80 results about "Meal plan" patented technology

A method, performed by an electronic device, for suggesting meal plans, comprises, obtaining diet information of a user; forming a first subset of meal plans from a predetermined meal plan set according to the diet information; generating a second subset of meal plans from the first subset of meal plans via an evolution algorithm; calculating a score for each meal plan in the second subset of meal plans; ranking meal plans in the second subset of meal plans, wherein the score for each meal plan is calculated based on the diet information and one or more elements comprised in each meal plan.

The system according to the embodiment comprises an acquisition unit, a generation unit, a list generation unit, and a suggestion unit. The acquisition unit acquires health data. The generation unit analyzes the data acquired by the acquisition unit and generates a meal plan according to the user's health condition, goals, preferences, and food allergies. The list generation unit automatically generates a shopping list based on the meal plan generated by the generation unit. The suggestion unit makes suggestions based on the shopping list generated by the list generation unit.

An object of a system according to an embodiment is to propose the best meal for the day near the user's home.SOLUTION: A system includes an information collection unit, an analysis unit, and a proposal unit. The information collection unit collects information on menus, prices, coupons, reviews, and the like of restaurants on the Internet. The analysis unit analyzes the information collected by the information collection unit and calculates the most profitable meal of the day near the home of the user. The suggestion unit suggests the optimal meal plan calculated by the analysis unit to the user.SELECTED DRAWING: Figure 1

We provide the system. [Solution] Information processing means that collects preference information and health information and generates personalized food menus based on this information, Information processing means that collects information on preferences and health, and generates an individualized meal plan based on this information, An interactive interface means that engages with the user in a conversational format and supports their choices using natural language, Route optimization methods to optimize paths and reduce travel time by means of transportation, A means of linking with smart devices to understand the user's exercise and nutritional intake and manage health information, A means of simplifying operations that allows food selection to be repeated with a single instruction, A system that includes this.

An object of a system according to an embodiment is to propose an optimal meal plan based on a health condition and a request of an employee.SOLUTION: A system includes a health data acquisition unit, a request data acquisition unit, an analysis unit, and a proposal unit. The health data acquisition unit acquires health data of employees. The request data acquisition unit acquires employee request data. The analyzer analyzes the data acquired by the health data acquirer and the demand data acquirer. The proposing section proposes a meal plan based on a result of the analysis by the analyzing section.SELECTED DRAWING: Figure 1

An object of a system according to an embodiment is to provide an exercise menu and a meal plan that are personalized according to a training purpose of a user.SOLUTION: A system includes a reception part, a generation part, an analysis part, a proposal part, and a management part. The reception unit inputs a training purpose of a user. The generation unit generates a personalized exercise menu based on the purpose input by the reception unit. The analysis unit analyzes an exercise form of the user on the basis of the exercise menu generated by the generation unit. The proposing section proposes correction on the basis of the exercise form analyzed by the analyzing section. The suggestion unit suggests a meal plan to achieve the goal based on the correction suggested by the suggestion unit. The management unit performs management based on the meal plan proposed by the proposal unit.SELECTED DRAWING: Figure 1

An object of the system according to the embodiment is to individually propose and adjust a diet plan for healthy weight gain for thin people.SOLUTION: A system includes a user information input unit, a meal plan suggestion unit, and a meal plan adjustment unit. The user information input unit inputs detailed information on the user's physical constitution, dietary preferences, and health condition. The meal plan suggestion unit suggests a meal plan based on the information input by the user information input unit. The meal plan adjustment part adjusts the meal plan suggested by the meal plan suggestion part on the basis of the user's physical condition and reaction to the meal.SELECTED DRAWING: Figure 1

1. The name of the design product: graphical user interface for AI-generated recommended recipes for electronic devices. 2. The use of the design product: for electronic devices. 3. The design features of the design product: in the graphical user interface. 4. The picture or photo that best represents the design features: front view. 5. Common design, omit rear view, pitch view, left and right view. 6. The use of the graphical user interface: graphical user interface for AI-generated recommended recipes for electronic devices. The front view is the AI helps me choose function, the interface automatically enters the AI recommended recipe process, and enters the interface state change 1 after the recipe is generated. Interface change state diagram 1 is AI recommended recipes, which will recommend recipes based on cooking preferences, refrigerator ingredients, etc. Users can check the desired recipes, such as interface change state diagram 2, slide the screen up, enter interface change state diagram 3, and users can add selected recipes to the meal plan. If there is no favorite recipe, click "no favorite, try manual search" to enter interface state change 4. Enter the recipe in interface change state diagram 4, enter interface change state diagram 5. Users can select the recipe from the search results to add it to the meal plan, as shown in interface change state diagram 6. The "X" and single color block in the view are changeable text and pictures. Reference can be made to the use state reference diagram 1-5.

