Health monitoring and diet guidance system and method based on homology of medicine and food

Abstract

The invention discloses a health monitoring and diet guidance system based on homology of medicine and food, and the system comprises a data collection module which is used for collecting multi-source health data of a user, and the multi-source health data comprises human body medical examination equipment data, traditional Chinese medicine observation, listening, listening and questioning information, human face health image data and wearable equipment monitoring data; the data processing and analyzing module is connected with the data acquisition module and is used for preprocessing, integrating and analyzing the acquired data and outputting a user health condition evaluation result based on a health evaluation model combining traditional Chinese medicine and western medicine, and modern medical equipment data, traditional Chinese medicine diagnosis information, image data and dynamic monitoring data are creatively fused; according to the invention, comprehensive and multi-angle evaluation of the health condition of the user is realized, early discovery and active early warning of health risks are realized through real-time data analysis, early warning information is directly converted into executable diet suggestions, and closed-loop management of'monitoring-early warning-intervention 'is formed.

Description

Technical Field

[0001] This invention relates to the interdisciplinary field of intelligent health management and nutrition, and in particular to a health monitoring and dietary guidance system and method that combines modern medical equipment monitoring technology with the traditional Chinese medicine theory of "medicine and food sharing the same origin". Background Technology

[0002] With increasing health awareness, various health monitoring devices and health management applications are becoming more and more widespread. Modern medicine can quantitatively monitor a user's health status through data from medical equipment such as blood tests and biochemical indicators, as well as data from wearable devices. At the same time, the four diagnostic methods of traditional Chinese medicine—observation, auscultation, inquiry, and palpation—provide another holistic perspective on health and empirical basis for judgment.

[0003] The concept of "medicine and food sharing the same origin" is an important part of traditional Chinese medicine theory, referring to the fact that many foods possess medicinal properties, serving both as daily food and for disease prevention and treatment. However, combining precise data from modern medicine, the holistic view of traditional Chinese medicine, and the theory of "medicine and food sharing the same origin" to provide users with personalized, real-time health status assessments and precise dietary guidance remains a challenge in the field of health management. Existing technological solutions often suffer from the following problems: 1) Data sources are limited, relying solely on modern equipment or subjective inquiries, resulting in incomplete assessments; 2) Health assessments and dietary recommendations are disconnected, failing to deeply integrate the theory of "medicine and food sharing the same origin"; 3) There is a lack of real-time analysis capabilities regarding the incompatibilities and health compatibility of everyday ingredients, resulting in insufficient preventative and timely intervention. Summary of the Invention

[0004] The purpose of this invention is to provide a health monitoring and dietary guidance system and method based on the concept of "medicine and food sharing the same origin" to solve the following problems: 1. Data sources are limited, relying solely on modern equipment or subjective inquiries, resulting in incomplete assessments; 2. Health assessments and dietary recommendations are disconnected, failing to deeply integrate the theory of "medicine and food sharing the same origin"; 3. There is a lack of real-time analysis capabilities for the compatibility and health compatibility of everyday ingredients, resulting in insufficient preventative and timely measures.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a health monitoring and dietary guidance system based on the principle of food and medicine sharing the same origin, including a data acquisition module for collecting multi-source health data of users, wherein the multi-source health data includes data from human medical examination equipment, information from traditional Chinese medicine observation, auscultation, inquiry and palpation, facial health image data and wearable device monitoring data; The data processing and analysis module is connected to the data acquisition module and is used to preprocess, integrate and analyze the acquired data, and output the user's health status assessment results based on the integrated traditional Chinese and Western medicine health assessment model. The early warning module, connected to the data processing and analysis module, is used to generate and issue a health early warning when the health status assessment result indicates an abnormal risk. The food and medicine homology database module is used to store the properties of ingredients, the incompatibilities between ingredients, the medicinal efficacy data of food and medicine homology ingredients, and dietary plans that match different health conditions. The diet analysis and suggestion module is connected to the data processing and analysis module and the food and medicine homology database module, respectively. It is used to perform food incompatibility analysis and health matching degree analysis based on the user's health status assessment results and the food information input by the user on the day, and generate diet suggestions. The health report generation module is connected to the data processing and analysis module and the diet analysis and advice module, respectively, and is used to integrate the health status assessment results, health warning information and diet advice to generate a comprehensive health report. The recipe creation module is connected to the diet analysis and suggestion module and the food and medicine homology database module, respectively, and is used to generate personalized food and medicine homology nutritionally balanced recipes based on the diet suggestions and the food and medicine homology theory.

