38 results about "Nutrition analysis" patented technology

The invention discloses a personalized medical health service recommendation system based on big data analysis, and belongs to the technical field of medical health services. The synchronization module is used for generating a standardized data stream according to dynamic blood glucose monitoring data and an original heart rate variability signal; the analysis module is used for generating a diet time sequence data stream according to the intake event timestamp; the blood glucose feature extraction module is used for extracting data from the standardized data stream; the insulin sensitivity analysis module is used for generating an insulin sensitivity factor matrix; the nutrition analysis module is used for generating a carbohydrate equivalent time distribution vector and a dietary fiber intake intensity value; the feature fusion module is used for generating a fusion feature vector according to the blood glucose drift trend coefficient, the insulin sensitive factor matrix and the carbohydrate equivalent time distribution vector; the risk assessment module is used for generating a hypoglycemia risk probability value according to the fusion feature vector; and the recommendation generation module is used for generating a personalized service recommendation set according to the hypoglycemia risk probability value.

The invention discloses a nutrition recipe intelligent generation system and method, and belongs to the technical field of nutrition information processing and intelligent recommendation. The system is suitable for individual nutrition management of individuals of all ages, and particularly, optimization design is carried out for infant stages of 0-72 months. The system intelligently generates a personalized nutrition recipe based on individual basic information, growth indexes, nutrition standards, available food materials, user preferences and feedback and other multi-dimensional data, and supports nutrition intake evaluation and dynamic optimization. The system comprises core modules of data input, nutritional requirement calculation, recipe generation, nutrition analysis and interactive display and the like, and expands and supports functions of sensitization screening, regional and seasonal adaptation, work and rest linkage, family sharing and the like. Through fusion of individual growth data and environmental conditions, the system realizes scientific and high-adaptability nutrition recommendation, improves feeding convenience and intervention accuracy, and has a wide application prospect.

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 invention relates to the technical field of computer vision, and discloses a catering consumption automatic settlement method based on image recognition, and the method comprises the steps: obtaining multi-scale image data through a multi-level image quality evaluation and self-adaptive preprocessing technology; target detection and instance segmentation are realized by adopting hierarchical feature extraction and dish template matching; carrying out dish three-dimensional measurement and volume calculation based on a stereoscopic vision and shape recovery method; realizing classification and identification of dishes through multi-modal feature fusion and an attention mechanism; performing nutrient component analysis and health assessment based on nutrition database matching and image feature analysis; and intelligent settlement is realized through price calculation, nutrition statistics, intelligent recommendation and settlement processing. According to the invention, dish identification, nutrition analysis and dynamic pricing can be rapidly completed, and a complete technical solution is provided for intelligent catering service.

The application discloses a formula food operation and management device based on human-computer interaction technology, which comprises a human-computer interaction module, a nutrition analysis module, a formula food screening module and a formula food mixing module which are connected in communication. The detailed health information collected by the human-computer interaction module can provide highly personalized nutrition matching information through the nutrition analysis module, so that the postoperative patient can obtain the most suitable nutrition supply for recovery needs. For special nutritional needs that cannot be met directly through standard full-nutrition formula food, the formula food screening module can be combined with a nutrient component matching prediction model to dynamically generate customized nutrient component mixing matching parameters, thereby solving the problem that it is difficult to configure under the traditional method.

According to the daily diet nutrition analysis method based on the wireless weighing record, the intelligent nutrition scale can collect the food weight and conduct peeling calculation, and the net diet weight is accurately obtained. Through peeling calculation, weight interference of non-food parts such as containers can be eliminated, it is ensured that data uploaded to a cloud analysis background is the real food weight, and a foundation is laid for follow-up accurate nutrition analysis. The cloud analysis background can record the data in time and bind the data with the user ID, so that the diet data of each user can be independently stored and managed, and subsequent personalized nutrition analysis and health management for the user are facilitated. After the cloud analysis background records the data, a nutrition analysis notice or a food type selection input notice is sent to the user terminal in time. The timely notification mechanism can improve the participation degree and the response speed of the user, and ensures that the whole nutrition analysis process is efficiently carried out. The user can quickly log in the cloud analysis background to perform subsequent operation according to the notification, and waiting time is shortened.

