] The main cabinet 2 has a layered structure, including: The upper monitoring module area 21 is used to store the cuff of the blood pressure measurement module and the blood sampling pen of the blood glucose measurement module; The middle-layer verification module area 22 is used to set up the authentication and data security modules; The lower extension drawer 23 is used to store user-supplied health monitoring supplies.

[0024] The dynamic light source component 312 includes multiple sets of high color rendering index LED beads, an ambient light sensor, and a driving module. The dynamic light source component 312 is activated only when facial recognition or AI face diagnosis is performed through the camera 311, and dynamically adjusts the lighting brightness and color temperature according to the detection results of the ambient light sensor.

[0025] In the authentication and data security module, the national cryptographic encryption unit uses the SM2 asymmetric encryption algorithm to encrypt transmitted data and the SM4 symmetric encryption algorithm to encrypt stored data.

[0026] The health plan generation unit is configured to automatically generate personalized health improvement plans based on user identity information determined through authentication and their historical health data.

[0027] The health trend prediction unit uses an LSTM neural network model to predict users' future health trends based on their historical health data.

[0028] The authentication and data security module supports the creation of independent encrypted data partitions for multiple users, enabling the isolation and management of multi-user data.

[0029] The emotional connection unit is configured to provide AI-generated emotional feedback information based on the user's health data and monitored behavior, and to support family members in sending messages to the device through associated applications.

[0030] The device supports connecting to external devices or cloud servers via Bluetooth or Wi-Fi.

[0031] Specifically, the main cabinet 2 has a layered structure, divided into "upper layer monitoring module area 21, middle layer verification module area 22, and lower layer expansion drawer 23", with each layer fixed by M3 screws; Upper monitoring module area 21 (corresponding to health monitoring module): The left side is fixed with an upper arm blood pressure cuff storage box (transparent ABS material, with a press-type pop-out buckle on the front of the box). EVA cushioning cotton (0.3cm thick) is pasted inside the storage box to hold the folded upper arm blood pressure cuff. The cuff connection cable is led out from the cable hole at the bottom of the storage box and reserved to the central processing unit interface. The right side features a fixed blood glucose measurement module assembly, including a mini lancing device storage compartment (an independent transparent compartment with a capacity of 10 lancing devices and a rotating cover on the top of the compartment), and a blood glucose test strip signal processing board (equipped with an AD8232 chip, with a magnification of 1000 times). The signal processing board is connected to the central processing unit via a 2-pin terminal cable. The middle layer has an environmental monitoring module mounting position: embedding a temperature and humidity sensor (SHT30) and a light sensor (BH1750). The sensor probes are exposed on the front of the cabinet and connected to the central processor via an I2C interface cable to collect environmental data in real time and assist the skin moisture / oil measurement module in correcting the data. Mid-layer authentication module area (corresponding to authentication and data security module): front panel Figure 1 An opening is made at the location of the "fingerprint recognition module" shown, into which the fingerprint module (AS608) is embedded. The surface of the module is flush with the front of the cabinet and is connected to the national cryptographic encryption chip (model SM32F103, supporting SM2 / SM4 algorithms) via a 4-pin ribbon cable.

[0032] The internal fixed national cryptographic encryption unit and control unit (STM32L431, power consumption ≤10mW) are used to realize the linkage of "fingerprint verification-data encryption". The encryption unit is connected to the central processing unit through the SPI interface cable (10cm in length), and the control unit is connected to the fingerprint module through the UART interface (12cm in length) to realize the linkage of "fingerprint verification-data encryption".

[0033] Lower extension drawer 23 (corresponding) Figure 1The "storage area drawer" shown: The drawer adopts a pull-out structure (slide rail model SK2010, travel 6cm). The interior is divided into two areas by a partition: the left area is used to store thermometers and alcohol wipes; the right area is used to store spare blood glucose test strips. The front of the drawer is attached with anti-slip silicone strips for easy pulling out.

