70 results about "Diet management" patented technology

The invention relates to the field of health management, in particular to an intelligent food identification and diet analysis system based on multi-modal interaction, which comprises an intelligent food scale hardware module, a multi-modal identification module, a food database module, a diet analysis module and a mobile phone end synchronization module. The intelligent food scale hardware module comprises a weighing sensor, a camera, a voice interaction unit and a communication unit; the multi-mode recognition module obtains food information through image recognition or voice recognition and matches the food information with the food database module. The diet analysis module calculates the actual intake according to the weighing data and the matched food information; and the mobile phone end synchronization module supports real-time transmission of data to a mobile phone end APP, and generates visual diet analysis reports and health suggestions. Through an image and voice bimodal recognition mechanism, the food recognition accuracy is remarkably improved, the intelligent weighing and data synchronization functions are combined, the user operation process is simplified, and accurate diet management and health guidance are achieved.

The invention discloses an intelligent dietary nutrition nursing management system and method based on health data, and relates to the technical field of medical nutrition management. The method includes generating nutritional requirement feature information of a user; analyzing the loss rates of the key nutritional ingredients of the target food material in different processing modes, and obtaining a nutritional loss weight value corresponding to each processing mode; establishing an adaptability matching model according to the nutrition demand feature information and the nutrition loss weight value, and selecting a processing mode meeting the user demand; dynamically adjusting the recommended diet scheme according to the selected processing mode in combination with the current real-time health state data of the user; and recording feedback data of the user on the recommended diet scheme and subsequent changes of the health state, and dynamically optimizing the matching model. According to the invention, a more personalized and scientific diet management scheme is provided, and the problems of low diet scheme recommendation precision and insufficient dynamic adaptive capacity in the prior art are effectively solved.

The invention, which relates to the field of diabetes nursing, discloses a multi-model fusion personalized diet recommendation system for diabetes mellitus, comprising a recipe recommendation decision module based on a system architecture, a blood sugar prediction module, and an intelligent question and answer interaction module. The nutritional requirements and the blood sugar control target of the patient are met at the same time; the blood glucose prediction module predicts the postprandial blood glucose level according to the current blood glucose level of the user and the recommended recipe; the intelligent question and answer interaction module provides convenient natural language interaction, collects user feedback and dynamically adjusts recommended content. Compared with the prior art, the method has the advantages that scientific diet recommendation is provided, the recommendation result is optimized through a user feedback mechanism, and the recommendation accuracy and practicability are ensured; a convenient health management tool is provided, and the compliance of the patient on diet management is enhanced; the health condition of the diabetic patient can be improved, the burden of a medical system is relieved, and the public health level is improved.

The invention provides a patient treatment diet intelligent monitoring system and method based on a mobile intelligent terminal. The system comprises a medical care terminal, a patient terminal and a computing terminal. The medical care terminal collects basic information and disease information of the patient and formulates a diet formula; the patient side sets daily diet intake and uploads food photos; and the calculation end analyzes the picture and the formula, calculates the actual and recommended nutrient intake, the weighted deviation degree, the total recommendation amount, the compliance factor and the trend adjustment factor, further obtains a diet conformity dynamic optimization index, and realizes diet deviation degree monitoring and early warning. The system integrates three modules, comprehensively optimizes diet management, improves efficiency and accuracy, provides a convenient management means for medical staff, and has important practical significance and application value.

The invention relates to the technical field of artificial intelligence, in particular to a diet recommendation management method and system based on the vital sign state of a user, and the method comprises the steps: building a food nutrition information base in advance; generating sign monitoring data of a target user, acquiring vital sign characteristics of the user according to the monitoring data, and calculating the reference intake of personal dietary nutrients at the same time; the user carries out daily healthy diet card punching, diet analysis is carried out, and daily diet recommendation is carried out according to the vital signs of the user and the nutrient elements needing to be ingested every day; acquiring vital sign feedback information of the target user, and updating the daily recommended diet scheme according to the feedback information to obtain an updated daily diet management scheme; and performing health management and vital sign monitoring on the target user according to the updated daily diet management scheme. According to the invention, diet control under the condition of abnormal vital signs of the user can be improved, and life quality is improved.