This invention relates to the technical field of dietary nutrition analysis, and discloses an intelligent integrated machine and method for automatically collecting and calculating the nutritional content of dishes in real time. The method includes the following steps: identifying various ingredients and weighing them, recording their raw weight; weighing and recording the cooked weight of the finished dish after cooking; weighing and recording the types and weights of seasonings and cooking oil used during cooking in real time; and calculating the content of a certain nutrient element per 100 grams of the cooked dish using the raw weight of the ingredients, the cooked weight of the dish, and the weights of the seasonings and cooking oil used in cooking. This invention provides an intelligent integrated machine and method for automatically collecting and calculating the nutritional content of dishes in real time, which can accurately calculate the calories and nutritional content of various nutrients in the cooked dish.

The invention provides a food recognition and calorie estimation method and system based on a YOLOv8 model, and the method comprises the steps: inputting a food image, detecting food in the image in real time based on the YOLOv8 model, recognizing the type of the food, combining the cooking mode and component information of the food, and dynamically calculating the calorie content. The functions of accurately identifying the food in the meal scene and efficiently estimating the calorie are realized. According to the method, the detection precision is greatly improved while the advantage of detection speed is reserved, and the problems that a traditional target detection method is prone to background interference and low in recognition accuracy in meal recognition are effectively solved. According to the method, the practical application capability of the model in a specific scene is greatly improved, and a reliable basis is provided for subsequent calorie estimation and personalized health intervention. The method has high robustness, transportability and real-time performance, is suitable for various intelligent terminals and edge computing platforms, can be widely applied to the fields of intelligent restaurants, nutrition analysis, health management and the like, and has good popularization prospects and industrialization value.

The invention provides a pregnant and lying-in woman health dynamic monitoring system and method based on big data, and relates to the technical field of data processing, and the method comprises the steps: inputting the physiological data of a pregnant and lying-in woman, the doctor's advice information and the current pregnancy period into a health planning model, and obtaining standard energy consumption and standard nutrition parameters; obtaining current-day exercise data and current-day diet data of the pregnant and lying-in woman; on the basis of the current-day exercise data, the physiological data and the current pregnancy period, the current-day energy consumption of the pregnant and lying-in woman is determined; inputting the daily diet data and the standard nutrition types into a nutrition analysis model to obtain daily intake parameters corresponding to each standard nutrition type; comparing the energy consumption of the day with standard energy consumption to obtain an exercise monitoring result of the pregnant and lying-in woman; and comparing the daily intake parameter corresponding to each standard nutrition type with the standard intake parameter corresponding to each standard nutrition type to obtain a nutrition monitoring result of the pregnant and lying-in woman. The accuracy of the health assessment result of the pregnant and lying-in woman can be improved.

An object of a system according to an embodiment is to propose an appropriate nutrient or food ingredient for a physical disorder of a user.SOLUTION: A system according to an embodiment includes a malfunction selector, a nutrient analyzer, an ingredient selector, and a recipe suggester. The bad condition selection unit selects a bad condition of the body that the user wants to improve. The nutrient analyzer analyzes necessary nutrients based on the poor condition selected by the poor condition selector. The ingredient selection unit selects an ingredient that supplements the nutrient analyzed by the nutrient analysis unit. The recipe proposal unit proposes a recipe using the ingredients selected by the ingredient selection unit.SELECTED DRAWING: Figure 1

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 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.

Disclosed herein is a system and method are provided for rapid, high-throughput phenotyping of nutritional traits in plants using mid-infrared (MIR) spectroscopy and chemometric modeling. One or more processors control MIR sensors to capture spectral images of plant material, which are analyzed using a chemometric model, such as partial least squares regression, to determine characteristics including protein, fatty acids, dietary fiber, starch, resistant starch, sulfur-containing amino acids, and digestibility. The method supports non-destructive analysis with minimal sample preparation and is applicable to a wide range of plant species and biological materials. Results can be stored in a local or cloud database and visualized through a graphical user interface. The chemometric models may be trained and validated using K-fold cross validation and can include spectral preprocessing and interpolation filters. This enables rapid, cost-effective nutritional analysis to support plant breeding, food quality assessment, and industrial applications.

The invention provides a food nutritional ingredient analysis method and system based on a palm proportion scale, and relates to the technical field of nutrition analys.The method comprises the steps that a palm image of a user is collected to extract a plurality of hand size parameters, and a size reference set is constructed; then collecting an image containing food and a palm of a user, and identifying a current gesture state, a food contour and a dining scene in the image through a computer vision technology; according to the recognized gesture state, corresponding hand size parameters are dynamically matched from the size reference set to serve as a proportional scale; calculating the actual physical size of the food and further determining the actual weight of the food based on the proportional scale and the food contour; and finally, generating a personalized food nutritional ingredient analysis result in combination with the dining scene, the actual weight and the cooking additive parameters. According to the invention, the technical problem of low accuracy of food identification and nutrition analysis in the prior art is solved, and the accuracy of food actual weight and nutrition intake estimation is remarkably improved.