[0006] A method for health monitoring and dietary guidance based on the principle of food and medicine sharing the same origin includes the following steps: S1: Collect multi-source health data of users through the data acquisition module. The multi-source health data includes data from human medical examination equipment, information from traditional Chinese medicine observation, auscultation, inquiry and palpation, facial health image data and wearable device monitoring data. S2: The data processing and analysis module preprocesses, integrates, and analyzes the data collected by S1, and obtains the user's health status assessment results based on preset assessment rules; S3: The early warning module assesses health risks based on the evaluation results obtained in S2. If any abnormal risks are found, a health warning is generated and issued. S4: Obtain information on the ingredients the user plans to eat that day; S5: By combining the food incompatibility and medicinal efficacy data stored in the food and medicine homology database module with the diet analysis and suggestion module, the food information obtained in S4 is subjected to incompatibility judgment and health suitability analysis. S6: Integrate the health status assessment results from S2, the early warning information from S3, and the dietary analysis results from S5 through the health report generation module to generate a health report that includes a health status summary, risk warnings, and dietary recommendations; S7: Based on the analysis results of S5 and combined with the theory of food and medicine sharing the same origin, the recipe creation module customizes personalized nutritional recipes for users. S8: Output the health report and personalized recipes to the user terminal.

[0007] Preferably, in S1, the human medical examination equipment data includes blood routine, urine routine and biochemical index data; the traditional Chinese medicine observation, auscultation, inquiry and palpation information includes tongue appearance, pulse appearance, complexion, voice, body odor and symptom complaint information; facial health image data is used to analyze facial health status through image recognition; wearable device monitoring data includes heart rate, blood pressure, steps, sleep duration and sleep quality data.

[0008] Preferably, in step S2, data preprocessing includes data cleaning, format standardization, and abnormal data processing; data integration includes multi-source data association based on user identifiers; and data analysis includes generating user health status assessment results using machine learning algorithms or integrated traditional Chinese and Western medicine assessment models.

[0009] Preferably, in step S5, the food incompatibility analysis is achieved by querying a food incompatibility table; the health compatibility analysis is based on the user's health status assessment results to determine whether the food attributes and effects meet the user's current health needs.

[0010] Compared with the prior art, the beneficial effects of the present invention are: 1. Multi-source data fusion: It creatively integrates data from modern medical equipment, traditional Chinese medicine diagnostic information, image data, and dynamic monitoring data to achieve a comprehensive and multi-dimensional assessment of the user's health status; 2. Intelligent early warning and intervention: Through real-time data analysis, early detection and proactive warning of health risks are achieved, and the warning information is directly transformed into actionable dietary recommendations, forming a closed-loop management of "monitoring-early warning-intervention"; 3. Deeply integrates the theory of food and medicine from the same source: It not only provides basic checks on food incompatibilities, but also judges the suitability of food based on the user's specific constitution and health status, and provides personalized recipes that combine therapeutic effects and nutritional balance, organically combining traditional wisdom with modern nutrition. 4. Personalization and practicality: The entire system is user-centric, and the output results (health reports, recipes) are intuitive, easy to understand, and highly operable, truly realizing personalized daily health management. Attached Figure Description

[0011] Figure 1 This is a system structure block diagram of the present invention; Figure 2 This is a flowchart of the method of the present invention. Detailed Implementation

[0012] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Identical components are denoted by the same reference numerals. It should be noted that the terms "front," "rear," "left," "right," "up," and "down" used in the following description refer to directions in the accompanying drawings, while the terms "bottom" and "top," "inner" and "outer" refer to directions toward or away from the geometric center of a specific component, respectively.