The invention relates to the technical field of puerpera diet management, in particular to a postpartum diet management system and method. The server comprises a data acquisition module, a dimension extraction module, an evaluation module, a diet customization module, a baby data acquisition module and a diet optimization module; wherein the infant data acquisition module is used for monitoring physical state data of an infant born by a puerpera in real time at the first time after the puerpera is postpartum; the judgment module is used for determining the to-be-supplemented nutrient elements missed by the infant and the corresponding missing content according to the body state data corresponding to the infant in each time period; and the diet optimization module is used for optimizing the basic diet scheme according to the basic diet scheme corresponding to each time period of the lying-in woman and the to-be-supplemented nutrient elements and the deficiency content required by the baby born by the lying-in woman in each time period to form a diet optimization scheme.

The invention discloses a diet data analysis method and device based on a large language model, and belongs to the technical field of diet data analys.The method comprises the steps that user basic information and taste preferences described by natural languages are collected through a user interface; unstructured data of food is captured regularly, and a healthy diet database is constructed after large language model cleaning and tagging processing; basic metabolic rate and daily total energy consumption are calculated in combination with the basic information of the user, and a nutrient intake target is determined; the big language model application layer generates a daily diet plan containing cooking suggestions; and receiving the diet recorded by the user photographing or natural language, analyzing the diet, comparing the analyzed diet with the nutrition target, and generating personalized feedback containing problems, reasons and adjustment suggestions. The device correspondingly comprises five functional modules. According to the invention, automatic maintenance and personalized analysis of diet data are realized, and intelligence and practicability of diet management are improved.

The present invention relates to the field of smart elderly care technology, and discloses a community smart elderly care service system, including a user information management module: managing the basic information, physical examination records and sensor data of the elderly; a data acquisition module: collecting the user's physical examination information, vital sign sensor data, and regularly updating the data; a data analysis and processing module: analyzing the user's health data, generating a health report, and performing trend analysis; an intelligent recommendation module: providing personalized lifestyle suggestions based on the user's health status; and a user interaction module: providing a user interaction interface. The community smart elderly care service system proposed in the present invention solves the shortcomings of existing systems in terms of personalized services. Through precise nutritional demand calculation, comprehensive data collection and analysis, social interaction and incentive mechanisms, convenient food delivery and kitchen assistants, etc., the system can provide customized diet plans for the elderly, ensuring that users receive comprehensive and accurate diet management.

The invention discloses a diet management system for diabetic patients, which relates to the technical field of intelligent diet management and is technically characterized by comprising a data acquisition module, a nutrition analysis and suggestion generation module, a blood glucose prediction module, a feedback learning module, a personalized strategy recommendation module, an excitation and verification module and a communication module, the system automatically collects health and diet data of a user through a camera, a body fat scale, a glucometer and wearable equipment, identifies food types and estimates components by using a convolutional neural network, and realizes automatic calculation of energy and nutritional ingredients. The food-blood glucose response model constructed on the basis of individual historical data can predict postprandial blood glucose changes, sensitivity coefficients are dynamically updated through a regression correction mechanism, individualized blood glucose prediction is achieved, the system further generates intake suggestions through a component back-calculation method, and the intake suggestions and the intake suggestions are given to a user. And the result is visually displayed on the terminal in the form of a blood glucose curve and an energy distribution diagram, and real-time diet guidance is provided.

This disclosure teaches the generation of multiple recipes for patients with chronic kidney disease. The recipes are generated by application of a large language model to patient data, including both medical and preference data. The recipes are verified by a dietician and may be used to generate shopping lists and instructions for an automated food preparation device.

