61 results about "Meal plan" patented technology

A novel system and methodology for dietary and medical treatment planning wherein meals and treatment plans are specifically individualized for a user according to a number of unique characteristics associated with that user. These characteristics are provided to the system of the present invention and one or more resulting meal plans and/or therapies are generated. According to the present invention, particular dieter specific characteristics that may be considered in developing the meal plan include daily caloric limitations and or recommendations, daily nutritional requirements including minimum and maximum vitamin, mineral, water, and electrolyte intake as well as specific genetic characteristics concerning the individual. Dieter food preferences and other factors may also be considered. The system of the present invention uses this dieter specific information to generate one or more meal plans for that dieter in connection with an ingredient, food, supplement, drug and recipe database containing a universe of foods, supplements, and drugs available for generating meals and treatment plans in accordance with the diet. The system of the present invention may function as a standalone application or it may be web-based wherein users may access the application on a server accessible through the internet or some other public or private network.

A system for personalized meal planning is provided which includes a client device and a meal planning center configured to communicate with the client device and to receive a customer's information, including a weight designator, a gender designator, a goal designator, and an activity level designator. The meal planning center includes a storage device and a processing unit. The storage device is configured to store recipe template files having an ingredient designator and a plurality of recipe rule factors, which include a nutrient contribution value, a minimum ingredient value, and a maximum ingredient value. A plurality of recipe rule factors are each assigned to each ingredient designator. The processing unit is configured to determine a nutritional allowance based upon the customer information and to create a recipe that satisfies the nutritional allowance by using the recipe rule factors assigned to the ingredient. The meal planning center is further configured to transmit the recipe to the client device.

An individualized system and method of mass diagnosis and treatment of obesity that is optionally configurable for a plurality of patients and health providers. Computer and relational data storage systems are used for operating a computer program and a secure web site on an internet. User profiles are assigned for accessing the secure web site using a plurality of computer terminals. Patient data and information are gathered for use in a health risk analysis to determine values for variables in a caloric energy equation. An individualized health provider web page is used to administer a meal plan, an exercise plan and an education plan to influence variables in the caloric energy equation to derive an individualized caloric energy deficit and a starvation response threshold in the patient. Patient compliance information is gathered for use in the health risk analysis and for correlation with the stored data to re-derive the variables.

A system and method for method defining, creating, and managing meals according to user preferences regarding a diet plan, preferred foods, preferred meal preparation options, and meal times. An expert system uses information about an individual's diet preferences and related goals, to develop a personalized plan including a complete meal plan and to generate meal suggestion messages for each meal. Meal suggestion messages are transmitted to users' portable devices at their preferred meal times. If a user accepts a meal suggestion, nutritional information regarding the accepted meal is tracked and considered in determining the user's progress toward a goal. If a user rejects a meal suggestion, the expert system generates a meal substitute suggestion or a specific food item substitute suggestion. When the user accepts the substitute suggestion, nutritional information regarding the substituted meal or food item is tracked and considered in determining the user's progress toward a goal.

A meal plan is generated based on user health data, goals and other information. The data regarding user health goals, eating habits, current health condition, and eating preferences is accessed. A user meal plan is then generated based on at least a portion of the accessed information. The meal plan may be modified based on user selected substitutions, automatically generated substitutions, or in some other manner. When the meal plan is modified, information related to the meal plan is updated.

Methods, systems, apparatus and computer-readable mediums, storing sets of instructions, provide for determining at least one meal combination including receiving, at a server, information identifying at least one food item; accessing, from a storage, device, a set of meal combination rules; applying, at the server, the accessed set of meal combination rules to a plurality of food items; determining, at the server, at least one meal combination including a plurality of food items including the food item identified by the received information; and transmitting the determined at least one meal combination from the server to a computing device for display. Alternatively, methods, systems, apparatus and computer-readable mediums, storing sets of instructions, provide for generating a meal plan, including accessing a set of meal plan rules; applying the set of meal plan rules to a plurality of food items; determining a plurality of meal combinations, each of the plurality of meal combinations including a plurality of food items, based on the applied set of rules; and transmitting the determined plurality of meal combinations from a server device to a computing device.

Disclosed is a method for managing obesity, diabetes, hair loss, aging, cardiovascular, or other blood glucose-spike-induced diseases by reducing the post-prandial blood glucose spike, or the glucose shock. The blood glucose spike, or the glucose shock is reduced by generating a person-specific glucose profile for at least one significant meal to tune or train a blood glucose model (kinetic, artificial intelligence or hybrid), and then using the tuned or the trained model embedded in a computation-capable electronic device to compute and recommend a person-specific meal plan and an exercise plan, including semi-continuous meal ingestion and post-meal exercise while sitting at home or office. Advantages over prior art are that the method uses less strenuous exercise with no or less medicine, is person-specific, quantitative and more suitable for use by an individual, a dietician, or a health care practitioner.