The disclosure provides a meal plan specification production system having modular components that can be reused across different meal planning configurations to efficiently produce customized meal plan specifications for many different individuals whose food consumption routines, meal structure customs and meal content preferences vary widely from one individual to the next.

The invention provides a diet matching method and system based on child characteristic expression, and the method comprises the steps: obtaining nutritional ingredients and content range required by a target object based on the characteristic expression information of the target object, determining a food combination based on the nutritional ingredients, and determining the content range of the target object based on the diet preference of the target object; matching the food combination meeting the diet preference of the target object, and generating a diet matching scheme of the target object; a diet matching scheme is dynamically adjusted according to nutritional ingredient intake and residual nutritional requirements required in different stages; according to the method, the dietary scheme is planned according to the characteristic expression of the child, and the dietary scheme is dynamically adjusted at different stages of the child, so that the nutrition intake of the child during hospital stay is ensured, and meanwhile, diet matching is performed based on the diet preference of the child, so that the diet experience of the child is improved, and the goal of promoting rehabilitation by diet is achieved.

An object of a system according to an embodiment is to propose an optimal exercise plan or diet plan to a user.SOLUTION: A system includes a data collection part, an analysis part, an exercise plan suggestion part, and a meal plan suggestion part. The data collection unit collects data from a wearable device, medical examination results, and photographs of meals. The analysis unit analyzes the data collected by the data collection unit. The exercise plan suggestion unit suggests an optimal exercise plan to the user based on the result analyzed by the analysis unit. The meal plan suggestion unit suggests an optimal meal plan to the user on the basis of the result analyzed by the analysis unit.SELECTED DRAWING: Figure 1

The system according to this embodiment aims to provide a customized meal plan based on genetic information. [Solution] The system according to the embodiment comprises a collection unit, an analysis unit, a generation unit, a provision unit, and an upload unit. The collection unit collects genetic information. The analysis unit analyzes the genetic information collected by the collection unit. The generation unit creates a customized meal plan based on the analysis results obtained by the analysis unit. The provision unit provides the meal plan created by the generation unit. The upload unit uploads health checkup results.

An integrated weight management system comprising a biocompatible intraoral device and personalized software is disclosed. The device, configured for insertion into the user's mouth, creates a separation between the tongue and teeth causing the stomatognathic system, limiting hunger cues associated with food anticipation. Sensors coupled to the device detect its removal and insertion, enabling the system to track adherence to meal plans and weight loss progress. The software utilizes machine learning algorithms to generate personalized meal plans, food intake timing, nutrition education, and exercise routines based on user preferences, dietary restrictions, and weight loss goals. The system analyzes user data to provide progress reports, adjust meal plans, and send alerts to promote accountability and compliance. This comprehensive approach addresses both physiological and psychological aspects of weight management, offering a novel and effective solution for achieving and maintaining a healthy weight.

This application discloses a nutritional meal recommendation system, method, equipment, and medium for post-gynecological surgery, relating to the field of digital health management technology and applied to a computer device. It includes: an association matrix acquisition module, used to construct dynamic physiological signs by combining the patient's hormone levels and blood loss after gynecological surgery, and splicing them according to time sequence and the nutritional ratio of candidate ingredients to generate a nutritional metabolism association matrix; an evolution matrix acquisition module, used to perform first-order differentiation and normalization of the matrix in the time dimension to construct a metabolic nutritional evolution feature matrix; a node sequence construction module, used to split feature vectors, construct a heterogeneous graph using gastrointestinal dynamic impedance, and use a graph attention network to screen ingredient nodes to form a sequence of nodes with absorption potential; and a meal plan generation module, used to calculate the nutritional difference in the sequence, extract decreasing topological fragments, and generate an individualized nutritional meal plan adapted to the patient's dynamic physiology and gastrointestinal capacity.