[0034] Specifically, regarding the assembly between the top countertop and the AI ​​Magic Mirror: (as per...) Figure 1 A groove is provided at the location of the "blood glucose test strip insertion hole" shown. A foolproof guide strip (silicone material, 0.1cm thick, only allows blood glucose test strips to be inserted with the "face up") is pasted on the inner wall of the groove. Metal contacts (0.5cm spacing, connected to the signal processing board of the blood glucose measurement module) are embedded at the bottom of the groove. When the test strip is inserted incorrectly, the contacts will not trigger a signal, and the magic mirror will pop up a window prompting "Please adjust the test strip orientation and reinsert it". A fingertip placement groove is provided on the left side of the table. A heart rate / blood oxygen sensor (MAX30102, probe diameter 0.8cm) is embedded at the bottom of the groove. The sensor surface is covered with a transparent acrylic cover to avoid wear and tear. It is connected to the central processing unit via a 3-pin cable.

[0035] AI Magic Mirror Assembly: The mirror surface uses anti-glare silver mirror, tilted at a 25° angle to the top tabletop (fixed by a metal bracket made of aluminum alloy, 1mm thick, the tilt angle can be finely adjusted using M2 screws). The right side of the mirror integrates the interactive module 6 (including a 5-inch touchscreen display, 1280×720 resolution, embedded inside the mirror, with the display area exposed) and a speaker (1cm below the display, volume range 50-80dB). A camera 311 (12MP, lens exposed 0.5cm) is installed in the center of the top of the mirror, surrounded by three groups of LED beads in a ring (corresponding to...). Figure 1 The "LED beads" shown consist of two beads with a CRI ≥ 90 per group, spaced 1cm apart, forming a ring light source with a diameter of 3cm. A light-transmitting cover (acrylic material, 3.5cm in diameter) is installed on the outside of the beads to prevent direct light from shining into the user's eyes. A light radar sensor (AWR1843, 2cm×1cm×0.5cm, detection distance 0.5-1.5m) is attached to the right side of the camera 311. The sensor signal cable (20cm long) is threaded through the bracket on the back of the mirror and connected to the central processing unit. A mounting position for a dynamic light source driver module (TPS61040, 3cm×2cm×1cm) is reserved on the back of the mirror. The driver module is connected to the LED beads via a PWM signal line (18cm long) and to a light sensor (BH1750) via an I2C interface to achieve "ambient light detection - brightness / color temperature adjustment" linkage (brightness 50-500lux, color temperature 3000K-6500K).

[0036] Skin moisture / oil measurement module installation (corresponding to "health monitoring module"): A telescopic hole (0.6cm in diameter) is made on the right side frame of the AI ​​Magic Mirror (5cm from the tabletop), and a capacitive sensor (SHT30, probe diameter ≤5mm) is embedded. The sensor is connected to a 28BYJ-48 telescopic motor (1cm stroke, 10rpm speed). The motor is connected to the central processing unit via a 4Pin control cable (15cm in length). When not in use, the sensor is completely hidden inside the frame. When the measurement function is activated, the motor pushes the sensor to extend 1cm, and after it fits against the skin, it completes data collection (collection time ≤2 seconds).

[0037] Specifically, the central processing unit is connected to each module: The central processing unit uses an STM32F407 chip (4cm×3cm×0.5cm), which is fixed on the right side of the verification module area 22 in the middle layer of the main cabinet (1cm away from the national cryptographic encryption unit). A heat dissipation space (≥2cm³) is reserved around the chip, and an aluminum heat sink (3cm×2cm×0.3cm) is attached to the surface.

[0038] Wiring connection specifications: Health monitoring modules (blood pressure, blood glucose, heart rate / blood oxygen, skin sensors): The blood pressure module is connected to the processor via an ISP interface cable (25cm long), the blood glucose module is connected via a 2-pin terminal cable (20cm long), the heart rate / blood oxygen module is connected via a 3-pin cable (15cm long), and the skin module is connected via a 4-pin control cable (15cm long). All cables use 0.1mm enameled wire and are stored along the cable management channel (2mm wide, 1.5mm deep) on the inner wall of the cabinet to avoid crossing. AI Magic Mirror Module 31 (Camera 311, LED Beads, Respiratory Rate Radar): Camera 311 is connected to the processor via a USB 2.0 cable (30cm long), LED beads are connected via a PWM signal line (18cm long), and the respiratory rate radar is connected via an SPI interface cable (20cm long). Identity verification and data security module: The fingerprint module is connected to the national cryptographic encryption chip via a 4-pin ribbon cable (15cm in length). The encryption chip is connected to the processor via an SPI interface cable (10cm in length). A 16GB SD card (partitioned into 8 independent encrypted partitions, each ≥4GB, SM4 encryption) is inserted into the processor's SD card slot. The cloud synchronization cable (Wi-Fi 6 module, 20cm in length) is led out from the cable hole (0.8cm in diameter) on the back of the cabinet. Interactive Module 6 and Power Management Module: The touch screen is connected to the processor via an HDMI cable (25cm long), the speaker is connected via an audio cable (20cm long), and the power management module is connected to the processor via a 12V power cable (30cm long). All cable connectors are insulated with heat shrink tubing (1cm in diameter and 2cm in length).