To enable comprehensive health management of diet management, exercise management, sleep management, hospital visit management, and amusement management, and to solve problems such as increase in health needs and weight gain due to lack of exercise.SOLUTION: Provided is a health management system, the system comprising: diet management means, exercise management means, sleep management means, hospital visit management means, and entertainment management means.SELECTED DRAWING: Figure 1

The application discloses an intelligent diet management method and system based on multi-source health data fusion, and relates to the field of health diet management. In order to solve the defects of the existing diet management system, such as data fragmentation, manual input dependence, incapability of generating personalized diet plans and incapability of forming a closed-loop feedback, basic information, medical information and body composition data of a user are acquired; initial health parameters are generated according to the basic information, the medical information and the body composition data of the user, wherein the initial health parameters include basal metabolic rate, total energy consumption and total energy requirement; and the initial health parameters are updated according to dynamic input real-time data, so as to realize intervention and management on diet behaviors, wherein the dynamic input real-time data includes diet data and exercise data. The application is mainly used for intervention and management on diet behaviors according to the results of multi-source health data fusion.

The invention discloses a chronic disease patient diet management system, and the system comprises a data collection and integration module which is used for obtaining and fusing multi-source data, and forming a patient exclusive data set; the personalized diet scheme generation module is used for calculating and generating an initial diet scheme based on a medical rule base and the exclusive data set, and a final scheme is formed after the initial diet scheme is audited by the medical terminal; the diet scheme execution support module is used for assisting the user to adjust the diet scheme through a visual tool, a recipe library and an intelligent recording mode; and the monitoring and dynamic adjustment module is used for collecting diet execution data and physiological index data of the user, analyzing the relevance through a machine learning algorithm, generating an adjustment suggestion, and updating the scheme after confirmation of the medical end. According to the invention, multi-source data can be automatically integrated, a personalized diet scheme is intelligently generated and dynamically adjusted, and convenient execution support and continuous health management are provided for patients.

The invention relates to the technical field of catering diet management, in particular to an intelligent catering system and a diet management method. The server comprises a data acquisition module, an optimization module, a sending module, a data receiving module, an identification module and a putting module; wherein the optimization module is used for determining a catering type corresponding to the catering when the catering needs to be carried out on a patient, calling food corresponding to the catering type from a corresponding food database, and carrying out random matching based on the called food to form a plurality of food matching sets; according to the current physical state data, the personal basic information and the medical basic information of the patient, selecting the healthiest food matching from the plurality of food matching sets; and the putting module is used for putting a related video which explains the eating importance corresponding to the unselected food and the benefit degree to the patient to the user side according to the identified unselected food in the healthy food collocation.

Disclosed are a digital treatment method, system, and computer program for providing personalized diet management for alleviating mild cognitive impairment. The digital treatment method comprises the steps of: storing, in a cognitive training providing device, a list of food ingredients to be consumed by a mild cognitive impairment patient for a set period; when a food ingredient list request command is input to a user terminal communicating with the cognitive training providing device, transmitting the list of food ingredients stored in the cognitive training providing device to the user terminal and providing the list of food ingredients through an application executed in the user terminal; when a food ingredient selection command is input to the user terminal, providing, through the application, the number of selections for each food ingredient selected from the list of food ingredients; and when the set period expires, providing, through the application, a result calculated according to a MIND diet score for the consumed food ingredient.

To provide a system capable of providing health management and an exercise plan optimum for an individual user.SOLUTION: The system includes a body weight / body fat acquisition part, a metabolism calculation part, a calorie / exercise amount calculation part, a voice advice part, a meal management part, an exercise management part, a timer part, a data storage part, and a statistical data creation part. The body weight / body fat acquisition unit acquires body weight and body fat. The metabolism calculation unit calculates basal metabolism and active metabolism. The calorie / exercise amount calculation unit calculates a required calorie intake and a required exercise amount. The audio advice unit provides audio advice. The meal management unit manages meal contents. The exercise manager may manage an exercise menu. The timer unit manages a rest time. The data storage unit stores data. The statistical data creation unit creates statistical data.SELECTED DRAWING: Figure 1