A system for real-time generation of therapeutic meal plans based on predictive analytics of patient profile data including a processor of a therapeutic plan server (TPS) node configured to host a machine learning (ML) module and connected to at least one patient-entity node over a network and a memory on which are stored machine-readable instructions that when executed by the processor, cause the processor to: receive patient profile data from the at least one patient-entity node; parse the patient profile data to derive a plurality of key classifying features; query a local database to retrieve local historical patients-related data based on the plurality of key classifying features; generate at least one classifier feature vector based on the plurality of key classifying features and the local historical patients-related data; provide the at least one feature vector to the ML module coupled to an Artificial Neural Network (ANN); receive a plurality of meal recommendation parameters from a meal plan predictive model generated by the ML module using outputs of the ANN based on the at least one feature vector; and generate a meal plan for the at least one patient-entity node based on the plurality of meal recommendation parameters.

The system according to the embodiment aims to provide a sustainable meal plan based on personal health data. [Solution] A system according to an embodiment includes a collection unit, an analysis unit, a generation unit, and a provision unit. The collection unit collects health data. The analysis unit analyzes the data collected by the collection unit. The generation unit generates a meal plan based on the analysis results obtained by the analysis unit. The provision unit provides the meal plan generated by the generation unit.

Systems, methods, and other embodiments associated with an interactive customizable meal and event planning and management system for facilitating personal organization and planning, e-commerce, social engagement and collaboration, are described. In one embodiment, a method includes generating a customizable plan module of a multi-process meal plan including creating one or more recipe cards, each recipe card includes ingredient, dietary, allergen, or nutritional information, and configuring the at least one recipe card to define a meal component of a plurality of meal components of the multi-process plan, where each defined meal component includes at least one recipe card. The example method may also include displaying partitions for each customizable plan module, each partition corresponding to one meal component, and each partition receiving at least one recipe card for defining a corresponding meal component and retrieving a nutritional information for each recipe card based on the contents of the recipe card.

An artificial intelligence (AI) based system for nutrient estimation, and meal planning comprises a server processor coupled with a database in network communication with a plurality of users connected over the said network. The database stores characteristics that represent physical conditions about the users (e.g. DNA test results, family health history, BMI along with meal patterns, hunger, sleep patterns, and food habits). The database coupled with the said server processor includes a diet plan dataset, and an ingredient nutritional information dataset. The server processor is operable to generate a meal profile for each of the users, wherein each meal profile comprises a plurality of individual characteristics representative of the user's physical condition. The system analyses the stored characteristics, and recommended nutritional intake levels to generate at least one meal plan.

The system according to the embodiment aims to propose an optimal meal plan based on an individual's health condition and to suggest how to arrange ingredients and how to cook them. [Solution] A system according to an embodiment includes a collection unit, an analysis unit, a proposal unit, an arrangement unit, and a presentation unit. The collection unit collects health status values. The analysis unit analyzes the values ​​collected by the collection unit. The proposal unit proposes an appropriate meal plan based on the analysis results obtained by the analysis unit. The arrangement unit arranges the necessary ingredients based on the meal plan proposed by the proposal unit. The presentation unit presents cooking methods based on the meal plan proposed by the proposal unit.

We provide the system. [Solution] A means for the user to input a meal menu, A means of sending the meal menu entered by the user to the server, A method for the server to analyze the received meal menu and identify deficient nutrients, A means for generating a meal plan to supplement the nutrient deficiencies identified by the server, A means of providing the user with a meal menu generated by the server, A method for searching for and suggesting supermarkets or restaurants based on the user's location information, A system that includes this.

The application discloses a kind of personalized nutrition meal intelligent recommendation method, device, equipment and storage medium.The method comprises: obtaining the basic health information of target object, reference favorite menu and blood glucose monitoring data;According to the pre-established food material library and menu library, determine the target associated entity of reference favorite menu;According to the pre-established food material-menu-component knowledge graph and target associated entity, the candidate favorite menu is obtained by multidimensional reasoning to reference favorite menu;According to the correlation degree and feature matching degree of candidate favorite menu and reference favorite menu and the adaptation degree of candidate favorite menu and food material taboo, candidate favorite menu is screened to obtain potential favorite menu;Based on basic health information and blood glucose monitoring data, potential favorite menu is checked by multilayer rule, and daily meal plan is recommended for target object according to the checking result.This scheme can solve the problems of low recommendation accuracy and poor scientific adaptability, and realize the scientific and accurate recommendation of GDM pregnant women diet.