[0039] After assembly is complete, verify the relevant operations: (1) The upper arm blood pressure monitor cuff storage box and the storage area drawer do not overlap (horizontal distance ≥ 3cm). (2) There is no operational conflict between the fingerprint recognition module and the blood glucose test strip socket (vertical distance ≥ 5cm). (3) LED beads are arranged in a ring around camera 311 (center aligned); (4) All exposed components (such as fingerprint module, test strip socket) are connected to Figure 1 The indicated markings are consistent (deviation ≤ 0.5cm) to ensure that users can intuitively identify each functional area during operation.

[0040] When this application is used: The specific implementation uses the scenario of "an elderly person with high blood sugar (65 years old, type 2 diabetes for 5 years) using the device" as an example. Combining the device's visualization effects (mirror display, test strip insertion operation, fingerprint verification) and the health management system APP screenshots (data reports, science popularization push), it realizes the entire process of "identity verification - indicator collection - health management - emotional interaction". The specific steps are as follows: 1. Software debugging (must be completed in advance to ensure hardware compatibility) Blood glucose calibration (corresponding) Figure 1 Verification of the "blood glucose test strip socket" function shown): Prepare 50 standard samples with different blood glucose values ​​(3.9-16.7 mmol / L), insert the blood glucose test strips into the test strip socket (the test strips must be "face up"; if inserted incorrectly, a pop-up window will prompt "Incorrect test strip orientation, please reinsert"). Measure each sample 3 times. Adjust the signal threshold of the spectral sensor (S1133) through the device backend to ensure that the detection error is ≤0.5 mmol / L; at the same time, distinguish between "fasting (6:00-8:00)" and "postprandial (12:00-14:00)" scenarios, establish a scenario-based correction model, and label the scenario in the "blood glucose data" column of the APP effect diagram; National cryptographic encryption and data synchronization debugging (corresponding to the identity verification module): Verify SM2 transmission encryption (key length 256 bits): Record the fingerprints of 3 test users through the fingerprint module (AS608). After each verification, data encryption transmission is triggered. Record the transmission delay ≤1 second and the encryption / decryption success rate 100%; SM4 storage encryption (block length 128 bits): Write 100 simulated health data records to each user partition of the SD card. Fingerprint verification is required to unlock the data when reading it to ensure that the data is not leaked. Health management system debugging (corresponding to the APP screenshot "Data Reports, Trend Prediction"): Import 1000 cases of chronic disease (hypertension, hyperglycemia) data over 6 months, train the LSTM trend prediction model, and ensure that the trend prediction accuracy is ≥92%; set the "normal range line" (blood pressure 120 / 80mmHg, blood sugar 3.9-6.1mmol / L) in the APP screenshot "Blood Pressure / Blood Sugar Trend Chart", and automatically mark abnormal data in red; at the same time, debug the health science popularization push logic to ensure that "hypertension / hyperglycemia care content is pushed to elderly users" and "growth and development content is pushed to children's users".

