27 results about "Diet advice" patented technology

The invention provides a CKD nutrition management visual monitoring method and system based on big data, and relates to the technical field of data processing, and the method comprises the steps: carrying out the data preprocessing according to real-time health data, and obtaining a standardized health data set; according to the standardized health data set, evaluating nutritional requirements of the patient, and combining disease progression, individual differences and diet preferences of the patient to generate a personalized nutrition management scheme, the personalized nutrition management scheme including recommended diet, a nutrition supplement scheme and an intake behavior adjustment scheme; according to the personalized nutrition management scheme, a visual display interface is generated, and the visual display interface displays the nutrition state, diet suggestions, potential health risks and predicted effects of the patient; adjusting a personalized nutrition management scheme in real time according to feedback data and health state changes provided by the patient in the use process, and presenting an updated scheme through a visual display interface; the autonomy and accuracy of nutrition management are improved.

The invention discloses a human-in-the-loop diet monitoring robot based on body intelligence. The human-in-the-loop diet monitoring robot at least comprises a food information acquisition module, a food identification module, a human-computer interaction module, an identification model incremental learning module, a diet recording module and a diet analysis module. The system obtains food information, and performs real-time identification and recording in combination with a machine learning algorithm. Besides, the man-machine interaction module provides an intelligent diet accompanying function by utilizing cue word engineering and improves the diet experience of the user, and the diet analysis module carries out nutritional ingredient analysis on diet records through an image-text interaction deep fusion technology based on a multi-modal large model and generates personalized diet suggestions according to the diet condition of the user. The system is combined with a healthy diet recording and analyzing function to ensure data synchronization and analysis. According to the method, the adaptability of new food types is remarkably improved, and reliable technical support is provided for intelligent diet monitoring, diet accompanying and healthy diet analysis.

The present application relates to a terminal device for blood sugar management during pregnancy and its cloud server, the terminal device collects physiological data and blood sugar data of a target user including the gestation period, the cloud server obtains a plurality of blood sugar data of reference users from a plurality of terminal devices and forms an overall reference data set in a manner associated with gestational age, the cloud server calculates basic statistical indicators for each group in the overall reference data set, combines the specific percentile position of the user's blood sugar data in its own group distribution, judges the current blood sugar state of the user by comparing the user's blood sugar data with the preset healthy blood sugar range, and generates a graded diet suggestion accordingly, the diet suggestion optimizes the diet structure of the target user by selecting food categories with different GI values; the terminal device receives and visually displays personalized diet suggestions matching the blood sugar status of the target user to the target user.

A system is provided.SOLUTION: A system including means for a user to photograph and upload an image of a food, means for a server to analyze the received image and identify the food, means for the server to acquire nutrition information of the identified food and chart a nutrition balance, means for the terminal to display the nutrition balance chart to a user, means for the user to input a chronic disease information and a health goal and for the server to individually make a suitable diet proposal, means for supporting purchase of foodstuffs according to a budget in a convenience store and a supermarket, and means for linking the nutrition balance information with a medical institution.SELECTED DRAWING: Figure 1

The invention discloses a healthy diet intelligent management system, which comprises an acquisition module used for acquiring basic data, body data and food material reserve data of a user, and a calculation module used for calculating basic metabolism of the user based on the basic data and the body data of the user; the recommendation module is used for regularly recommending daily nutrition indexes to the user and recommending a target diet of each meal every day to the user according to the basic metabolism and food material reserve data of the user; the target diet comprises a first diet suggestion and a second diet suggestion; the first diet suggestion package is used for recommending target food in the food material reserve data and the weight of each single food of the target food species according to the basic metabolism of the user and the nutrition required by the user; the second diet suggestion calculates the weight of each food of the target food species selected by the user according to the target food selected by the user from the food material reserve and the basic metabolism of the user, and takes the target food selected by the user and the weight as target diet recommendation.

The invention relates to the field of health management and personalized nutrition guidance, and discloses an intelligent nutrition management method and system, an intelligent bracelet and a mobile terminal.The intelligent nutrition management method comprises the following steps that physiological parameters and behavior data of a user are collected in real time; according to the collected physiological parameters and behavior data, a dynamic physiological state model of the user is constructed, and the model describes the change of the physiological state of the user along with time; on the basis of the dynamic physiological state model of the user and a preset health target, personalized diet suggestions of the user are generated through an optimization algorithm; the diet suggestions generated through optimization are fed back to the user in a chart or character mode, the dynamic physiological state model and the diet suggestions are dynamically adjusted based on real-time feedback data of the user, and circulation optimization is achieved. According to the invention, dynamic monitoring and adjustment of the health state of the user can be realized, accurate and personalized diet suggestions are generated, and scientificity and real-time performance of health management are improved.

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.

