Passive tracking and prediction of food consumption

• US 10,049,598 B1
• Filed: 10/14/2014
• Issued: 08/14/2018
• Est. Priority Date: 10/11/2013
• Status: Active Grant

• Current Assignee: Zipongo, Inc.
• Original Assignee: Zipongo, Inc.
• Inventors: Langheier, Jason, Schwartz, Greg
• Primary Examiner(s): Thai, Xuan
• Assistant Examiner(s): Shirley, Kristen
• Application Number:
  US14/514,287
• Time in Patent Office: 1,400 Days
• Field of Search: 434127
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/4866 Evaluating metabolism A61B5/083 takes precedence
• CPC Class Codes: A61B 5/4872 Body fat
• CPC Class Codes: G09B 19/0092 Nutrition
• CPC Class Codes: G09B 5/00 Electrically-operated educational appliances working with questions and answers G09B7/00; simulators G09B9/00; advertising or displaying in general G09F

Abstract

A passive nutrition tracking service automatically tracks food consumption over time for a user and for populations from a variety of food consumption sources, including food purchase input such as grocery loyalty shopping card data, restaurant dining data, estimates of food consumption within a household, estimates of free food intake and estimates of food pantry use. The tracking service also passively tracks and uses total energy expenditure information for the user, which describes the physical activity level, muscle and fat gain, and optionally waste output of the user. The tracking service analyzes the food consumption and user energy expenditure information and generates a food dietary history for the user, which includes calories and nutrient consumption estimated based on the analysis. The tracking service also generates a variety of personalized healthy lifestyle recommendations based on the analysis and presents the dietary history and personalized healthy lifestyle recommendations to the user.

Claims

1. A computer-implemented method comprising:

receiving loyalty information from a client device of a user of a tracking system, the loyalty information indicating that the user belongs to a loyalty program of a grocery store;

receiving grocery information from a first computer server associated with the loyalty program, the grocery information describing a first plurality of food items that the user acquired at the grocery store;

receiving restaurant information from a second computer server associated with a restaurant, the restaurant information describing a second plurality of food items that the user acquired at the restaurant, the restaurant information determined based on dish information programmed onto radio-frequency identification (RFID) tags coupled to receptacles each configured to contain at least one of the food items of the second plurality of food items;

estimating a third plurality of food items included in a pantry of the user based on average pantry food item consumption according to survey responses of a population of users of the tracking system and a family size of the user;

determining, using a database table including mappings of food items to numbers of calories, a total number of calories consumed by the user based at least in part on the first plurality of food items, the second plurality of food items, and the third plurality of food items;

determining an energy expenditure of the user using sensor data from a physical activity tracker of the user and estimates based on activity of the population of users of the tracking system; and

providing a recommendation based at least in part on the total number of calories consumed by the user and a number of calories used by the user according to the energy expenditure for display on the client device.

2. The computer-implemented method of claim 1, further comprising:

receiving, from a wireless transceiver, device information of the client device; and

determining that the user acquired the second plurality of food items in response to determining that the device information is associated with the user.

3. The computer-implemented method of claim 1, further comprising:

receiving free food consumption information from the client device indicating a fourth plurality of food items, different than the first plurality of food items, the second plurality of food items, and the third plurality of food items consumed by the user; and

wherein determining the total number of calories consumed by the user is further based on the fourth plurality of food items.

4. The computer-implemented method of claim 1, further comprising:

determining a nutrient information based on the first plurality of food items, the second plurality of food items, and the third plurality of food items, the nutrient information indicating an intake level of the user of at least one of sodium, fat, and cholesterol during a predetermined period of time; and

wherein the recommendation is further based on the nutrient information.

5. The computer-implemented method of claim 4, further comprising:

determining that the intake level of the user is greater than a threshold value based on a recommended daily allowance; and

wherein the recommendation indicates that the user should reduce the intake level.

6. The computer-implemented method of claim 1, further comprising:

receiving user information describing demographic data of the user;

receiving population level norms describing recommended nutrient and caloric intake levels; and

wherein determining the total number of calories consumed by the user is further based on the demographic data and the population level norms.

7. The computer-implemented method of claim 6, wherein the user information further describes genetic data of the user, and wherein the recommended nutrient and caloric intake levels are associated with other users having similar demographic data or genetic data with the user.

8. The computer-implemented method of claim 1, wherein the population of users of the tracking system shares similar demographic characteristics as the user.

