39 results about "Diet management" patented technology

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 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.

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.

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 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.

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.

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.

The invention belongs to the field of diet management, and particularly discloses a diet management system and a diet management method for type 2 diabetes mellitus through combination of food failure and ketogenesis, and the system comprises an applicable population screening module which is configured to lock patients based on biochemical indexes; the blood ketone dynamic monitoring module is configured to detect a blood ketone value in real time through a micro-fluidic chip sensor; the nutrition execution module is configured to output the following stage schemes: a feed-off period scheme; a ketogenic stage scheme; a transitional period scheme; according to the invention, through the staged management of the food failure combined ketogenic diet, in combination with the precise screening of suitable people, the dynamic monitoring of blood ketogen and the scientific configuration of a nutrition scheme, the blood glucose index of the type 2 diabetes mellitus patient can be effectively improved, and at the same time, by supplementing electrolyte, compound nutrients, antioxidants and the like, the intestinal health is maintained, the mitochondrial function is improved, and the blood uric acid is regulated and controlled, so that the health of the type 2 diabetes mellitus patient is improved. And after the HbA1c reaches the standard, the patient is assisted to smoothly transit to low-sugar diet, so that scientific management and control on the type 2 diabetes mellitus are realized.

This invention relates to an orally administrated nutritional supplement for the management of symptoms of irritable bowel syndrome (IBS) and related functional disorders. The composition includes:1) zinc-L-carnosine 60-100 mg per daily dose or an equivalent combination of zinc and L-carnosine providing 16?20 mg elemental Zn and 55-60 mg L-carnosine; 2) extract of Boswellia serrata resin with 25-35% total AKBA yielding 60-90 mg AKBA; 3) a probiotic blend 30-100 billion CFU that includes, at least, one strain from the genera Streptococcus, Bifidobacterium, and Lactobacillus. The active ingredients are incorporated into an acid-resistant or slow-release pharmaceutical form which limits their release in gastric pH and releases them when the pH is "greater than or equal to" 5.5, ensuring their integrity until they reach the intestine. The combination of the three above components strengthens the intestinal barrier, reduces intestinal inflammation, and restores the intestinal microbiota, providing comprehensive support to patients with IBS and related functional intestinal disorders.

The invention relates to a method for realizing automatic recipe recommendation based on personalized parameter setting. The method comprises the following steps: inputting the age, gender, height, weight and labor type of a patient, the diagnosis of a current doctor and the type of food to be forbidden; a recipe suitable for the patient is judged, and if the patient is a diabetic patient, a food exchange method is selected; if the patient is a weight losing group, selecting a combined calculation method of basic metabolism BMR and daily consumption TDEE; and automatically generating a recipe menu through the large model according to the recipe cycle needing to be recommended and the careful degree of recipe recommendation. By adopting the method and the device for realizing automatic recipe recommendation based on personalized parameter setting, the processor and the computer readable storage medium thereof, through intelligent and personalized diet management, the requirements of a patient are accurately met, meanwhile, the calculation process is simplified, a scientific and reasonable diet plan is automatically generated, and diet diary records are cooperated, so that the user experience is improved. And the diet management efficiency and effect are greatly improved.

The application relates to a behavior guidance data generation method, system, device and computer equipment. The method comprises the following steps: collecting a multi-modal physiological perception signal of a target object; analyzing the multi-modal physiological perception signal based on a behavior recognition model to obtain effective behavior data in a target time period; processing the effective behavior data based on a state recognition model to obtain a behavior execution state; determining a behavior control strategy corresponding to the behavior execution state in a corresponding relationship between execution states and control strategies; and generating guidance information based on the behavior control strategy and outputting the guidance information. The method can improve the accuracy of the prompt for user diet management.

The application relates to the technical field of data analysis, and discloses a health diet collaborative management method and system based on a big data platform, which comprises the following steps: based on a nutrition and health big data platform, a health management scheme suitable for a user is acquired according to a scene type; the health management scheme at least comprises a personalized recipe; according to the health management scheme, a smart cooking system corresponding to the scene is controlled to execute a cooking operation for the personalized recipe, so that a diet dish is obtained; the eating condition data of the user for the diet dish and the health data of the user are monitored; the monitoring data is uploaded to the nutrition and health big data platform; and based on the nutrition and health big data platform, a health diet analysis result for the user is generated according to the monitoring data. It can be seen that the application can realize multi-scene collaborative management of the health diet of the user, and can improve the management reliability and flexibility of the health scheme in different scenes while realizing personalized health diet management.

