Technology-Assisted Dietary Assessment

Abstract

Dietary intake provides valuable insights for mounting intervention programs for prevention of disease. With growing concern for adolescent obesity, the need to accurately measure diet becomes imperative. Assessment among adolescents is problematic as this group has irregular eating patterns and have less enthusiasm for recording food intake. Preliminary studies among adolescents suggest that innovative use of technology may improve the accuracy of diet information from young people. In this paper, we propose a novel food record method using a mobile device that will provide an accurate account of daily food and nutrient intake among adolescents. Our approach includes the use of image analysis tools for identification and quantification of food consumption. Images obtained before and after food is consumed can be used to estimate the diet of an individual. In this paper we describe our initial results and indicate the potential of the proposed system.

Figure 1

Examples of input techniques for use with mobile device food record (a) Using the tree method to select a food item from the database, (b) Using the search method to select a food item from the database, (c) Using the tree method to mark digital pictures with a food item in the database and (d) Using the search method to mark digital pictures with a food item in the database.

Figure 2

Additional input devices and labels for use with mobile device food record (a) Using stylus to hand write notes to label food items in a digital picture of a meal, (b) Using the an onscreen tree method to label food items in a digital picture of a meal, (c) Using an onscreen keyboard to search for a food item from the database and (d) A labeled meal and not shown are the secondary prompts for dressing on salad and spread on bread.

Figure 3

A Typical Image of a Meal.

Figure 4

Image Analysis System.

Figure 5

Example of segmented food items (a) Food Item Segmented Using a Fix Threshold (T = 127), (b) Additional Food Item Segmented Using Color Information.

Figure 6

Example of classified food items (a) All food items are successfully classified using a SVM, (b) Some food items are misclassified by the SVM, i.e. beef roast is misclassified as steak.