Dynamic nutrition tracking utensils

• US 9,939,312 B2
• Filed: 08/27/2015
• Issued: 04/10/2018
• Est. Priority Date: 04/13/2015
• Status: Active Grant

• Current Assignee: Umar Rahim Bakhsh
• Original Assignee: Umar Rahim Bakhsh
• Inventors: Bakhsh, Umar Rahim
• Primary Examiner(s): VILLECCO, JOHN M
• Application Number:
  US14/838,153
• Publication Number:
  US 20160296053A1
• Time in Patent Office: 957 Days
• CPC Class Codes: A47G 21/02 Forks; Forks with ejectors; Combined forks and spoons; Salad servers
• CPC Class Codes: A47G 21/023 Forks; Forks with ejectors
• CPC Class Codes: A47G 21/04 Spoons; Pastry servers
• CPC Class Codes: A47G 2200/08 Illumination
• CPC Class Codes: A47G 2200/186 meter; timer
• CPC Class Codes: A47G 2200/22 Weight
• CPC Class Codes: A47G 23/12 Consumption counters combined with table-ware or table-service
• CPC Class Codes: B26B 11/008 comprising electronic or electrical features, e.g. illuminating means, computing devices or sensors
• CPC Class Codes: B26B 3/02 Table-knives B26B9/02 takes precedence
• CPC Class Codes: G01G 19/4146 for controlling caloric intake, e.g. diet control
• CPC Class Codes: G01G 19/56 combined with handles of tools or household implements
• CPC Class Codes: G09B 19/0092 Nutrition
• CPC Class Codes: G09B 5/02 with visual presentation of the material to be studied, e.g. using film strip

Abstract

Systems, methods, and computer-readable media are disclosed for dynamic nutrition tracking with utensils. In an example embodiment, a food consumption utensil may include a handle portion, a food loading portion adjacent to the handle portion, the food loading portion having a first surface and a second surface, and a controller positioned within the handle portion. The food consumption utensil may include an accelerometer positioned within the handle portion and in communication with the controller, and a force measurement device configured to measure a force imparted at the first surface of the food loading portion.

Claims

1. A method comprising:

receiving, by one or more computer processors coupled to at least one memory, a first user input from a user indicative of a meal event initiation;

identifying a first food item;

receiving first accelerometer data indicative of a first gesture;

associating the first gesture with the first food item;

identifying a second food item;

receiving second accelerometer data indicative of a second gesture;

associating the second gesture with the second food item;

detecting a motion event;

determining that the motion event corresponds to the first gesture;

triggering, based at least in part on the motion event, a force measurement;

determining a weight based at least in part on force data from the force measurement;

identifying nutritional information associated with the first food item;

automatically determining that a food consumption event is complete based at least in part on a change in force; and

determining consumed nutrition values based at least in part on the weight and the nutritional information associated with the first food item.

2. The method of claim 1, further comprising:

causing a perceptible feedback event after detecting that the motion event corresponds to the first gesture associated with the first food item.

3. The method of claim 2, wherein the perceptible feedback event is a vibrational feedback event.

4. The method of claim 1, further comprising:

determining an image;

wherein identifying the first food item comprises identifying the first food item based at least in part on the image.

5. The method of claim 1, wherein automatically determining that the food consumption event is complete based at least in part on the change in force comprises automatically determining that the food consumption event is complete based at least in part on the change in force to substantially zero force.

6. The method of claim 1, further comprising:

processing an image using image pattern recognition.

7. The method of claim 1, further comprising:

determining that the meal event is complete; and

determining total meal nutritional data based at least in part on food consumption event data during the meal event.

8. A device comprising:

at least one memory that stores computer-executable instructions; and

at least one processor configured to access the at least one memory and execute the computer-executable instructions to;

determine a first user input from a user indicative of a meal event initiation;

determine a first food item;

determine first accelerometer data indicative of a first gesture;

associate the first gesture with the first food item;

determine a second food item;

determine second accelerometer data indicative of a second gesture;

associate the second gesture with the second food item;

detect a motion event;

determine that the motion event corresponds to the first gesture;

cause, based at least in part on the motion event, a force measurement;

determine a weight based at least in part on force data from the force measurement;

determine nutritional information associated with the first food item;

determine that a food consumption event is complete based at least in part on a change in force; and

determine consumed nutrition values based at least in part on the weight and the nutritional information associated with the first food item.

9. The device of claim 8, wherein the at least one processor is further configured to access the at least one memory and execute the computer-executable instructions to:

cause a perceptible feedback event after detecting that the motion event corresponds to the first gesture associated with the first food item.

10. The device of claim 9, wherein the perceptible feedback event is a vibrational feedback event.

11. The device of claim 8, wherein the at least one processor is further configured to access the at least one memory and execute the computer-executable instructions to:

determine an image.

12. The device of claim 8, wherein the at least one processor is further configured to access the at least one memory and execute the computer-executable instructions to:

determine that the meal event is complete; and

determine total meal nutritional data based at least in part on food consumption event data during the meal event.

13. A method comprising:

determining, by one or more computer processors coupled to at least one memory, a first user input from a user indicative of a meal event initiation;

determining a first food item;

determining first accelerometer data indicative of a first gesture;

associating the first gesture with the first food item;

determining a second food item;

determining second accelerometer data indicative of a second gesture;

associating the second gesture with the second food item;

detecting a motion event;

determining that the motion event corresponds to the first gesture;

causing, based at least in part on the motion event, a weight measurement;

determining nutritional information associated with the first food item;

determining that a food consumption event is complete based at least in part on a change in weight; and

determining consumed nutrition values based at least in part on the weight and the nutritional information associated with the first food item.

14. The method of claim 13, further comprising:

causing a perceptible feedback event after detecting that the motion event corresponds to the first gesture associated with the first food item.

15. The method of claim 14, wherein the perceptible feedback event is a vibrational feedback event.

16. The method of claim 13, further comprising:

determining that the meal event is complete; and

determining total meal nutritional data based at least in part on food consumption event data during the meal event.

17. The method of claim 13, further comprising:

determining an image.

18. The method of claim 17, further comprising:

processing the image using image pattern recognition.

19. The method of claim 17, further comprising:

determining that the food consumption event is complete based at least in part on a change in weight comprises automatically determining that the food consumption event is complete based at least in part on the change in weight to substantially zero weight.

20. The method of claim 17, further comprising:

determining that an elapsed time between consecutive food consumption events is less than a threshold length of time; and

generating a slow down notification.