Provide a system. 【Solution means】 Means for obtaining health-related data from a user, Means for transferring the obtained data to an information processing device, Means for analyzing the transferred data and generating a health management plan for the user, Means for visually and aurally providing the generated health management plan to the user, Means for receiving the achievements and feedback from the user and utilizing them for the creation of the next health management plan, Means for recording dietary information using a mobile terminal, Means for proposing exercise time and dietary advice based on the data transmitted from the mobile terminal, A system including the above.

The present invention provides a fully automatic intelligent fresh-keeping refrigerator system and an operation method, which relates to the technical field of smart home. The system includes a high-resolution camera, an image processing chip and an edge computing device module, an RFID tag and an RFID reader module, a cloud server and an interaction interface. The present invention combines a deep learning model with Internet of Things technology to achieve real-time monitoring and accurate prediction of the freshness of food in the refrigerator. Its advantages are that it can automatically identify the state of food, timely warn of expired food, effectively reduce food waste, and continuously optimize the prediction accuracy through adaptive learning, provide personalized diet suggestions and health management for users, and greatly improve the convenience and health of smart home life.

The invention discloses a diet recommendation method and system based on a big language model and electronic equipment, and the diet recommendation method comprises the steps: constructing a system instruction used for guiding a big language model behavior role, constructing a user context according to health data and diet preference, and generating a model prompt word based on the system instruction and the user context. Wherein the system instruction comprises a role definition layer, a behavior constraint layer and an output specification layer, and the diet preference comprises explicit preference and implicit preference. And inputting the model cue word into the large language model, and obtaining a text result. And analyzing the text result, generating a structured diet recommendation, and outputting the diet recommendation. And obtaining interaction information sent by the user based on diet recommendation, and iteratively optimizing model parameters and diet preferences of the large language model based on the interaction information. According to the invention, the big language model is guided to generate diet suggestions meeting the health requirements and tastes of the user by constructing the system instruction and the user context, so that more accurate and personalized diet recommendation is realized.

Provide a system. 【Solution means】An acquisition means for acquiring exercise data, An acquisition means for acquiring exercise data, A body shape analysis means for photographing and analyzing body shape data, A nutrition analysis means for analyzing diet data and determining the calorie and nutrient balance, A proposal generation means for generating a personalized exercise program and diet proposal based on these data, A notification means for notifying the user of the generated exercise program and diet proposal, An audio output means for providing health-related information via audio output, Means for providing a consumer health management robot for acquiring and analyzing data in a residential environment, A system including.

The invention provides a diet recommendation method and device, electronic equipment and a storage medium, and relates to the technical field of intelligent medical treatment, and the method comprises the steps: obtaining a historical feeding record of a user, and calculating a daily habitual feeding time period set; when a user injects a medicine, querying a corresponding medicine concentration prediction curve according to the current injection dosage; calculating an initial suggested feeding time period set according to the drug concentration prediction curve and the habitual feeding time period set; the initial suggested feeding time periods with the duration smaller than a preset threshold value are combined and prolonged, and a target suggested feeding time period set is obtained; and when the target suggested eating time period is reached, sending a diet suggestion scheme containing the food type and the quantity to the user. By implementing the technical scheme provided by the invention, the technical problem of discomfort caused by eating according to a fixed diet scheme after GLP-1 drugs are injected at present is solved.

This invention discloses a method for dynamic regulation of pancreatic enzymes based on dietary intake, comprising the following steps: S1: collecting patient data through an input module; S2: calculating an individualized pancreatic enzyme dose based on the data collected by the input module through an algorithm module; S3: outputting the pancreatic enzyme dose and dietary recommendations based on the calculation results through an output module; S4: adjusting parameters through a closed-loop feedback module. The pancreatic enzyme dose is dynamically calculated based on the patient's fat intake and digestive capacity at each meal to achieve a precise match between "how much fat is consumed and how much enzyme is given."

The invention provides a diet scheme recommendation method and system based on machine learning and linear programming, and the method comprises the steps: obtaining multi-source user data, and obtaining a user health target based on the multi-source user data; providing a food nutrition database, generating an initial personalized diet suggestion by using a machine learning algorithm based on the user health target, and recommending the initial personalized diet suggestion; tracking user feedback according to the initial personalized diet suggestion, performing dynamic analysis on information fed back by the user, and correcting a health target of the user; when the target deviation of the information fed back by the user is smaller than a set threshold value, continuing to push the original diet suggestions; and otherwise, obtaining a user deviation reason, and correcting the initial personalized diet suggestion in real time by using a linear programming algorithm. According to the method, the accuracy of diet suggestions is improved through a machine learning algorithm, the diet scheme is optimized by using a linear programming algorithm, and dynamic self-adaptive personalized diet suggestion recommendation and tracking are realized.