A decision support system that aids healthcare practitioners in making more informed clinical decisions and avoiding errors related to diagnosis and treatment of diseases. The system utilizes several data points from the patient history and clinical findings input by the patient and the doctor, to help the doctor make a more accurate diagnosis and develop a more informed treatment plan that incorporates not just drugs and procedures, but also dietary and lifestyle interventions. A system of the present disclosure comprises dosage calculator, symptom checker, differential diagnosis, drug interaction checker, side effect checker, nutritional analyzer and drug-food interaction checker input pathways and corresponding database compartments. Output data is generated in correspondence with patient input data and stored on a database server, where it is correlated with patient outcomes over time and improved through machine learning.

This invention discloses an intelligent nutritional analysis food weighing device based on artificial intelligence, belonging to the field of intelligent weighing equipment technology. The device consists of a weighing base module, a supporting column module, and an intelligent display terminal module. The base is a Φ220mm milky-white acrylic thin disc, housing a built-in four-quadrant high-precision weighing sensor and main control board, achieving accurate weighing from 0-5kg / 1g. The column is a Φ30mm×300mm smooth cylinder, with internal cable channels, an independent acoustic cavity speaker, and a noise-reducing microphone array, supporting long-distance voice interaction up to 1.5 meters. The top 4-inch IPS touchscreen is tilted back 10°, integrating an AI recognition chip and a 2-megapixel camera, equipped with a CNN deep learning model, capable of recognizing over 3000 foods within 1.5 seconds. This invention achieves integrated weighing, recognition, calculation, interaction, and management, offering high precision, simple operation, a pleasant appearance, and strong adaptability, making it widely applicable to scenarios such as postpartum care centers, hospital nutrition departments, rehabilitation institutions, and family health management.

The invention relates to the technical field of meal ordering management, in particular to an enterprise employee meal ordering management system based on big data, which comprises a meal nutrition demand determination module for determining meal nutrition demands through a nutrition analysis model according to historical meal data and personal information of employees, the nutrition analysis model is established on the basis of an improved CNN-GRU-Attention network architecture; the candidate food determining module is used for selecting candidate food from the ordering food nutrition library through an improved clustering algorithm according to the food nutrition requirements; the heat distribution module is used for determining the heat distribution proportion of multiple meals on the day according to the personal information of the employees, and determining a recommended meal sequence in the candidate meal through a meal determination model based on a genetic algorithm; and the meal ordering management module displays the recommended meal sequence when the employees order meals, and uses the meal ordering results of the employees to update the historical meal data. According to the invention, personalized nutritional requirements of employees are met, and the employees are helped to keep diet balance and a better working state.

The application provides a molybdenum-based polyoxometalate-hemin composite nanomaterial and a preparation method and application thereof, and the method comprises the following steps: under room temperature conditions, molybdenum-based polyoxometalate and hemin are mixed by means of manual grinding, and then the obtained mixture is sequentially subjected to centrifugal separation, washing and vacuum drying, so that a solid-phase molybdenum-based polyoxometalate-hemin composite nanomaterial is prepared. 12 The nanocomposite material is synthesized by a simple manual grinding method, and is prepared through the steps of room temperature grinding, centrifugal separation, washing and vacuum drying without the need of complex equipment, high temperature and high pressure or toxic organic solvents. 12 The colorimetric sensor constructed by the nanocomposite material can rapidly and accurately quantitatively detect the AA content in fresh fruits, and has a wide application prospect in the fields of food nutrition analysis, quality control and on-site detection.

The invention provides a catering recommendation method and system based on personal nutrition intake, and the method comprises the steps: S1, constructing a nutrition analysis model, and obtaining a target nutrition intake parameter according to the nutrition analysis model; s2, meal nutrition intake parameters are obtained according to the user meal data; s3, analyzing to obtain recommended nutrition intake parameters; s4, analyzing to obtain a dish component recommendation coefficient, a dish side dish recommendation coefficient and a dish first recommendation coefficient of the existing dish; s5, according to the restaurant geographic position of the restaurant corresponding to the existing dishes and the user position data, obtaining a second dish recommendation coefficient of the existing dishes; and S6, analyzing to obtain a comprehensive dish recommendation coefficient of the existing dishes, obtaining a dish recommendation sequence of the existing dishes according to the comprehensive dish recommendation coefficient, and forming a catering recommendation scheme of the target user according to the dish recommendation sequence and the restaurant geographic positions of the existing dishes. According to the invention, the comprehensiveness and accuracy of the catering recommendation result are improved.