System and method for identifying, measuring and analyzing food nutritional values and consumer eating behaviors is disclosed. A food container, having weight sensors and food identification sensors, identifies weight, type, and preparation status of the food item being consumed by the user from the food container. Based on the identified information, the nutritional value of the food item is determined and observed. The food container in communication with the system components may provide the user a recommended meal plan to improve the user's health condition. In addition, the food container issues an alert to the user when the user puts too much, too less, or the right amount of food items in the food container or eats the food items too fast.

A system for facilitating the control of body weight of a user includes a hand-held computing device having weight control software executing thereon for maintaining a meal plan for the user. The hand-held computing device includes a comprehensive information database having comprehensive information relating to a plurality of at least one of foods, exercises and meals stored thereon, a favorites information database having favorites information relating to at least one of favorite foods, favorite exercises and favorite meals of the user stored thereon, the favorites information being a subset of the comprehensive information, a display operable to present to the user the meal plan and the favorites information, and an input/output device operable to provide an interface for the user to operate the weight control software in order to select at least one favorite food, favorite exercise or favorite meal from the favorites information so as to manipulate the meal plan.

Some embodiments of the invention provide a system which creates and delivers a meal plan to a user. The meal plan may be customized to suit the user, by drawing from recipes in the user's personal collection, and by enabling the user to specify goals relating to nutrition, budget, preparation time, etc. Once approved by the user, a meal plan may serve as a basis for a shopping list which includes items called for by recipes in the meal plan, and/or other items. The shopping list may form the basis for a delivery order submitted to a grocery provider, if the user so desires. As such, embodiments of the invention may enable the user to avoid expending the time and mental energy conventionally associated with planning meals and shopping for their ingredients.

Various methods and systems are provided for meal planning. In one example, a method for meal planning includes receiving a user's meal preferences and automatically generating a meal plan including a plurality of separate meals based on the user's meal preferences.

Disclosed are a method for providing a meal plan using a refrigerator, and a refrigerator using the same. The method for providing a meal plan using a refrigerator comprises: storing information on food materials stored in a refrigerator; receiving personal information related to a user's health status; updating pre-stored personal information based on the received personal information; generating a reference meal plan based on the stored food material information, such that a plurality of replaceable dishes are included in the reference meal plan; providing a priority of the personal information based on input personal information and a user's selection; generating a meal plan by correcting the reference meal plan, such that dishes cooked with ingredients beneficial to personal information having a high priority are included in the reference meal plan; and providing a meal plan for a special day or a predetermined time period according to a user's selection, wherein at least part of dishes included in the meal plan includes one or more replaceable dishes.

A method, apparatus, and computer usable program product for generating meal plans based on a set of nutritional policies. The process determines nutritional requirements specified by a set of nutritional policies in response to receiving a request for a set of meal plans for a set of users. The set of nutritional policies correspond to the set of users. The process identifies a set of potential meal plans in response to determining the nutritional requirements specified by the set of nutritional policies. Each potential meal plan in the set of potential meal plans satisfies all nutritional requirements for the set of nutritional policies. The process generates a listing of ingredients required by the selected meal plan that is unavailable in a current inventory in an amount required by the selected meal plan, in response to receiving a selection of a potential meal plan to form a selected meal plan.

A personalized meal planning method is provided. The method utilizes a food clustering technique to generate personalized meal plans. The method provides a food clustering stage and a food matching stage. The food clustering stage includes the following steps: input a personal nutrient goal; set a weight and a necessity value for each target nutrient feature; generate food clusters by applying a clustering algorithm; compute food ranking; and provide a diet recommendation. The food matching stage includes the following steps: select a food item to be replaced; determine a threshold of target similarity; and provide at least one replaceable food item. A personalized meal planning system is also provided.

A customer profile for each user of a plurality of users is generated based on purchase history and reception of meals by the each user. A preferential fabric for each user is generated based on attributes of ingredients and dishes preferred by the user according to the user's customer profile. Users are clustered together according to the similarities of the preferential fabrics thereof. A sample product is selected based on its attributes having a high correspondence to the preferential fabrics of the users of a cluster. The sample product is transmitted to a portion of the users of the cluster and a response thereto is evaluated. In response to positive reception, direct shipment of the sample product to the cluster is invoked, bypassing a retail store. The sample product may therefore have a shelf life shorter than required to stock the sample product in a conventional retail store.