|Grant Number:||7U01CA130784-05 Interpret this number|
|Primary Investigator:||Boushey, Carol|
|Organization:||University Of Hawaii At Manoa|
|Project Title:||Improving Dietary Assessment Methods Using the Cell Phone and Digital Imaging|
DESCRIPTION (provided by applicant): Dietary intake provides some of the most valuable insights for mounting intervention programs for prevention. However, accurate assessment of diet is problematic. Immerging technology in mobile- telephones (cell phones) with higher resolution pictures, improved memory capacity, and faster processors, allow these devices to process information not previously possible. This project addresses several objectives of RFA-CA-07-032 by using cell phones to capture both visual and recorded detail that is electronically submitted to the researcher; eases respondent burden; and provides accurate estimates of nutrient, food, and supplement intakes. To adequately address these challenges, the research team assembled represents expertise in electrical engineering, computers, information science, nutritional epidemiology, stable isotopes, and statistics. Our goal is to develop, implement, and evaluate a mobile telephone food record (mpFR) that will translate to an accurate account of daily food and nutrient intake among adults. Our first steps include development of imaging software for use with digital photographs that will estimate quantities of foods consumed, modification of the FNDDS nutrient database, and development of user-friendly interfaces. Mobile telephones are widely used throughout the world and can provide a unique mechanism for collecting dietary information that reduces burden on record keepers. Pictures of food can be marked with a variety of input methods that link the item for image processing and analysis for quantification of food consumed. We plan to recruit a sample of adults to consume meals of precisely known composition while using the mpFR under controlled conditions to aid with quantifying the error associated with the food and nutrient output. The users of the mpFR under these controlled conditions will provide feedback for improving the accuracy and ease of use of the mpFR. A convenient sample of 103 free-living, healthy adults between 21 and 70 y will participate in the validation phase where total energy expenditure will be measured over 7 days with doubly labeled water and compared to total energy intake over the same 7 days as estimated from the mpFR. It is anticipated that the outcome of this project will be an innovate tool that can be used in population and clinical based studies to provide accurate dietary intake data.
Merging dietary assessment with the adolescent lifestyle.
Authors: Schap TE, Zhu F, Delp EJ, Boushey CJ
Source: J Hum Nutr Diet, 2014 Jan;27 Suppl 1, p. 82-8.
EPub date: 2013 Mar 13.
Comparison of known food weights with image-based portion-size automated estimation and adolescents' self-reported portion size.
Authors: Lee CD, Chae J, Schap TE, Kerr DA, Delp EJ, Ebert DS, Boushey CJ
Source: J Diabetes Sci Technol, 2012 Mar 1;6(2), p. 428-34.
EPub date: 2012 Mar 1.
Novel technologies for assessing dietary intake: evaluating the usability of a mobile telephone food record among adults and adolescents.
Authors: Daugherty BL, Schap TE, Ettienne-Gittens R, Zhu FM, Bosch M, Delp EJ, Ebert DS, Kerr DA, Boushey CJ
Source: J Med Internet Res, 2012 Apr 13;14(2), p. e58.
EPub date: 2012 Apr 13.
Evaluation of the Food and Nutrient Database for Dietary Studies for use with a mobile telephone food record.
Authors: Six BL, Schap TE, Kerr DA, Boushey CJ
Source: J Food Compost Anal, 2011 Dec 1;24(8), p. 1160-1167.
Segmentation Assisted Food Classification for Dietary Assessment.
Authors: Zhu F, Bosch M, Schap T, Khanna N, Ebert DS, Boushey CJ, Delp EJ
Source: Proc SPIE, 2011 Jan 24;7873, p. 78730B.
Multilevel Segmentation for Food Classification in Dietary Assessment.
Authors: Zhu F, Bosch M, Khanna N, Boushey CJ, Delp EJ
Source: Proc Int Symp Image Signal Process Anal, 2011 Sep 4;null, p. 337-342.
Volume Estimation Using Food Specific Shape Templates in Mobile Image-Based Dietary Assessment.
Authors: Chae J, Woo I, Kim S, Maciejewski R, Zhu F, Delp EJ, Boushey CJ, Ebert DS
Source: Proc SPIE, 2011 Feb 7;7873, p. 78730K.
Adolescents in the United States can identify familiar foods at the time of consumption and when prompted with an image 14 h postprandial, but poorly estimate portions.
Authors: Schap TE, Six BL, Delp EJ, Ebert DS, Kerr DA, Boushey CJ
Source: Public Health Nutr, 2011 Jul;14(7), p. 1184-91.
EPub date: 2011 Feb 16.
COMBINING GLOBAL AND LOCAL FEATURES FOR FOOD IDENTIFICATION IN DIETARY ASSESSMENT.
Authors: Bosch M, Zhu F, Khanna N, Boushey CJ, Delp EJ
Source: IEEE Trans Image Process, 2011;2011, p. 1789-1792.
Development of a Mobile User Interface for Image-based Dietary Assessment.
Authors: Kim S, Schap T, Bosch M, Maciejewski R, Delp EJ, Ebert DS, Boushey CJ
Source: MUM Int Conf Mob Ubiquitous Multimed, 2010 Dec 31;2010, p. 13.
The Use of Mobile Devices in Aiding Dietary Assessment and Evaluation.
Authors: Zhu F, Bosch M, Woo I, Kim S, Boushey CJ, Ebert DS, Delp EJ
Source: IEEE J Sel Top Signal Process, 2010 Aug;4(4), p. 756-766.
Evidence-based development of a mobile telephone food record.
Authors: Six BL, Schap TE, Zhu FM, Mariappan A, Bosch M, Delp EJ, Ebert DS, Kerr DA, Boushey CJ
Source: J Am Diet Assoc, 2010 Jan;110(1), p. 74-9.
Automatic portion estimation and visual refinement in mobile dietary assessment.
Authors: Woo I, Otsmo K, Kim S, Ebert DS, Delp EJ, Boushey CJ
Source: Proc SPIE, 2010 Jan 1;7533, p. null.
AN IMAGE ANALYSIS SYSTEM FOR DIETARY ASSESSMENT AND EVALUATION.
Authors: Zhu F, Bosch M, Boushey CJ, Delp EJ
Source: Proc Int Conf Image Proc, 2010;null, p. 1853-1856.
An Overview of The Technology Assisted Dietary Assessment Project at Purdue University.
Authors: Khanna N, Boushey CJ, Kerr D, Okos M, Ebert DS, Delp EJ
Source: ISM, 2010;null, p. 290-295.
Workshop 1: Use of technology in dietary assessment.
Authors: Winter J, Boushey CJ
Source: Eur J Clin Nutr, 2009 Feb;63 Suppl 1, p. S75-7.
Use of technology in children's dietary assessment.
Authors: Boushey CJ, Kerr DA, Wright J, Lutes KD, Ebert DS, Delp EJ
Source: Eur J Clin Nutr, 2009 Feb;63 Suppl 1, p. S50-7.
Personal Dietary Assessment Using Mobile Devices.
Authors: Mariappan A, Bosch M, Zhu F, Boushey CJ, Kerr DA, Ebert DS, Delp EJ
Source: Proc SPIE, 2009 Jan 1;7246, p. null.
Technology-Assisted Dietary Assessment.
Authors: Zhu F, Mariappan A, Boushey CJ, Kerr D, Lutes KD, Ebert DS, Delp EJ
Source: Proc SPIE, 2008 Mar 20;6814, p. 681411.