[0013] Please see Figures 1-2 This invention provides a technical solution: a health monitoring and dietary guidance system based on the principle of food and medicine sharing the same origin, comprising: The data acquisition module integrates data from multiple channels, including data from medical examination equipment, information from traditional Chinese medicine diagnostic methods (inspection, auscultation, inquiry, and palpation), facial health image data, and wearable device monitoring data. Medical examination equipment data: Through standardized interfaces of hospital information systems (HIS) and laboratory information systems (LIS) (such as HL7, FHIR), or through user-uploaded images of physical examination reports (which are then extracted using OCR technology), structured biochemical indicators such as complete blood count, urinalysis, liver function, kidney function, blood glucose, and blood lipids are obtained. Information from the four diagnostic methods of Traditional Chinese Medicine (TCM): A structured form is provided via a terminal app for users or professional physicians to fill out. For example, the "Tongue Appearance" sub-item provides a standard color chart for users to compare and select (light red, light white, red, crimson, purple, etc.), and allows uploading close-up photos of the tongue coating; the "Pulse Appearance" is selected via a drop-down menu (floating, deep, slow, rapid, wiry, slippery, etc.); and the "Symptoms" section allows users to submit their chief complaint by checking boxes from a common symptom database and supplementing with free text. Facial health image data: Access the camera of the terminal device, guide the user to take a facial photo in a standard pose (facing forward, with uniform lighting, and no obstructions), and upload it to the server; Wearable device monitoring data: By accessing the APIs of Apple HealthKit, Google Fit, or the open platforms of major smartwatch manufacturers (such as Huawei, Xiaomi, and Apple), the user's continuous heart rate, blood pressure (supported by some devices), daily steps, and sleep stage (deep sleep, light sleep, REM, and wakefulness) data can be synchronized in an authorized manner.

[0014] The implementation of the data processing and analysis module includes data preprocessing, data integration, data analysis and health assessment, modern medical indicator analysis and traditional Chinese medicine health status identification; Data preprocessing: Cleaning the received multi-source heterogeneous data, including handling missing values ​​(such as filling or deleting with the mean), removing obvious outliers (such as heart rate 200 beats / minute), standardizing the timestamp format, and converting various types of data into a standardized data format defined internally by the system (such as JSON or Protocol Buffers). Data integration: A unique identifier (UserID) is created for each user. All collected data is associated with this UserID and stored in the user's personal health record database, forming a longitudinal time series of health data; Data Analysis and Health Assessment: The core of this module is a health assessment model that integrates traditional Chinese and Western medicine. Modern medical indicator analysis: This involves defining normal ranges for various biochemical indicators and physiological parameters. A rule engine determines whether each indicator is abnormal and calculates a comprehensive score. For example, blood pressure consistently above 140 / 90 mmHg is marked as "risk of hypertension." Traditional Chinese Medicine (TCM) Health Status Identification: Machine learning models (such as Convolutional Neural Networks) are used to extract and classify features from user-uploaded tongue images, identifying characteristics such as tongue color, tongue coating thickness, and color. Combined with user-inputted pulse and symptom information, this data is fed into another classification model (such as Support Vector Machines (SVM) or a deep learning model) for TCM syndrome identification, outputting assessment results such as "Qi Deficiency Constitution," "Damp-Heat Constitution," and "Yin Deficiency with Yang Excess."

[0015] Finally, the results of modern medical indicator analysis and TCM syndrome identification are integrated to generate a multi-dimensional "User Health Status Assessment Report". This report includes both abnormal Western medical indicators and TCM constitution assessment, and provides a comprehensive health risk level (e.g., low risk, medium risk, high risk).

[0016] The early warning module monitors the health assessment results output by the data processing and analysis module. The system has a set of preset early warning rules, such as: "IF systolic blood pressure >160 mmHg THEEN triggers an emergency hypertension warning." "If Traditional Chinese Medicine (TCM) constitution is identified as 'phlegm and blood stasis' and total cholesterol > 6.2 mmol / L, then a moderate warning for cardiovascular and cerebrovascular risk is triggered." Once the assessment results meet the conditions of any of the early warning rules, the early warning module will immediately generate an early warning message and send it to the user and / or their designated emergency contact via App push notification, SMS, or email.

[0017] The implementation of the food and medicine homology database module is a structured relational database (such as MySQL or PostgreSQL), and the main data tables include: Foods table: Fields include food ID, name, nature (cold, cool, neutral, warm, hot), flavor (sour, bitter, sweet, pungent, salty), meridian tropism, main effects, and nutritional content.