The invention provides an intelligent recommendation system for diet management of headache patients. The intelligent recommendation system comprises a data acquisition module, a frequent combination analysis module, a continuous frequent statistics module, a non-frequent sequence analysis module and a taboo diet recommendation module. Wherein the data acquisition module is used for acquiring a plurality of preset duration diet records before headache; the frequent combination analysis module is used for obtaining a plurality of k-item frequent food combinations and a plurality of non-frequent food combinations; the continuous frequent statistics module is used for obtaining a continuous frequent food combination and a discrete frequent food combination; the infrequent sequence analysis module is used for obtaining a continuous infrequent food combination; and the taboo diet recommendation module sends the taboo diet recommendation list to the diet management end. The technical problems that in the prior art, diet management of headache patients depends on subjective evaluation, and personalized precise recommendation is lacked are solved, and the technical effects that a headache inducement food combination mode is automatically recognized based on the data mining technology and personalized taboo diet recommendation is provided are achieved.

The present invention provides a method for constructing a knowledge graph database based on chronic disease diet management, which relates to the field of health management. The method includes: determining various types of chronic disease types; obtaining historical patient information of the k-th type of historical patients according to the k-th type of chronic disease type; determining a dietary health relationship function of the k-th type of chronic disease type according to the historical patient information of the k-th type of historical patients; determining various types of food names; obtaining the nutritional components of the i-th food according to the i-th type of food name; determining a food health score according to the nutritional components of the i-th food and the dietary health relationship function of the k-th type of chronic disease type; generating a knowledge graph database according to the food health score, food name, and chronic disease type. According to the present invention, the accuracy of generating the knowledge graph database can be improved.

The invention relates to the cross technical field of artificial intelligence and healthy diet management, in particular to a healthy diet intelligent recommendation system and method based on a large model and an ai agent, multi-dimensional data of plateau environment, human physiology, storable food materials and cooking conditions are collected through a multi-modal module, a standardized data set is formed through preprocessing, and on the basis of the data set, an ai intelligent agent is obtained; the dynamic energy demand is accurately evaluated in combination with an altitude influence coefficient, a physical power coefficient and the like, meanwhile, a nutrient supply gap is calculated, an optimal storable food material combination with the minimum resource consumption is screened by establishing a nutrition standard constraint equation and inventory constraints, and a dietary scheme is generated in combination with plateau cooking evaluation. The health standard-reaching rate and the food material utilization rate are calculated based on the body feedback data, the scene, health and resource risk factors are fused to obtain the early warning index, grading intervention is triggered, intelligent and dynamic adaptation of plateau diet supply is achieved, the health of the garrison is effectively guaranteed, the food material utilization rate is increased, and the scene adaptation risk is reduced.

The invention discloses a multi-modal accurate quantification nutritional diet management system, and the system comprises an image processing module which collects image data of dishes, carries out the preprocessing of the image data, carries out the self-adaptive division of the image data according to the types and numbers of the dishes, and extracts contour features, the fuzzy reasoning module recognizes the dishes after contour feature division and outputs recognition results and corresponding confidence coefficients, the weight distribution module calculates a weight ratio distribution proportion based on an image region area proportion and a confidence coefficient proportion of each dish, dynamic compensation calibration is carried out in combination with total weight data to obtain weight, and the weight distribution proportion is calculated according to the weight distribution proportion. The nutrition calculation module performs nutrition data correction according to the weight and a preset nutrition database to obtain nutritional ingredient data, and the intelligent decision-making module generates diet suggestions based on the nutritional ingredient data, the health target of the user and the dining scene. Therefore, the recognition precision and the real-time performance can be improved, the recognition and weight calculation precision of the mixed dishes can be improved, and meanwhile operation is simplified to adapt to various requirement scenes.