[0041] 2. User Flow (Combining Visual Operations and App Interaction): Step 1: Identity Verification (corresponding to) Figure 1 The fingerprint recognition module and camera 311 are shown below: The elderly person lightly presses their finger on the fingerprint recognition module in the middle of the cabinet (the mirror displays the prompt "Please verify fingerprint" simultaneously). After successful verification, the camera 311 automatically starts (the ring LED lights up, the brightness is adjusted to 300 lux, the color temperature is 4500K to adapt to the indoor lighting environment), and completes the facial verification (to avoid verification failure due to fingerprint wear). The system automatically retrieves the elderly person's history of hyperglycemia, blood sugar data for the past 30 days, and personalized plan, and displays the user's avatar and the prompt "Welcome back, Grandpa Zhang" on the 5-inch touch screen (right side of the mirror). Step 2: Multi-indicator data collection (corresponding to...) Figure 1 The following are examples of blood glucose test strip insertion holes, fingertip placement area 4, and upper arm blood pressure monitor cuff storage boxes: Blood glucose measurement: Take out the lancing device from the upper lancing device storage compartment of the main cabinet 2 (press to pop out the device). After blood collection, insert the blood glucose test strip into the blood glucose test strip insertion hole on the table (insertion depth 3cm, you will hear a "click" sound when it is in place). After 15 seconds, the mirror will display "Fasting blood glucose 5.8mmol / L, within the normal range (3.9-6.1mmol / L)". The data will be synchronized to the "Blood Glucose Record" column in the APP (marked "2025-09-20 07:00 Fasting"). Blood pressure measurement: Take out the cuff from the upper arm blood pressure monitor cuff storage box (press the pop-out buckle to open the box), wrap it around the upper arm (fits 20-35cm arm circumference), click the "Start Blood Pressure Measurement" button on the mirror, the cuff will automatically inflate, and after 30 seconds it will display "Systolic pressure 135mmHg, Diastolic pressure 85mmHg", and the data will be synchronized to the "Blood Pressure Trend Chart" in the APP (data points marked on March 4th); Heart rate / blood oxygen measurement: Gently place your fingertip on the left side of the tabletop in the fingertip placement groove (fitting the transparent cover). After 3 seconds, the mirror displays "Heart rate 75 bpm, blood oxygen 98%", and the data is synchronized to the "More Indicators" section of the APP. At the same time, the skin moisture / oil measurement module automatically starts (the sensor on the right side extends 1cm). The elderly person places the right side of their face close to the sensor, and after 2 seconds, it displays "Skin moisture 35%, oil 20%". The data is corrected by the temperature and humidity (25℃, 50%RH) of the environmental monitoring module to ensure an accuracy of ±3% / ±2%. Tongue Image Assessment: After selecting Tongue Image Assessment on the touchscreen, the AI ​​Magic Mirror Module 31 activates the tongue image acquisition mode (the ring LED lights up, brightness 400 lux, color temperature 5500K, and the mirror displays a guide diagram to guide the user to extend their tongue and place it in the appropriate position). The elderly person extends their tongue, and the camera 311 automatically captures 3 tongue image images (1 second apart to avoid deviation from a single shot). During the shooting process, the mirror displays a real-time preview (marked "the tongue surface must completely cover the red box area," the red box being the effective range for tongue image acquisition): After the 3 images are preprocessed by the software, the best image is selected for AI analysis (time ≤ 5 seconds), and the mirror displays the analysis result: "Tongue image analysis: the tongue color is pale red, the tongue coating is thin and white, indicating that the current spleen and stomach function is normal, and there are no obvious signs of damp heat," while also noting "the data has been encrypted and stored, and previous tongue image assessments can be viewed in the 'Detection Records' module of the APP." If the tongue analysis reveals abnormalities (such as a deep red tongue or a yellow, greasy tongue coating), an additional message will pop up on the screen: "Tongue image suggests possible internal heat. It is recommended to combine this with recent blood sugar data. If accompanied by symptoms such as dry mouth and excessive thirst, consult a TCM doctor." A "TCM consultation appointment" to-do item will also be added to the "Reminder Tasks" section of the app (linked to "Health Management Closed Loop"). Step 3: Health Management Interaction (corresponding to the APP screenshots "Reports, Science Popularization, Reminders"): Data report generation: The mirrored touchscreen displays the weekly report "This week's average fasting blood glucose was 5.7 mmol / L, a decrease of 0.2 mmol / L from last week, indicating that the diet plan is effective." The "Weekly Report" section of the APP also generates a bar chart (comparing the data from last week and this week). Trend Prediction: The system analyzes data from the past 3 months using an LSTM model and displays a pop-up message stating, "Based on data from the past 3 months, if the current diet is maintained, fasting blood glucose is expected to drop to 5.5 mmol / L in 1 month." The "Trend Prediction" section of the app displays a line chart (with predicted data points marked). Push notifications: The mobile app sends a message reminding users to "remember to measure your fasting blood glucose at 6:00 tomorrow." The app's "Reminder Tasks" section displays to-do items, and the same reminder is also pushed to users via the mobile app (authorization required in advance). Health Education: The mobile app accurately displays disease-related educational articles to users, such as "How should people with high blood sugar eat breakfast? 3 low-GI recipes recommended." The "Health Education" section of the app also updates the video, which can be "favorited" (by clicking the star icon in the lower right corner of the video). Step 4: Emotional Interaction (corresponding to the device's "Voice Interaction, Health Diary" function): After completing multiple health data monitoring sessions, the app automatically prompts relevant encouraging messages based on the monitored indicators, such as: "Great! Stick to exercise and a good mood, and blood sugar control will be easier~", and the content is synced to the app. Family members can send messages to the device via the app (such as "Dad, remember to check your blood sugar today"), and the elderly can operate the mirror to "view the message" and the touch screen will display the text.