The embodiment of the invention discloses a personalized healthy catering matching system constructed by utilizing artificial intelligence, and how to realize intelligent and dynamic menu generation and recommendation taking high-nutrition food materials (such as salmons) as a core based on multi-dimensional user data, authoritative nutrition knowledge and food material characteristics. The system not only solves the pain point of'thousands of people one face 'of traditional diet suggestions, improves user compliance and health benefits through accurate matching, but also deeply integrates nutritional science, cooking science and information technology, and provides a core tool for intelligent health management.

The embodiment of the application discloses a kind of healthy diet management method, system, electronic equipment and storage medium, it is related to health management technical field, comprising: obtaining the diet scene time sequence image frame under diet scene, and the diet behavior time sequence image frame corresponding to target object under diet scene;Diet scene time sequence image frame is obtained according to the image of pre-configured image acquisition equipment and is collected diet area, and diet area is the area where target object is located, and diet behavior time sequence image frame is obtained according to the image of pre-configured image acquisition equipment and is collected target object;In response to feature extraction is carried out to diet behavior time sequence image frame, obtain diet behavior time sequence data, according to diet behavior time sequence data, determine the effective eating behavior data of target object under diet scene;According to diet scene time sequence image frame, determine the nutrition characteristic data of diet under diet scene;According to effective eating behavior data and nutrition characteristic data, generate the diet suggestion scheme corresponding to target object.

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.

The present invention relates to systems and methods for estimating an individual's Faecalibacterium prausnitzii (Fprau) amounts and for providing personalized recommendations to maintain or improve the Fprau. In several embodiments of the invention, the individual's Fprau amounts are estimated based on their Food FrequencyQuestionnaire (FFQ) records. In several embodiments, the methods are implemented by a computer system. In several embodiments of the invention, personalized recommendations and dietary advice are given to the individual to maintain or improve said individual's Fprau.

The invention belongs to the field of diet monitoring, and provides a multi-terminal data collaboration method and system based on user diet records for solving the problems of traditional multi-terminal diet data transmission conflicts, bandwidth waste, one-sided analysis and the like. The method comprises the steps that the robot and the intelligent device generate first data and second data respectively and send the first data and the second data to the compiler; the compiler processes the data by adopting a wavelength and amplitude differential compiling mode, synchronously transmits the data to the interpretation end in the same transmission line, and sends the interpreted data to the server; and the server analyzes user diet based on Nash equilibrium, generates diet suggestions through the capsule neural network and feeds back the diet suggestions to the multiple terminals. The system comprises a data acquisition module, a data compiling module, a data transmission module, a data interpretation module and a data processing module which respectively execute corresponding steps. According to the invention, the transmission efficiency is improved through differentiated compiling, multi-source data are fused and subjected to collaborative analysis, comprehensive and accurate diet suggestions are generated, and the method is suitable for multi-scene diet monitoring and management.

1. Name of the product of this design: Dietary report graphical user interface for electronic device. 2. Purpose of this design product: for use in an electronic device. 3. The key design point of this design product lies in the graphical user interface. 4. The picture or photo that best illustrates the design points: interface change state diagram. 5. Conventional design, omitting rear view, elevation view, left and right view. 6. Purpose of the graphical user interface: Dietary report graphical user interface for electronic devices. The main view is the interface display in standby mode. The upper half of the interface uses the refrigerator 3D scene model as the background, with the status bar, time and weather, date, and week displayed on the top. The four commonly used buttons of child lock, lock screen, settings, and personal center are displayed on the right. The card below shows the operating status of the device; the two sections of ingredient management and recipes are displayed at the bottom. The user clicks "More" in the main view recipe section to enter the interface change status diagram. The interface displays three parts: comprehensive ingredient rating, ingredient structure analysis, and dietary recommendations. The semicircle shows the comprehensive score of the current ingredients, which is a comprehensive evaluation score based on three aspects: ingredient richness, ingredient freshness, and nutritional balance. The richness of ingredients includes high, medium and low, the freshness includes fresh / general / not fresh, and the nutritional balance includes balanced / unbalanced. The ingredient structure analysis uses a bar chart to count the number of different types of ingredients, and counts them according to the number of stored ingredients according to eggs, milk, meat, vegetables, fruits, grains, beans, and aquatic products. Dietary recommendations prompt users to supplement their intake based on the types of ingredients currently missing from their ingredient management list. The reference diagram of the usage status is the interface in the usage status.