To improve a meal habit of an animal.SOLUTION: An animal meal evaluation system comprises: an acquisition unit for acquiring ecological information of an animal; an analysis unit for analyzing a tendency of a meal of the animal based on biological information; a detection unit for detecting a change in the tendency; and a notification unit for giving a notification of a result of the detection. In particular, the system analyzes a change in a time zone of the meal, a meal continuation time taken for a meal of one time, the frequency of meals in a predetermined period, and a meal-related behavior made during a meal or / and after the meal, and gives a notification of the change. A constitution like this allows health control and meal control of the animal to be performed efficiently and effectively.SELECTED DRAWING: Figure 1

The invention relates to the technical field of infant diet management, and discloses an infant nutrition intake analysis and diet intelligent management method. The method comprises the following steps: interactively obtaining physiological characteristic parameters and diet history parameters of an infant individual; determining nutritional requirement type selection, and obtaining a target diet plan; interactively acquiring target structure features of the target diet plan, initializing diet management conditions in combination with nutritional demand selection, and outputting initial management control constraints including a nutrition intake threshold and a maximum allowable deviation rate; taking the initial management control constraint as an optimization condition, optimizing the ingestion preparation speed according to the food ingestion record information and the preset time constraint, and positioning the ingestion control speed; analyzing a nutrition deviation trend of the target diet plan according to the intake control speed, and optimizing diet adjustment control parameters based on an analysis result; and when food intake is managed according to the intake control speed during diet execution, intermittently and automatically adjusting the target diet plan by using the diet adjustment control parameters.

To address the problem of saving time and effort and improving efficiency when proposing a menu for the day aiming at nutrition balance and diet management from the content of meal.SOLUTION: Provided is a system for proposing a menu for the day aiming at nutrition balance and diet management from the content of meal. The system includes: means for analyzing the meal contents during the prior week and proposing a menu taking into account appropriate nutrition balance; and means for adjusting the proposition in accordance with the difficulty level of cooking.SELECTED DRAWING: Figure 1

1. Name of the Design Product: Graphic User Interface for Health AI Intelligent System's Sports Diet Management for Electronic Devices. 2. Use of the Design Product: The design product is used for an electronic device. 3. Design Key Points of the Design Product: Lies in the interface content in the graphic user interface. 4. Picture or Photograph that Best Illustrates the Design Key Points: Interface Variation State Diagram 1. 5. The electronic device is of conventional design, and other views are omitted. 6. Use of the Graphic User Interface: For the management of sports courses and diet combinations. 7. Human-Computer Interaction Method of the Graphic User Interface: The main view is the main interface of sports courses and diet combinations. Click on the "Sports Course" icon in the main view to enter Interface Variation State Diagram 1. Slide up by clicking on the blank area in Interface Variation State Diagram 1 to enter Interface Variation State Diagram 2. Click on "17" in the calendar of Interface Variation State Diagram 2 to enter Interface Variation State Diagram 3 to view the sports courses on the 17th. Slide up by clicking on the blank area in Interface Variation State Diagram 3 to enter Interface Variation State Diagram 4. Interface Variation Reference Diagram 1 is the usage state diagram of Interface Variation State Diagram 1. Interface Variation Reference Diagram 2 is the usage state diagram of Interface Variation State Diagram 2. Interface Variation Reference Diagram 3 is the usage state diagram of Interface Variation State Diagram 3. Interface Variation Reference Diagram 4 is the usage state diagram of Interface Variation State Diagram 4.