The invention provides a digital nutrition service pushing method and system based on a diabetic patient, and the method comprises the steps: firstly obtaining the real-time monitoring log data, containing blood glucose level data, insulin injection records and diet intake information, of the diabetic patient, inputting the real-time monitoring log data into a pre-trained nutrition analysis model, and carrying out the multi-dimensional processing; the method comprises the following steps: generating a dynamic nutrition demand characteristic representing a nutrient element demand change trend in a preset time period, matching the dynamic nutrition demand characteristic with service entries in a digital nutrition database, determining a candidate nutrition service set and sorting, and performing spatial correlation analysis on a real-time geographic position of a patient and a position of a service provider to obtain a real-time geographic position of the patient. According to the method and the system, a reachable target nutrition service subset is screened out, finally, the reachable target nutrition service subset is sent to a patient terminal device according to a pushing strategy, service selection feedback is received to trigger a service execution instruction, and personalized and reachable digital nutrition service accurate pushing is realized.

The invention discloses a food nutrition analysis method based on a multi-modal large model, and belongs to the technical field of natural language processing. According to the method, a multi-modal model is trained by using an image-nutritional ingredient contrast data set, and a plurality of key nutritional indexes such as carbon water, fat, fiber, calorie, protein, salt, saturated fat and sugar are automatically deduced from a single picture. The technical innovation comprises multi-source data fusion, that is, a unified multi-modal feature space is constructed in combination with food picture features and nutrition database data; end-to-end regression prediction is carried out, that is, an image is directly used as input, and a plurality of continuous numeric nutrition indexes are output instead of being only limited to category identification; the interpretability is enhanced, that is, the relationship between an image area concerned by the model and nutrition prediction is displayed through an attention mechanism or a visualization tool, and the user credibility is improved; and performing personalized adaptation, namely dynamically adjusting prediction and recommendation strategies of the model in combination with historical diet records and health targets of the user.

The invention relates to an intelligent canteen health management system and management method based on multi-source data analysis, and the system comprises an identification perception system, an acquisition system, a data processing system, and a nutrition analysis system. The identification perception system is arranged above a dining table of a canteen and is used for identifying specific dishes and surrounding environment; the identified and perceived dishes are collected, the collected data are uploaded to the data processing system to be processed and analyzed, and finally a report is generated through the analyzed conclusion. According to the invention, global data connection and dynamic decision engine can be realized, a closed-loop service architecture is adopted as a whole, an end-edge-cloud three-level response system is constructed, and the data acquisition rate is improved.

The invention relates to the technical field of health management, in particular to a CLIP-based diet recognition and nutrition analysis method, which comprises the following steps: acquiring and preprocessing diet data to obtain a preprocessed diet data set; constructing a CLIP multi-task model, and performing initial training on the CLIP multi-task model by using the labeled diet data to obtain a trained CLIP multi-task model; based on the trained CLIP multi-task model, performing optimization training through an active learning strategy by using unlabeled diet data to obtain an optimized CLIP multi-task model; and analyzing an input diet image by using the optimized CLIP multi-task model, and outputting a diet category identification result and a nutritional ingredient prediction result. According to the method, the CLIP model is constructed, optimization training is carried out in combination with an active learning strategy, and the recognition precision and nutrition prediction accuracy of the model in a complex diet scene are remarkably improved.

The invention belongs to the technical field of biological nutrition analysis, and discloses application of principal component analysis in comprehensive grading of nutrition and functional components of sea cucumbers. The method comprises the steps of data standardization, covariance matrix calculation, eigenvalue and eigenvector calculation of a covariance matrix, eigenvalue sorting and dimension reduction operation, principal component analysis coefficient establishment, component matrix table construction and principal component analysis to obtain a final score. According to principal component analysis, more indexes with high correlation are synthesized and then recombined into a group of new comprehensive indexes which are mutually independent and small in correlation, under the condition that the number of the indexes is reduced, original index information is reserved, high interpretability is achieved, and analysis is more accurate and objective compared with single index analysis.