9. A non-transitory computer readable medium storing executable computer program instructions that, when executed by a processor, cause the processor to:

receive loyalty information from a client device of a user of a tracking system, the loyalty information indicating that the user belongs to a loyalty program of a grocery store;

receive grocery information from a first computer server associated with the loyalty program, the grocery information describing a first plurality of food items that the user acquired at the grocery store;

receive restaurant information from a second computer server associated with a restaurant, the restaurant information describing a second plurality of food items that the user acquired at the restaurant, the restaurant information determined based on dish information programmed onto radio-frequency identification (RFID) tags coupled to receptacles each configured to contain at least one of the food items of the second plurality of food items;

estimating a third plurality of food items included in a pantry of the user based on average pantry food item consumption according to survey responses of a population of users of the tracking system and a family size of the user;

determine, using a database table including mappings of food items to numbers of calories, a total number of calories consumed by the user based at least in part on the first plurality of food items, the second plurality of food items, and the third plurality of food items;

determine an energy expenditure of the user using sensor data from a physical activity tracker of the user and estimates based on activity of the population of users of the tracking system; and

provide a recommendation based at least in part on the total number of calories consumed by the user and a number of calories used by the user according to the energy expenditure for display on the client device.

10. The computer-readable storage medium of claim 9, having further instructions that when executed by the processor cause the processor to:

receive, from a wireless transceiver, device information of the client device; and

determine that the user acquired the second plurality of food items in response to determining that the device information is associated with the user.

11. The computer-readable storage medium of claim 9, having further instructions that when executed by the processor cause the processor to:

receive free food consumption information from the client device indicating a fourth plurality of food items, different than the first plurality of food items, the second plurality of food items, and the third plurality of food items consumed by the user; and

wherein determining the total number of calories consumed by the user is further based on the fourth plurality of food items.

12. The computer-readable storage medium of claim 9, having further instructions that when executed by the processor cause the processor to:

determine a nutrient information based on the first plurality of food items, the second plurality of food items, and the third plurality of food items, the nutrient information indicating an intake level of the user of at least one of sodium, fat, and cholesterol during a predetermined period of time; and

wherein the recommendation is further based on the nutrient information.

13. The computer-readable storage medium of claim 12, having further instructions that when executed by the processor cause the processor to:

determine that the intake level of the user is greater than a threshold value based on a recommended daily allowance; and

wherein the recommendation indicates that the user should reduce the intake level.

14. The computer-readable storage medium of claim 9, having further instructions that when executed by the processor cause the processor to:

receive user information describing demographic data of the user;

receive population level norms describing recommended nutrient and caloric intake levels; and

wherein determining the total number of calories consumed by the user is further based on the demographic data and the population level norms.

15. The computer-readable storage medium of claim 14, wherein the user information further describes genetic data of the user, and wherein the recommended nutrient and caloric intake levels are associated with other users having similar demographic data or genetic data with the user.

16. The computer-readable storage medium of claim 9, wherein the population of users of the tracking system shares similar demographic characteristics as the user.

17. A method comprising:

receiving loyalty information from a client device of a user of a tracking system, the loyalty information indicating that the user belongs to a loyalty program of a grocery store;

receiving grocery information from a first computer server associated with the loyalty program, the grocery information describing a first plurality of food items that the user acquired at the grocery store;

receiving restaurant information from a second computer server associated with a restaurant, the restaurant information describing a second plurality of food items that the user acquired at the restaurant, the restaurant information determined based on dish information programmed onto radio-frequency identification (RFID) tags coupled to receptacles each configured to contain at least one of the food items of the second plurality of food items;

estimating a third plurality of food items included in a pantry of the user based on average pantry food item consumption according to survey responses of a population of users of the tracking system and a family size of the user;

determining, using a database table including mappings of food items to numbers of calories, a total number of calories consumed by the user based on the first plurality of food items, the second plurality of food items, and the third plurality of food items;

determining an energy expenditure of the user using sensor data from a physical activity tracker of the user and estimates based on activity of the population of users of the tracking system;

predicting a daily intake of a plurality of nutrients of the user based on a correlation with the total number of calories and a number of calories used by the user according to the energy expenditure;

modifying a dietary history of the user based on the total number of calories and the predicted daily intake of the plurality of nutrients; and

providing a customized health feedback generated based on the dietary history to the client device for display to the user.

18. The method of claim 17, further comprising:

receiving free food consumption information from the client device indicating a fourth plurality of food items, different than the first plurality of food items, the second plurality of food items, and the third plurality of food items consumed by the user; and

wherein determining the total number of calories consumed by the user is further based on the fourth plurality of food items.

19. The system of claim 17, wherein the dietary history of the user indicates that a daily intake of a nutrient of the plurality of nutrients is lower than a threshold value, and wherein the customized health feedback includes a recommendation indicating that the user should consume a greater amount of the nutrient.

20. The method of claim 17, wherein the population of users of the tracking system shares similar demographic characteristics as the user.