To provide a technique that enables easy prediction of weight loss of a subject through dietary management.SOLUTION: A method of the present invention for quantitatively predicting weight loss of a subject through dietary management comprises an acquisition step of acquiring at least one indicator selected from a group consisting of: an indicator computed from physical indicators consisting of the height and pulse rate, and answer indicators consisting of answers to questions about awareness and / or behavior regarding health-consciousness; an indicator regarding recognition of the physical constitution and weight computed from answers to an eating behavior questionnaire; an indicator computed from answers to questions regarding mindset about dieting; and an indicator computed from answers to questions regarding motivation for dietary management.SELECTED DRAWING: None

The invention discloses a food calorie calculation method based on binocular vision, and relates to the technical field of computer vision and nutrition analysis. The method comprises the following steps: firstly, acquiring a food image by using a calibrated binocular camera, and preprocessing the image; and then a semi-global block matching algorithm is combined with weighted least square filtering to calculate and optimize a disparity map, and an edge-disparity collaborative network is introduced to improve the matching precision of the weak texture food. Then, segmenting a food area through a U-Net network, and outputting an accurate contour after edge optimization; and identifying the specific category of the food by using a lightweight classification network. And then, according to the food form, adaptively selecting an equivalent cylinder method or a point cloud reconstruction method to carry out three-dimensional volume reconstruction, and converting the volume into mass in combination with a density database. And finally, querying a calorie database containing cooking mode information to obtain an accurate calorie value. The method is obviously superior to the prior art, and an efficient and reliable solution is provided for family diet management and health monitoring.

The invention discloses an intelligent nutrition evaluation system and method based on multi-source data fusion and an adaptive algorithm. Based on Chinese resident dietary pagoda guidelines, a user uploads food photos and weight through an APP, and the system identifies food types by using deep learning and calculates calories of a meal or a day in combination with the weight; food calorie can be quickly identified through photographing, and manual calculation is not needed; meanwhile, diet data of the user are continuously recorded, daily diet habits are analyzed, professional diet suggestions are generated through an adaptive algorithm, accurate and convenient exercise nutrition evaluation and guidance are achieved, the diet management efficiency and scientificity of the user are improved, a psychological nutrition module is adopted, lightweight test questionnaires are set around emotions, emotion, cognition and behaviors, and end-side encryption is adopted to protect privacy; evaluation results and guidance suggestions are obtained according to psychological scales, retest is reminded, and intervention resources are pushed when risks occur; the module is fused with an original scheme, psychological results are brought into diet analysis, a'physiological and psychological 'comprehensive report is generated monthly, and dual health management is achieved.

The utility model discloses a blood glucose control diet management dinner plate for diabetics, which comprises a main dinner plate and an embedded dinner plate, a weighing sensor is fixedly mounted on the lower surface of the main dinner plate, the lower surface of the weighing sensor is movably connected with a bearing panel, and a holding handle is fixedly mounted on the cambered surface of the main dinner plate. According to the blood glucose control diet management dinner plate for the diabetic patient, the main dinner plate can be inversely buckled on a kitchen table top, the patient can place food on the bearing panel to be weighed, and fresh dishes can be quantitatively calculated and made; therefore, the intake amount can be accurately controlled, excessive amount is avoided under the condition that the food is full, the intake weight and the satiety critical point of the user can be known at any time after frying, the user can conveniently control the corresponding food material amount in the next making process, and waste caused by excessive making is avoided.

The invention relates to the technical field of intelligent recipe recommendation, and particularly discloses an intelligent recipe recommendation and optimization system based on user demands, and the system comprises the steps: firstly collecting the multi-source heterogeneous diet related data of a user; then, a tense heterogeneous knowledge graph fusing time slice nodes is constructed, and the time slice nodes are marked with state labels representing short-term physiological fluctuation of the user; then, based on the map, generating a user state sensing feature vector capable of resisting periodic interference through aggregation weight distribution of state sensing; then, reasoning is carried out in the map along a predefined health target constraint path, and a health association degree score of the recipe is calculated in combination with a path damping factor; and finally, generating and outputting a recommendation list by integrating the health score and the diversity balance factor. According to the method, technical isolation of short-term fluctuation preference of the user is achieved, it is ensured that recommendation closely conforms to a long-term health target, and individuation and scientificity of healthy diet management are effectively improved.