The invention relates to a mandibular movement function rehabilitation system, belongs to the technical field of mandibular rehabilitation detection, and solves the problems of difficult measurement, subjective evaluation, fixed scheme and poor interaction in existing mandibular rehabilitation. The image acquisition module is used for acquiring and processing a first target image set and a second target image set; the mandible motion range measuring module is used for identifying a key mark point set and a reference point set in the first target image set to obtain a mandible motion range physical value; the chewing efficiency evaluation module is used for extracting tone features of each target image in the second target image set and obtaining a chewing efficiency evaluation value; and the personalized scheme generation module is used for generating a personalized mandibular movement rehabilitation training scheme and a diet management scheme through a constructed recommendation model by combining a pre-constructed medical knowledge base on the basis of each received mandibular movement activity physical value and the chewing efficiency evaluation value. The mandibular rehabilitation process which is simple in measurement, objective in evaluation and personalized in scheme is achieved.

This application discloses a method, apparatus, device, and medium for adjusting game tasks related to diet regulation, relating to the field of game content update technology and applicable to interactive game systems. The method includes: collecting historical dietary behavior uploaded by users and analyzing it to identify several abnormal feature tags among multiple feature tags in a first theoretical system; determining a first task ratio based on the correlation between the feature tags and the several abnormal feature tags; determining the user's first task score based on multiple dimensions according to the historical dietary behavior; and determining a second task ratio based on the first task score; constructing several game tasks based on the first theoretical system according to the first task ratio and the second task ratio, so that the user can complete operational interactions with the interactive game system according to the game tasks. By implementing this application, the semantic association of the corresponding theoretical system can be added to gamified diet management, ensuring a better user experience.

The invention relates to the field of diet management, in particular to an intelligent nutritional diet management system and method. The method comprises the following steps: acquiring female multi-dimensional physiological data, and based on the female multi-dimensional physiological data, performing analysis through a multi-modal data fusion strategy to generate a female skin state quantization set; obtaining a female sequential diet record set, tracing the female food intolerance through correlation analysis based on the female skin state quantification set and the female sequential diet record set, and generating a female food intolerance map; and acquiring female physiological cycle stage data, creating a cycle-synchronous diet planning engine based on the female physiological cycle stage data and the female food intolerance atlas, and generating and outputting staged personalized diet management schemes. In the female diet management process, it can be ensured that diet suggestions are accurately matched with physiological needs of women in different stages, and meanwhile the risk of food intolerance is avoided.

The invention discloses a hyperuricemia diet management method and platform based on a community interaction and incentive mechanism. The method comprises the following steps: collecting health information, diet behaviors and community interaction information of a user, and performing correlation analysis to generate basic risk data containing metabolic risks and community influence tendency; estimating daily purine intake based on the basic risk data and comparing the daily purine intake with the community to generate joint risk data; performing risk layering and behavior clustering on the users, dividing the users with similar risks and complementary community influence into intervention groups, and generating a target task set containing contents such as limited high-purine food; and calculating a user behavior contribution value in combination with the task completion condition and the driving degree to the behaviors of other people, thereby determining an incentive parameter and issuing points or virtual rights and interests. According to the method, the physiological features and the social attributes are deeply fused, and the diet management compliance and the intervention effect of the hyperuricemia patient are effectively improved through complementary grouping and dynamic excitation.

The invention relates to the technical field of diet management, and discloses a digital diet management method and system for children obesity, and the method comprises the steps: data collection: collecting physiological data in real time through wearable equipment, including the blood glucose, heart rate variability and body fat rate of children, and collecting the diet data of children through a mobile phone application, the food type and component are automatically identified by adopting an image identification technology. The system comprises a data acquisition module, a modeling module, a reinforcement learning module, a causal intervention module, a federal learning module and a feedback module. The real-time performance and accuracy of personalized diet intervention are improved through federal learning and global optimization, and efficient learning is realized while data privacy is guaranteed; combining a dynamic graph neural network and causal reasoning to realize dynamic optimization of metabolism modeling and an intervention strategy; and through the virtual nutritionist and the gamification task, the interactivity and the participation degree of children are enhanced, the formation of healthy diet habits is promoted, and the personalized and intelligent health management level is remarkably improved.