The invention discloses a nutrition analysis and diagnosis and treatment decision support system based on artificial intelligence, and the system comprises a data preprocessing module which is used for carrying out the formatting and standardization processing of collected diet pictures and health record information; the dietary image segmentation module is used for carrying out edge detection and segmentation on the standardized dietary image; the dietary feature extraction module is used for respectively extracting dietary picture features and health record features through a substream neural network; the feature fusion module is used for fusing the dietary picture features and the health record features; the feature optimization module is used for optimizing a substream neural network structure and weight parameters by adopting an ant algorithm; the nutritional ingredient analysis module is used for analyzing the nutritional ingredient condition of the user based on the fused joint features; and the personalized diagnosis and treatment decision module is used for generating a personalized nutrition analysis report and diagnosis and treatment suggestions in combination with the user health archive and the nutritional ingredient analysis result. Nutrition analysis and diagnosis and treatment are provided for the user.

1. Name of the product in this design: Graphical User Interface for Nutritional Analysis of Electronic Equipment. 2. Intended use of this design: for use in an electronic device. 3. The key design features of this product are its graphical user interface in electronic devices. 4. The image or photo that best illustrates the design points: Interface change state diagram 2. 5. Purpose of the graphical user interface: This graphical user interface is used for student nutrition analysis; the main view is the homepage after logging into the home-school management system. Clicking "More" in the middle of the main view will take you to interface state diagram 1. Clicking "Nutrition Analysis" in interface state diagram 1 will take you to interface state diagram 2. Clicking "Nutrition Analysis" in interface state diagram 2 will take you to interface state diagram 3 to view the student's nutrition analysis report at school.

The invention provides a food health analysis method and a computer program product, and relates to the technical field of large language models. Firstly, at least one original packaging image of to-be-detected food is obtained; then determining core element information of the food to be detected based on all the original packaging images; and finally, based on the core element information, determining a compliance analysis result and a nutrition analysis result of the to-be-detected food. The method can help a user to automatically evaluate the safety and nutrition of food, and improves the user experience.

The invention provides a nutrition information processing method of an intelligent voice food scale, a food scale, a program product and a storage medium, and relates to the technical field of intelligent health equipment. The processing module is responsible for coordinating operation of each functional module. After the weighing module acquires weight information and the voice module acquires a voice signal, when the network is normal, the processing module sends the weight information and the voice signal to the cloud server, a nutrition analysis report is generated according to a voice signal analysis result and the weight information through analysis and database resources of the cloud server and is transmitted back and displayed, and the cloud advantage is fully played to guarantee that the information is comprehensive and accurate. When the network is interrupted, the processing module generates a basic nutrition value through voice signal recognition and weight information processing based on a local database, so that a user can also have reference when no network exists. The display is updated after network recovery, and latest information is provided for the user at any time. The user does not need manual complex input and only reports the food types through voice, the obtaining process is simplified, and the efficiency is improved.

The application discloses a kind of nutrition with quantity recipe and nutrition analysis method and system of campus student meal. The method comprises: establishing "recipe-set meal-dish-raw material" four-level recipe data model and "raw material-commodity" mapping model, and built-in 《WS / T554-2017 student meal nutrition standard》And food nutrition database;User is based on week view Configuration daily meal set meal and dish, and set estimated number of diners;System is based on dish raw material consumption, real-time cascade calculation dish, set meal and corresponding meal nutrient content, and automatically check whether it conforms to the nutrition standard of the age and gender of the meal student. At the same time, according to the number of diners, the total consumption of each raw material required is automatically summarized and calculated, and is converted into estimated purchase quantity in units of grams, jin, kilograms;Finally, daily / weekly nutrition analysis report covering five dimensions of food category intake, nutrient intake, three meals energy proportion, energy source distribution and protein source distribution is automatically generated. The application realizes the precision, dynamic and automation of student meal nutrition catering, significantly improves the scientificity of recipe compilation and the accuracy of procurement plan.

The invention relates to the technical field of food detection and nutrition analysis, in particular to a nutrient component analysis method and system based on strawberry mineral detection, and the method comprises the steps: obtaining a strawberry sample mineral content data set, and carrying out preliminary component distribution detection, key element recognition, synergistic relationship calculation and multi-dimensional feature fusion. And a nutritional ingredient evaluation coefficient is obtained by using a pre-trained nutritional ingredient analysis model. Through precise mineral substance detection and dynamic fertilization regulation and control, the problem of lack of real-time mineral substance detection and dynamic fertilization optimization in the prior art is solved, efficient analysis and evaluation of nutritional ingredients of strawberries are realized, and the method has a relatively high agricultural application value.