[0018] Incompatibility Table: Fields include ingredient A_ID, ingredient B_ID, reason for incompatibility, and description of consequences.

[0019] The syndrome-based diet plan table (diet_therapy) includes fields such as syndrome type (e.g., "weak spleen and stomach"), recommended food list, prohibited food list, and sample recipe link.

[0020] This database needs to be built by nutritionists, traditional Chinese medicine practitioners, and professional chefs, and continuously maintained and updated.

[0021] The dietary analysis and suggestion module allows users to input a list of ingredients they plan to eat (such as "tomatoes, eggs, and crabs") through the App.

[0022] Food incompatibility analysis: The system combines the user-input food list into pairs and queries the food incompatibility table. If no incompatibility record is found for "tomatoes" and "crab," and also for "eggs" and "crab," then it is determined that there is no incompatibility. If "persimmons" and "crab" are input, incompatibility records are found, and a warning suggestion is generated: "Warning: Eating crab and persimmons together may cause discomfort; it is recommended to avoid eating them together." Health Matching Analysis: The system retrieves the user's "Health Status Assessment Report." Assuming the user's current condition is "cold stomach," the module queries the database and finds that "crab" is considered a cold food, suggesting that those with a cold stomach should consume it with caution. The system then generates a suggestion: "Reminder: Your current constitution is not suitable for consuming too much cold-natured crab. It is recommended to eat it with ginger and vinegar to dispel the cold, or to replace it with warm-natured meat." The health report generation module integrates text, data, and charts into a template. Using a template engine (such as Jinja2 or Apache FreeMarker), it automatically populates the following content into an HTML or Word template: basic user information, report generation date; a health status summary, displaying key indicator trends in chart form, listing major abnormal indicators and TCM constitution identification results; risk warnings, prominently displaying warnings issued by the early warning module (if any); dietary recommendations, listing incompatibility warnings and matching suggestions generated by the dietary analysis module; finally, the rendered file is exported as a PDF for users to view, download, or share.

[0023] The implementation of the recipe creation module represents a high level of system intelligence. This module is a recommendation system, and its operation process is as follows: Input: The user's health needs (e.g., "need to lower blood pressure, strengthen the spleen and remove dampness"), dietary restrictions, and preferences; Processing: Obtain a pool of recommended ingredients that meet the health needs from the syndrome dietary plan table; Combine nutritional principles (e.g., the food pyramid) to ensure a balanced combination of carbohydrates, proteins, fats, and vitamins; Use algorithms (e.g., constraint satisfaction algorithm CSP or collaborative filtering) to screen and combine ingredients from the pool, avoiding ingredients that are prohibited by the user; Match dishes containing these ingredients and cooked using healthy methods (e.g., steaming, boiling, stir-frying) from a pre-stored large recipe library, or automatically generate new recipes based on dish models; Output: Generate a complete personalized daily or weekly recipe, including the names of dishes for breakfast, lunch, dinner, and snacks, a list of required ingredients, precise quantities (grams), and detailed cooking steps.

[0024] A method for health monitoring and dietary guidance based on the principle of food and medicine sharing the same origin includes the following steps: S1: Collect multi-source health data of users through the data acquisition module. The multi-source health data includes data from human medical examination equipment, information from traditional Chinese medicine observation, auscultation, inquiry and palpation, facial health image data and wearable device monitoring data. S2: The data processing and analysis module preprocesses, integrates, and analyzes the data collected by S1, and obtains the user's health status assessment results based on preset assessment rules; S3: The early warning module assesses health risks based on the evaluation results obtained in S2. If any abnormal risks are found, a health warning is generated and issued. S4: Obtain information on the ingredients the user plans to eat that day; S5: By combining the food incompatibility and medicinal efficacy data stored in the food and medicine homology database module with the diet analysis and suggestion module, the food information obtained in S4 is subjected to incompatibility judgment and health suitability analysis. S6: Integrate the health status assessment results from S2, the early warning information from S3, and the dietary analysis results from S5 through the health report generation module to generate a health report that includes a health status summary, risk warnings, and dietary recommendations; S7: Based on the analysis results of S5 and combined with the theory of food and medicine sharing the same origin, the recipe creation module customizes personalized nutritional recipes for users. S8: Output the health report and personalized recipes to the user terminal.

