26 results about "Nutrition analysis" patented technology

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.

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 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 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 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 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.

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 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 medical health and intelligent diet management, in particular to an intelligent diet intervention system based on real-time food recognition and blood glucose analysis. Comprising a food identification module for collecting food images, identifying food types and extracting image feature information; the nutrition analysis module is used for calculating nutritional ingredients and carbohydrate content based on the food identification result; the blood glucose processing module is used for collecting, calibrating and analyzing continuous blood glucose data and generating blood glucose trend information; the prediction decision-making module is used for predicting the blood glucose change according to the nutrition data and the blood glucose information and generating a personalized intervention scheme; and the data management module executes data storage, encryption protection, information display and user interaction. The complete intelligent diet intervention system is formed by organically combining real-time food recognition, nutrition analysis, blood sugar processing, blood sugar prediction, intervention decision making and data management, and real-time monitoring and dynamic management of postprandial blood sugar changes of the user are achieved.

An object of a system according to an embodiment is to efficiently manage the contents of a refrigerator and reduce food waste while maintaining the balance of meals.SOLUTION: A system according to an embodiment includes an ingredient recognition unit, a recipe suggestion unit, a nutrient analysis unit, an ingredient ordering unit, and a food waste reduction unit. The food recognition unit recognizes the contents of the refrigerator. The recipe proposal unit proposes a recipe suitable for the mood and health goal of the day on the basis of the ingredient recognized by the ingredient recognition unit. The nutrition analysis unit analyzes the nutritional components of the recipe proposed by the recipe proposal unit and checks the balance of the meal. The ingredient ordering unit orders necessary ingredients based on the result checked by the nutrition analysis unit. The food waste reduction unit manages the use-by date of the ingredient recognized by the ingredient recognition unit and makes a proposal for reducing the food waste.SELECTED DRAWING: Figure 1

A computer-implemented method for facilitating purchases includes receiving a shopping list input from a user, and processing the shopping list input, identifying a plurality of desired products, determining an associated quantity of each of the plurality of desired products, and querying a plurality of distinct retailer data sources to obtain product data for each of the plurality of desired products. The querying is performed in parallel via API integrations with each of the plurality of distinct retailer data sources. The method includes aggregating and normalizing the product data retrieved from the plurality of distinct retailer data sources into a unified data set of a plurality of candidate products for the plurality of desired products. The method includes evaluating the plurality of candidate products using a recommendation algorithm and selecting a plurality of recommended products.

The invention provides a nutrition measurement and diet recommendation platform and method based on a multi-modal large language model, and the platform comprises an input information obtaining module which is used for obtaining word information, statement information and / or picture information inputted by a user in a plurality of target input regions, and is used for analyzing the word information, statement information and / or picture information, and sending the analyzed word information, statement information and / or picture information to a user terminal; determining at least one target food type and food quantity; the nutrition analysis module is used for determining the nutrient element quantity and the dynamic evaluation result of the user according to the at least one target food type and the food quantity, and is used for determining the health risk index of the user according to the nutrient element quantity and the dynamic evaluation result of the user; the health propaganda and education module is used for providing nutrition and health knowledge content; and the diet recommendation module is used for generating highly personalized diet suggestions according to the nutrient element quantity and the dynamic evaluation result of the user, the personal physiological parameters and the health targets. And intelligence, individuation and convenience of nutrition and health management are improved.

The embodiment of the present disclosure provides a kind of machine learning-based heart failure patient remote volume management method and system, comprising: collecting multi-source data, accurately identifying and nutrition analysis to diet image by deep learning model, combine the time trend analysis of physiological monitoring data and the professional evaluation of clinical test data, construct multilevel prediction model, realize the accurate prediction of volume overload risk;Automatic generation of graded warning information according to risk level, and matching individualized intervention scheme is pushed to mobile application terminal.The embodiment of the present disclosure can effectively improve the self-management ability of heart failure patients, realize early intervention of volume problem.

The present invention belongs to the fields of computer vision, deep learning and intelligent catering management, and specifically relates to a method for detection and identification of Chinese dishes in a complex environment. The present invention provides the method for detection and identification of Chinese dishes in a complex environment. On the basis of an improved YOLOv8 architecture and in combination with an attention mechanism, the method is endowed with the capability of performing efficient detection and identification in complex dining table environments, and can output the category and bounding box information of each dish in real time, thus solving the problems of multi-target Chinese dish detection and image classification in complex scenarios; and the method achieves automatic calculation of the calorie values of dishes, and provides comprehensive solutions for smart dish ordering and nutrition analysis, and thus has a broad application prospect.

The invention belongs to the technical field of big language models, and particularly relates to a big language model-based diet guidance chat system, which comprises a user interaction layer, a data processing layer, a model layer and a data storage layer, the input mode comprises a text input box, a voice input button and an image uploading area, a user describes diet related problems and self health conditions in the text input box, after clicking the voice input button, needs are transmitted to the system through speaking, by means of the image uploading area, the user uploads food pictures, and output is presented through image-text display and voice broadcast. Personalized diet suggestions, recipe recommendation and nutrition analysis results generated by the system can be displayed on an interface in an image-text form. The system adopts a modular design, can easily integrate other functions, such as exercise suggestion and health monitoring, and is high in expandability, so that the system can be applied to wider scenes.