A system is provided.SOLUTION: A system comprising: means for inputting exercise contents of a user; means for inputting meal contents of the user; means for transmitting the exercise contents and the meal contents to a server; generation and AI means for analyzing the exercise contents and the meal contents; means for generating an optimal training menu and meal advice based on an analysis result; and means for monitoring a progressing state of the user and adjusting a training plan as necessary.SELECTED DRAWING: Figure 1

According to the intelligent generation method for the healthy diet suggestions of the user, the category and the content of the nutrition ingested by the user are calculated, and if the change amplitude between the historical health state index and the current-day health state index of the user is larger than the preset amplitude threshold value, the healthy diet suggestions of the user are generated. If yes, calculating a difference proportion of corresponding health state data in the historical health state indexes and the health state indexes of the day, selecting target health state data, and adjusting diet data of the user; the category and content of food ingested by a user are obtained through automatic analysis, the category and content of nutrition ingested are calculated, and whether the health state data of the user is abnormal or not is judged according to the change amplitude between the historical health state index of the user and the health state index of the day. If yes, the diet data of the user is adjusted according to the abnormal data to obtain healthy diet data, so that the health state data of the user is tracked in real time, and healthy diet is accurately recommended to improve the diet health of the user.

The invention relates to the technical field of user diet management, and discloses a weight management method and device based on user characteristics and a diet recommendation method and device.According to the weight management method based on the user characteristics, an energy intake distribution model is combined with label information of a target user, a weight management target, an energy recommendation target and current motion information, so that the weight management efficiency is improved; according to the embodiment of the invention, the dynamic adjustment scheme of the daily diet suggestion can be generated, so that the accurate diet suggestion can be provided for the target user even if the real-time movement of the target user and / or the intake of each meal is changed, the target user is helped to realize the weight management target, and the weight management experience of the target user is enhanced. Therefore, according to the invention, not only can the future diet plan of the target user be dynamically adjusted to realize the weight management target of the target user, but also the recipe can be accurately recommended for the target user according to the diet preference of the target user.

The system according to the embodiment aims to provide an initial diagnosis based on the user's symptoms, suggest appropriate medical departments, and provide dietary suggestions based on the user's family structure and lifestyle in an integrated manner. [Solution] A system according to an embodiment includes a reception unit, a diagnosis unit, a proposal unit, and a reservation unit. The reception unit accepts input of symptoms from a user. The diagnosis unit performs an initial diagnosis based on the symptoms accepted by the reception unit. The proposal unit proposes a medical department based on the diagnosis results obtained by the diagnosis unit. The reservation unit searches for a hospital with the medical department proposed by the proposal unit and makes a reservation. The proposal unit makes specific meal proposals based on the user's family composition and lifestyle.

This application discloses an information-based planning and evaluation system for the treatment of active ulcerative colitis, belonging to the field of planning and evaluation technology. By analyzing the state data of food and drugs after they pass through the digestive tract, and calculating sharpness and residue load, it quantifies the potential mechanical stimulation or burden that different foods and drugs may cause to the fragile and damaged colonic mucosa. It provides a more sensitive and accurate quantitative tool by automatically extracting microscopic feature data from endoscopic images. In addition to predicting drug efficacy, it also predicts mucosal healing trends under specific food patterns. Regarding drug recommendations, it obtains a drug recommendation list through weighted integration using machine learning models and the aforementioned prediction results. For dietary advice, it combines association rule mining and Bayesian networks to obtain specific food pattern suggestions, improving the targeting and patient suitability of dietary management, and enhancing the transparency and safety of clinical decision-making.

The invention discloses a user semi-quantitative dietary habit self-evaluation and automatic report generation system based on images and texts, and belongs to the technical field of health management and text generation. Obtaining the sum of intake frequency and parts of each type of food input by the user after comparison with the reference standard reference graph as questionnaire result data; based on questionnaire result data, evaluating the rationality of a diet structure through principal component analysis, including balanced diet score and high-processing night diet score, and predicting individual future obesity occurrence and progress risk indexes by using a deep learning algorithm; a diet evaluation report including questionnaire result data, balanced diet scores, high-processing night diet scores, obesity occurrence and progress risk indexes and diet suggestions is generated and uploaded to a hospital information management system for viewing, and the system has the advantages of high efficiency, convenience, comprehensiveness, accuracy, real-time synchronization, high applicability and the like.

The present application is directed to a system which integrates advanced scientific methods, and artificial intelligence (AI) enabled software, applications and algorithms to assess and optimize health impacts of existing consumables and theoretical consumable formulations, artificial and natural ingredients, and associated bio-functional effects, for purposes of generating actionable Relevant Nutrition Scores (RNS's). RNS AI-enabled software, algorithms and applications, systems & methods analyze comprehensive food information, food preparation practices, additives, preservatives and packaging by weighting user-aligned inputs. RNS supports global product assessments inclusive of health benefits, opportunities and risks, dietary choices, food innovations, purposeful health certifications, and healing and recovery protocols, achieved through dynamic, multi-dimensional nutritional research and applied health impacts, each and all aligned in support of specific diverse users. System outputs optimize existing, speculative and future consumable formulations, deliberate dietary recommendations, purposeful products production, treatment protocols, and pharmaceutical efficacies, while promoting wellness, disease resilience and natural immunities.