[0042] In actual use, system malfunctions still exist: E03 fault code; the associated visualization component / module is: blood glucose test strip socket (blood glucose measurement module); the fault symptom is: no response after inserting the test strip, and the mirror displays "detection failed". The specific troubleshooting and solution steps are as follows: 1. Check the test strip insertion direction: observe the anti-foolproof guide strip inside the blood glucose test strip socket to ensure that the test strip is inserted "face up" (the colored end of the test strip is facing outwards). If it is reversed, it needs to be readjusted; 2. Clean the detection area: wipe the metal contacts at the bottom of the test strip socket with an alcohol swab (avoid dust or blood residue), wait 10 seconds after wiping before inserting the test strip; 3. Restart calibration: press and hold the "restart button" on the back of the device (1cm in diameter, 2cm from the power interface) for 3 seconds. After restarting, use the "Settings - Device Calibration - Blood Glucose Calibration" function on the mirror to insert a standard calibration test strip (included with the device) to complete the calibration. After successful calibration, the mirror displays "blood glucose module normal". E05 fault code; the associated visual component / module is: fingerprint recognition module (authentication module); the fault symptom is: after pressing the fingerprint, the mirror displays "verification failed", and multiple attempts are ineffective. The specific troubleshooting and solution steps are as follows: 1. Check the hardware connection: open the middle cover of the main cabinet 2 (remove with M3 screws, the screws are located on both sides of the cabinet), check if the 4-pin ribbon cable of the fingerprint module (AS608) is loose. If it is loose, you need to re-plug the ribbon cable (the ribbon cable connector is black and located at the bottom of the module), and fix the ribbon cable with tape after plugging and unplugging; 2. Clean the fingerprint module: wipe the surface of the fingerprint recognition module with a dry soft cloth (avoid water stains or oil stains), wait 5 seconds after wiping and then verify; 3. Reinitialize the key: in the mirror "Settings - Security - National Cryptographic Encryption Settings", select "Reinitialize SM2 / SM4 Key", after initialization you need to re-enroll the user's fingerprint (when enrolling, ensure that the finger completely covers the surface of the module and stay for 2 seconds). E07 fault code; the associated visualization component / module is: mirror touch screen (interactive module 6 + health management system); the fault symptoms are: the touch screen is unresponsive, and the APP rendering cannot be loaded. The specific troubleshooting and solution steps are as follows: 1. Check Wi-Fi connection: observe the Wi-Fi icon in the upper right corner of the mirror (if it is gray, it is not connected to the network), go to "Settings - Network" to reconnect to the home Wi-Fi (ensure that the Wi-Fi signal strength is ≥-70dBm). After successful connection, the icon will turn blue; 2. Check wiring connection: open the upper cover of the main cabinet 2 and check if the HDMI cable of the touch screen (connected to the central processing unit) is loose. If it is loose, it needs to be unplugged and plugged in again (the HDMI connector is white and located on the left side of the processor); 3. Repair doctor platform integration: if the APP "consultation entrance" cannot be opened, check the health management system version through the mirror's "Settings - System Update". If the version is too low, it needs to be upgraded (the upgrade takes about 5 minutes, and the device must not be powered off during the upgrade). After the upgrade, restart the device, and the consultation entrance will return to normal; E09 fault code; the associated visualization component / module is: Camera 311 + LED beads (AI Magic Mirror Module 31); the fault symptom is: the LED beads do not light up during facial recognition, and the Camera 311 displays no image. The specific troubleshooting steps are: 1. Check the LED bead power supply: Open the back bracket of the mirror (remove using M2 screws), check if the LED bead PWM signal line (red line) is connected to the dynamic light source driver module (TPS61040). If the wire is broken, it needs to be soldered (the soldering point is the driver module "LED+"). 1. Terminal); 2. Adjust the position of camera 311: Observe whether the lens of camera 311 is blocked (such as dust or stickers), wipe the lens with a dry soft cloth, and at the same time ensure that the user's standing distance is within the requirements (0.5-1.5m, corresponding to the respiratory rate radar detection range). If it is too close or too far, the standing position needs to be adjusted; 3. Restart the module: In "Settings - Device Calibration - AI Magic Mirror Calibration", select "Restart camera 311 and LED module". After restarting, the LED beads will flash 3 times (indicating normal start-up), and the camera 311 image will be displayed on the touch screen in real time; After all faults are resolved, the device needs to complete a full module test through the "Settings - Device Self-Test" function. After a successful self-test, the mirror will display "All components are normal", ensuring that all visualized components and modules resume working together.