The invention provides a family healthy diet management method and device, a storage medium and a program product, and the method comprises the steps: obtaining the nutrient demand information of each family member, the nutrient demand information at least comprising the demands of the family members for various nutrients; according to the nutrient demand information of each family member, determining the family member of the combined meal; and determining the recipes of the family members of the combined meal according to the nutrient demand information of the family members of the combined meal. The method solves the problem that a healthy diet management method in the prior art is a single-person catering mode and cannot realize balanced nutrition catering of family groups.

An object of a system according to an embodiment is to propose an optimal recipe in consideration of an individual's health condition and automatically incorporate the recipe into a diet management application.SOLUTION: A system according to an embodiment includes a keyword input unit, a recipe proposing unit, and a recipe importing unit. The keyword input unit allows a user to input a keyword. A recipe proposing part proposes an optimum recipe in which a generation AI considers a personal health state based on the keyword inputted by the keyword inputting part. The recipe importing unit automatically imports the recipe information proposed by the recipe proposing unit into the meal management application.SELECTED DRAWING: Figure 1

The present disclosure teaches the generation of multiple recipes for patients with chronic kidney disease. The recipes are generated by applying a large language model to patient data, including medical data and preference data. The recipes are validated by a nutritionist and may be used to generate a shopping list and instructions for an automated food preparation device.

The invention discloses a comprehensive weight reduction system based on light food interruption, and the system comprises a diet management module which comprises a light food interruption day management unit which is used for a user to use a meal replacement agent to replace a dinner for eating in two days; the normal diet day management unit is used for the user to eat the nutrition blocker before the meal of the remaining five days; the mobile phone terminal management module comprises a patient terminal unit which is used for a patient to punch in the body weight every day and recording diet and exercise records; the group management unit is used for performing group card punching; and the doctor end unit is used for checking patient data in real time and providing personalized diet and exercise suggestions. According to the method, discontinuous two-day light eating-up days and five-day normal eating-up days are set in a week, meal replacement agents are used in the light eating-up days, nutrition blocking agents are used before Chinese meal in the normal eating-up days, and the purpose of reducing weight is achieved while nutritional requirements are guaranteed; and the mobile phone terminal management module records and feeds back daily weight, diet and exercise data of the individual, and the doctor terminal unit provides personalized intervention and suggestions.

The invention discloses a weight loss postoperative diet nutrition intake evaluation system based on a neural network, relates to the technical field of medical health management, and aims to solve the problem that dynamic monitoring and optimization of patient diet management are difficult to realize in the prior art. The system comprises a data acquisition module, a data preprocessing module, a neural network model module, a nutrition evaluation module, a diet suggestion generation module and a user interaction module. The data acquisition module is used for acquiring basic information data, physiological index data and diet type and intake information data of a patient; the data processing module is used for cleaning the collected data and removing abnormal values, and then converting diet types and intake information into nutrition intake data; the neural network model module is used for constructing a neural network and forming a training set by collecting historical patient postoperative data. The method has the advantage that the diet management of the patient is dynamically monitored and optimized.

The invention relates to the field of diet management, in particular to a diet management system based on a carbon optimization technology, which is provided with an input module for collecting diet information of a user on that day, and a basic processor for calculating the total intake energy of the user, preprocessing the total intake energy, generating corresponding preprocessing data, and sending the preprocessing data to the user. The system comprises a preprocessing module used for preprocessing data and selecting a plurality of index characteristics of the preprocessed data, a machine learning module used for learning the preprocessed data according to a standard sampling rate and the index characteristics and obtaining a plurality of next-day recommended recipes and next-day recommended recipes, and a recommendation module used for displaying the next-day recommended recipes and displaying the next-day recommended recipes after a user clicks the recipes. According to the technical scheme, daily diet is input through voice, diet suggestions are generated and displayed, through machine learning, the speed of food energy recognition is increased, the healthy degree of user diet is increased, then corresponding recipes are recommended to users, and personalized effective control over food calorie data is achieved.