Dietary assessment system and method

• US 8,605,952 B2
• Filed: 12/27/2012
• Issued: 12/10/2013
• Est. Priority Date: 09/05/2008
• Status: Active Grant

• Current Assignee: Purdue Research Foundation (The Trustees of Purdue University (d/b/a Purdue University))
• Original Assignee: Purdue Research Foundation (The Trustees of Purdue University (d/b/a Purdue University))
• Inventors: Boushey, Carol, Delp, Edward John, Ebert, David Scott, Lutes, Kyle DelMar, Kerr, Deborah
• Primary Examiner(s): PHAM, HOA Q
• Application Number:
  US13/728,414
• Publication Number:
  US 20130113933A1
• Time in Patent Office: 348 Days
• Field of Search: 382/110, 382/100, 382/203, 382/286, 382/128, 382/218, 600/593, 600/301, 600/300, 434/127, 434/247, 345/810, 707/709
• US Class Current: 382/110
• CPC Class Codes: A23L 33/30 Dietetic or nutritional methods, e.g. for losing weight A23L33/10 takes precedence
• CPC Class Codes: G06F 18/00 Pattern recognition
• CPC Class Codes: G06V 20/68 Food, e.g. fruit or vegetables

Abstract

The present system and method provides a more precise way to record food and beverage intake than traditional methods. The present disclosure provides custom software for use in mobile computing devices that include a digital camera. Photos captured by mobile digital devices are analyzed with image processing and comparisons to certain databases to allow a user to discretely record foods eaten. Specifically, the user captures images of the meal or snack before and after eating. The foods pictured are identified. Image processing software may identify the food or provide choices for the user. Once a food is identified and volume of the food is estimated, nutrient databases are used for calculating final portion sizes and nutrient totals.

Claims

1. A system for measuring food intake of a user, the system comprising:

a mobile device having a built-in camera, the mobile device being configured to capture a first image including a food item to be eaten by the user; and

a remote server in communication with the mobile device, the remote server being configured to;

receive the first image;

calibrate a size of the food item in the first image;

segment the first image into one or more segmented regions where the food item is located;

identify a food type of the food item in one or more of the segmented regions; and

estimate a volume of the food item using only the one or more segmented regions of the first image.

2. The system of claim 1, the remote server further configured to calculate nutritional information of the food item in the first image and communicate the nutritional information to the mobile device before the user starts eating.

3. The system of claim 1, the mobile device being further configured to provide a user interface input selection for the user to indicate that all food items have been consumed.

4. The system of claim 1 wherein the mobile device receives input from the user and generates a label corresponding to an identity of the food item in the first image based on the input from the user.

5. The system of claim 1, the remote server being further configured to:

identify the food item in the first image with reference to a plurality of images for predetermined food items stored in a memory.

6. The system of claim 1, the camera in the mobile device being further configured to:

generate the first image including a fiducial mark of a predetermined size; and

the remote server being further configured to;

identify the fiducial mark in the first image; and

estimate the volume of the food item based on the predetermined size of the fiducial mark in the first image.

7. The system of claim 1, the remote server being further configured to:

identify nutritional information for the food item in the first image based on the identified food type and the estimated volume of the food item.

8. The system of claim 1 wherein the food item comprises a beverage.

9. The system of claim 1, the mobile device being further configured to:

capture a second image of one or more partially consumed food items with the camera, the second image being captured after the user has eaten; and

the remote server being further configured to;

receive the second image from the mobile device;

calibrate a size of a partially consumed food item in the second image, the partially consumed food item corresponding to the food item in the first image;

segment the second image into one or more segmented regions where the partially consumed food item is located;

estimate a volume of the partially consumed food item using only the segmented regions of the second image; and

identify a volume of food eaten by the user with reference to a difference between the estimated volume of food from the first image and the estimated volume of the partially consumed food from the second image.

10. the system of claim 9, the remote server being further configured to:

identify a food type of the partially consumed food item in one or more of the segmented regions of the second image.

11. A system for measuring food intake of a user comprising:

a processor configured to;

receive a first image including image data of a food item prior to the food item being eaten;

calibrate a size of the food item in the first image;

segment the first image into one or more segmented regions where the food item is located;

identify a food type of the food item in one or more of the segmented regions; and

estimate a volume of the food item using only the one or more segmented regions of the first image.

12. The system of claim 11, the processor being further configured to:

calculate nutritional information of the food item in the first image and generate an output of the nutritional information for display with an electronic device that generated the first image.

13. The system of claim 11, the processor being further configured to:

receive a second image including image data of the food item after a portion of the food item has been eaten;

calibrate a size of a partially consumed food item in the second image, the partially consumed food item corresponding to the food item in the first image;

segment the second image into one or more segmented regions where the partially consumed food item is located;

estimate a volume of the partially consumed food item using only the segmented regions of the second image; and

identify a volume of food eaten by the user with reference to a difference between the estimated volume of food from the first image and the estimated volume of the partially consumed food from the second image.

14. the system of claim 13, the processor being further configured to:

identify a food type of the partially consumed food item in one or more of the segmented regions of the second image.