[0025] Example 1: Take a user with potential risk of hypertension as an example.

[0026] Data collection (S1): Users continuously monitor heart rate and blood pressure through smartwatches (wearable devices); regularly measure biochemical indicators (such as blood lipids) on home health check devices; and upload photos of tongue coating (facial images), fill in recent symptoms (such as occasional dizziness), and enter pulse information (such as wiry pulse) from traditional Chinese medicine practitioners via mobile APP.

[0027] Data Processing and Early Warning (S2, S3): The data processing and analysis module cleans and analyzes data such as blood pressure and blood lipids. The analysis model finds that the user's blood pressure is consistently at a critical high point and blood lipids are slightly high. Combined with symptoms of wiry pulse and dizziness, the assessment result is "liver yang hyperactivity, with a risk of hypertension". The early warning module then issues an alert to the user: "High blood pressure risk detected. It is recommended to pay attention to diet and consult a doctor."

[0028] Dietary Analysis and Report Generation (S4, S5, S6): The user plans to make braised pork trotters with soybeans for dinner. After inputting the ingredients "soybeans" and "pork trotters," the dietary analysis module queries the database: a) Incompatibility Analysis: No incompatibility found; b) Health Suitability Analysis: Pork trotters are oily and high in cholesterol, which does not meet the requirements for lowering blood pressure and cholesterol. The module generates the following suggestion: "Pork trotters have a high fat content, so it is recommended to reduce consumption or replace them with lean meat. It is also recommended to add ingredients that help lower blood pressure, such as celery and black fungus." The health report generation module compiles all the above information into a report.

[0029] Recipe creation and output (S7, S8): The recipe creation module receives a "lower blood pressure and cholesterol" request, retrieves relevant ingredients from the database, and generates a personalized recipe, such as: "Dinner recommendation: Celery stir-fried with dried tofu, steamed sea fish, oatmeal rice." This recipe and health report are pushed to the user's mobile app.

[0030] Example 2: A user with type 2 diabetes mellitus (T2DM) and diagnosed by traditional Chinese medicine as having "deficiency of both Qi and Yin".

[0031] Data collection (S1): The user uploaded a recent physical examination report (showing a fasting blood glucose of 9.5 mmol / L), synchronized sleep and step data from the past week through a smartwatch, and filled in the symptoms of "fatigue, dry mouth, and excessive thirst" through the App, and uploaded a photo of the tongue (red tongue with little saliva).

[0032] Processing and Analysis (S2): The data processing and analysis module identified severely elevated blood glucose levels. Based on symptoms and tongue appearance, the TCM model determined it to be "Qi and Yin deficiency". The comprehensive assessment was "T2DM (Typical Diabetes Mellitus), Qi and Yin Deficiency Syndrome, High Risk".

[0033] Warning (S3): The warning module immediately issues a warning: "Blood sugar level is too high. It is recommended to seek medical attention as soon as possible to adjust the treatment plan and strictly control your diet." Dietary Analysis (S4, S5): The user inputs a lunch plan: "Rice, Braised Pork Belly, Honey Pumpkin". The dietary analysis module checks: a) No food incompatibilities; b) Matching analysis: Braised Pork Belly (rich and greasy, rapid glycemic index), Honey (high GI, strictly prohibited), Pumpkin (good, but the honey preparation method is unsuitable). The module generates a strong recommendation: "Warning: Braised Pork Belly and Honey Pumpkin are extremely unsuitable for your current situation! It is recommended to change the staple food to mixed grain rice, the meat to steamed fish, and the vegetable to cold spinach salad." Reports and Recipes (S6, S7, S8): The health report generation module summarizes all the above information. The recipe creation module generates a personalized recipe for the user, such as: "Lunch: Quinoa rice (50g), steamed sea bass (100g), cold spinach salad (200g), tofu and mushroom soup. This recipe aims to stabilize blood sugar and nourish qi and yin." Through the above embodiments, it can be seen that the system and method of the present invention can effectively realize dynamic health monitoring, risk warning and precise dietary guidance, and have strong practicality.