To solve problems related to household chores such as daily meal planning, ingredient ordering and delivery, and reducing dishwashing, by providing an AI-based meal suggestion system that efficiently and economically supports household chores.SOLUTION: An AI-based meal suggestion system for efficiently and economically supporting household chores, comprises: means for suggesting multiple meal plans each week; means for satisfying a condition that ingredient costs stay within "○○ yen" per meal; means for efficiently supporting the needs of boxed lunches for children; means for ordering and delivering ingredients online on the basis of the suggested meal plans; means for displaying recipe video; means for limiting the number of plates to the number that fits a single use of a dishwasher; and means for checking nutritional balance on a daily, weekly, and monthly basis.SELECTED DRAWING: Figure 1

To provide a system that allows users to read QR codes during shopping in supermarkets, search for recipes on the basis of the QR codes, and use the recipes as a reference for shopping.SOLUTION: In a data processing system comprising a data processing apparatus 12 and a smart device 14, the specific processing by a specific processing unit 290 of the data processing apparatus 12 includes the steps of: reading a QR code with a camera using a dedicated application installed on a mobile device such as a smartphone or tablet; searching for a recipe on the basis of the QR code and allowing a user to instantly refer to recipes that use the product; and retrieving price information of the product from a POS system and calculating the total cost of the meal plan when the user adds the products necessary for the selected recipe to a shopping cart.SELECTED DRAWING: Figure 2

A method of facilitating culturally-authentic and non-repetitive meal planning. The method includes receiving a meal planning request data, receiving a user meal history data, identifying a candidate meal data set, selecting a candidate meal data from the candidate meal data set, validating the candidate meal data against a cuisine signature data by executing a tri-level validation, rejecting the candidate meal data when the tri-level validation fails, classifying the candidate meal data as an authentic candidate meal data when the tri-level validation passes, and repeating the selecting, validating, rejecting, and classifying for each day of the multi-day planning duration.

We provide the system. [Solution] An information input means for the user to input their meal history and physiological data, A data analysis means that analyzes input information and evaluates nutritional status, A plan generation means that automatically generates a meal plan using food available from the nearest food service provider based on the analysis results, An information display means that presents the generated meal plan to the user and provides instructions to immediately place an order, A system that includes this.

An object of a system according to an embodiment is to efficiently propose a meal plan and a recipe in accordance with nutritional needs and dietary restrictions of a user.SOLUTION: A system includes a nutrition data analysis part, a meal plan suggestion part, a recipe suggestion part, a purchase / delivery support part, and a conversation support part. The nutrition data analysis unit analyzes nutrition data and food allergy information of the user. The meal plan suggestion unit suggests a customized meal plan based on the information analyzed by the nutrition data analysis unit. The recipe suggester suggests a personalized recipe based on the meal plan suggested by the meal plan suggester. The purchase / delivery support unit supports purchase and delivery of necessary food materials based on the recipe proposed by the recipe proposal unit. The dialogue support unit supports improvement of a daily diet through a dialogue with the AI.SELECTED DRAWING: Figure 1

The system according to this embodiment aims to provide an optimal training menu and meal plan based on the user's vital data, lifestyle habits, and ideal body image. [Solution] The system according to the embodiment comprises a data collection unit, an analysis unit, and a provision unit. The data collection unit collects the user's vital data, lifestyle habits, and ideal body image. The analysis unit analyzes the data collected by the data collection unit and generates an optimal training menu and meal plan for the user. The provision unit provides the training menu and meal plan generated by the analysis unit.

To manage nutrition for the elderly.SOLUTION: A system for managing nutrition for the elderly includes means for AI to create a balanced meal plan based on information supervised by a specialized nutritionist, taking into consideration the health condition, preferences, and nutritional needs of the elderly, means for making meal suggestions and monitoring a nutritional status, and means for delivery personnel to check on concerns and safety.SELECTED DRAWING: Figure 1

A system for generating personalized health food scores for one or more participants and / or group of participants (such as a household) based on participant data including microbiome data of each participant. In some cases, the system may generate recommended meal plan options based on the available food items, the participant data for each member of a group.

An object of a system according to an embodiment is to centrally manage and efficiently provide information and support regarding childcare.SOLUTION: A system according to an embodiment includes a support information providing unit, a medical information management unit, a meal plan suggestion unit, a growth record management unit, a communication promotion unit, an education support unit, and an information transfer unit. The support information providing section provides support information of the local government body. The medical information management part unitarily manages medical information in cooperation with the mother-child notebook. The meal plan suggestion unit suggests a meal plan according to the lifestyle of the user and the growth stage of the child. The growth record management unit manages a growth record of the child. The communication promotion unit promotes communication between parents and manages a joint schedule. The education support unit performs education support for children. The information inheriting unit inherits its own information when the child grows up.SELECTED DRAWING: Figure 1