[0043] The above embodiments are only used to illustrate the present invention and are not intended to limit the technical solutions described herein. Although the present invention has been described in detail with reference to the above embodiments, the present invention is not limited to the specific embodiments described above. Therefore, any modifications or equivalent substitutions to the present invention, as well as all technical solutions and improvements that do not depart from the spirit and scope of the invention, are covered within the scope of the claims of the present invention.

Claims

1. A small desktop intelligent health monitoring device, characterized in that, include: The core hardware architecture includes a base (1), a main cabinet (2) and a mirror area (3) on the front of the main cabinet (2). The mirror area (3) is inclined and integrates a fingertip placement area (4), a blood glucose test strip detection area (5) and an interactive module (6) below it. Multiple health monitoring modules are integrated on a core hardware architecture to collect multi-dimensional health indicator data of users. The health monitoring modules include at least a blood pressure measurement module, a blood glucose measurement module, a heart rate and blood oxygen measurement module, a skin moisture and oil measurement module, and an AI magic mirror module (31). The AI ​​magic mirror module (31) includes at least a camera (311) and a dynamic light source component (312). The authentication and data security module is used for user authentication and encryption of collected health data. It includes a multimodal authentication unit and a national cryptographic encryption unit. The intelligent health management system is used to process and analyze encrypted health data. It includes a data recording unit, a health plan generation unit, a health trend prediction unit, a health science popularization unit, and an emotional connection unit. The data collected by the multiple health monitoring modules are encrypted by the identity verification and data security module and then transmitted to the intelligent health management system for processing, forming a closed loop of health management from data collection, analysis, management to care.

2. The small desktop intelligent health monitoring device according to claim 1, characterized in that, The main cabinet (2) has a layered structure, including: The upper monitoring module area (21) is used to store the cuff of the blood pressure measurement module and the blood glucose measurement module's sputum pen; The middle layer verification module area (22) is used to set up the identity verification and data security module; The lower extension drawer (23) is used to store the user's own health monitoring supplies.

3. The small desktop intelligent health monitoring device according to claim 1, characterized in that, The dynamic light source component (312) includes multiple sets of high color rendering index LED beads, an ambient light sensor and a driving module; the dynamic light source component (312) is activated only when performing facial recognition or AI face diagnosis through the camera (311), and dynamically adjusts the lighting brightness and color temperature according to the detection results of the ambient light sensor.

4. The small desktop intelligent health monitoring device according to claim 1, characterized in that, In the identity verification and data security module, the national cryptographic encryption unit uses the SM2 asymmetric encryption algorithm to encrypt the transmitted data and the SM4 symmetric encryption algorithm to encrypt the stored data.

5. The small desktop intelligent health monitoring device according to claim 1, characterized in that, The health plan generation unit is configured to automatically generate personalized health improvement plans based on user identity information determined through authentication and their historical health data.

6. The small desktop intelligent health monitoring device according to claim 1, characterized in that, The health trend prediction unit uses an LSTM neural network model to predict a user's future health trend based on their historical health data.

7. The small desktop intelligent health monitoring device according to claim 1, characterized in that, The authentication and data security module supports the creation of independent encrypted data partitions for multiple users, enabling the isolation and management of multi-user data.

8. The small desktop intelligent health monitoring device according to claim 1, characterized in that, The emotional connection unit is configured to provide AI-generated emotional feedback information based on the user's health data and monitored behavior, and to support family members in sending messages to the device through associated applications.

9. The small desktop intelligent health monitoring device according to any one of claims 1-8, characterized in that, The device supports connection to external devices or cloud servers via Bluetooth or WiFi.

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