[0034] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0035] In the description of this invention, unless otherwise stated, "a plurality of" means two or more; the terms "upper," "lower," "left," "right," "inner," "outer," "front end," "rear end," "head," "tail," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, the terms "first," "second," "third," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0036] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "connected" and "linked" should be interpreted broadly. For example, they can refer to fixed connections or detachable connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

Claims

1. A health monitoring and dietary guidance system based on the principle of food and medicine sharing the same origin, characterized in that: It includes a data acquisition module for collecting multi-source health data from users, including data from human medical examination equipment, information from traditional Chinese medicine diagnostic methods (inspection, auscultation, inquiry, and palpation), facial health image data, and wearable device monitoring data. The data processing and analysis module is connected to the data acquisition module and is used to preprocess, integrate and analyze the acquired data, and output the user's health status assessment results based on the integrated traditional Chinese and Western medicine health assessment model. The early warning module, connected to the data processing and analysis module, is used to generate and issue a health early warning when the health status assessment result indicates an abnormal risk. The food and medicine homology database module is used to store the properties of ingredients, the incompatibilities between ingredients, the medicinal efficacy data of food and medicine homology ingredients, and dietary plans that match different health conditions. The diet analysis and suggestion module is connected to the data processing and analysis module and the food and medicine homology database module, respectively. It is used to perform food incompatibility analysis and health matching degree analysis based on the user's health status assessment results and the food information input by the user on the day, and generate diet suggestions. The health report generation module is connected to the data processing and analysis module and the diet analysis and advice module, respectively, and is used to integrate the health status assessment results, health warning information and diet advice to generate a comprehensive health report. The recipe creation module is connected to the diet analysis and suggestion module and the food and medicine homology database module, respectively, and is used to generate personalized food and medicine homology nutritionally balanced recipes based on the diet suggestions and the food and medicine homology theory.

2. A method for health monitoring and dietary guidance based on the principle of food and medicine sharing the same origin, comprising the following steps: S1: Collect multi-source health data of users through the data acquisition module. The multi-source health data includes data from human medical examination equipment, information from traditional Chinese medicine observation, auscultation, inquiry and palpation, facial health image data and wearable device monitoring data. S2: The data processing and analysis module preprocesses, integrates, and analyzes the data collected by S1, and obtains the user's health status assessment results based on preset assessment rules; S3: The early warning module assesses health risks based on the evaluation results obtained in S2. If any abnormal risks are found, a health warning is generated and issued. S4: Obtain information on the ingredients the user plans to eat that day; S5: By combining the food incompatibility and medicinal efficacy data stored in the food and medicine homology database module with the diet analysis and suggestion module, the food information obtained in S4 is subjected to incompatibility judgment and health suitability analysis. S6: Integrate the health status assessment results from S2, the early warning information from S3, and the dietary analysis results from S5 through the health report generation module to generate a health report that includes a health status summary, risk warnings, and dietary recommendations; S7: Based on the analysis results of S5 and combined with the theory of food and medicine sharing the same origin, the recipe creation module customizes personalized nutritional recipes for users. S8: Output the health report and personalized recipes to the user terminal.

3. The method for health monitoring and dietary guidance based on the principle of food and medicine homology according to claim 2, characterized in that: In S1, the data from the human medical examination equipment includes blood routine, urine routine and biochemical index data; the information from traditional Chinese medicine observation, auscultation, inquiry and palpation includes tongue appearance, pulse appearance, complexion, voice, body odor and chief complaint information; facial health image data is used to analyze facial health status through image recognition; and the data from wearable device monitoring includes heart rate, blood pressure, steps, sleep duration and sleep quality data.

4. A method for health monitoring and dietary guidance based on the principle of food and medicine homology according to claim 2, characterized in that: In S2, data preprocessing includes data cleaning, format standardization, and abnormal data processing; data integration includes multi-source data association based on user identifiers; and data analysis includes generating user health status assessment results using machine learning algorithms or integrated traditional Chinese and Western medicine assessment models.

5. A method for health monitoring and dietary guidance based on the principle of food and medicine homology according to claim 2, characterized in that: In step S5, the food incompatibility analysis is achieved by querying the food incompatibility table; the health compatibility analysis is based on the user's health status assessment results to determine whether the food attributes and effects meet the user's current health needs.

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