Literature DB >> 22020443

An Overview of The Technology Assisted Dietary Assessment Project at Purdue University.

Nitin Khanna1, Carol J Boushey, Deborah Kerr, Martin Okos, David S Ebert, Edward J Delp.   

Abstract

In this paper, we describe the Technology Assisted Dietary Assessment (TADA) project at Purdue University. Dietary intake, what someone eats during the course of a day, provides valuable insights for mounting intervention programs for prevention of many chronic diseases such as obesity and cancer. Accurate methods and tools to assess food and nutrient intake are essential for research on the association between diet and health. An overview of our methods used in the TADA project is presented. Our approach includes the use of image analysis tools for identification and quantification of food that is consumed at a meal. Images obtained before and after foods are eaten are used to estimate the amount and type of food consumed.

Entities:  

Year:  2010        PMID: 22020443      PMCID: PMC3183748          DOI: 10.1109/ISM.2010.50

Source DB:  PubMed          Journal:  ISM


  17 in total

1.  Portion-size estimation training in second- and third-grade American Indian children.

Authors:  J L Weber; L Cunningham-Sabo; B Skipper; L Lytle; J Stevens; J Gittelsohn; J Anliker; K Heller; J L Pablo
Journal:  Am J Clin Nutr       Date:  1999-04       Impact factor: 7.045

2.  Validity of reported energy expenditure and energy and protein intakes in Swedish adolescent vegans and omnivores.

Authors:  Christel L Larsson; Klaas R Westerterp; Gunnar K Johansson
Journal:  Am J Clin Nutr       Date:  2002-02       Impact factor: 7.045

Review 3.  Evaluation of dietary assessment instruments against doubly labeled water, a biomarker of habitual energy intake.

Authors:  J Trabulsi; D A Schoeller
Journal:  Am J Physiol Endocrinol Metab       Date:  2001-11       Impact factor: 4.310

Review 4.  Evaluation of dietary assessment instruments in adolescents.

Authors:  Helaine R H Rockett; Catherine S Berkey; Graham A Colditz
Journal:  Curr Opin Clin Nutr Metab Care       Date:  2003-09       Impact factor: 4.294

5.  Longitudinal changes in the accuracy of reported energy intake in girls 10-15 y of age.

Authors:  Linda G Bandini; Aviva Must; Helene Cyr; Sarah E Anderson; Jennifer L Spadano; William H Dietz
Journal:  Am J Clin Nutr       Date:  2003-09       Impact factor: 7.045

6.  Low accuracy and low consistency of fourth-graders' school breakfast and school lunch recalls.

Authors:  Suzanne Domel Baxter; William O Thompson; Mark S Litaker; Francesca H A Frye; Caroline H Guinn
Journal:  J Am Diet Assoc       Date:  2002-03

7.  Automatic portion estimation and visual refinement in mobile dietary assessment.

Authors:  Insoo Woo; Karl Otsmo; Sungye Kim; David S Ebert; Edward J Delp; Carol J Boushey
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2010-01-01

8.  Personal Dietary Assessment Using Mobile Devices.

Authors:  Anand Mariappan; Marc Bosch; Fengqing Zhu; Carol J Boushey; Deborah A Kerr; David S Ebert; Edward J Delp
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2009-01-01

9.  The Use of Mobile Devices in Aiding Dietary Assessment and Evaluation.

Authors:  Fengqing Zhu; Marc Bosch; Insoo Woo; Sungye Kim; Carol J Boushey; David S Ebert; Edward J Delp
Journal:  IEEE J Sel Top Signal Process       Date:  2010-08       Impact factor: 6.856

10.  Who underreports dietary intake in a dietary recall? Evidence from the Second National Health and Nutrition Examination Survey.

Authors:  R C Klesges; L H Eck; J W Ray
Journal:  J Consult Clin Psychol       Date:  1995-06
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  17 in total

1.  Development and evaluation of a short 24-h food list as part of a blended dietary assessment strategy in large-scale cohort studies.

Authors:  J Freese; S Feller; U Harttig; C Kleiser; J Linseisen; B Fischer; M F Leitzmann; J Six-Merker; K B Michels; K Nimptsch; A Steinbrecher; T Pischon; T Heuer; I Hoffmann; G Jacobs; H Boeing; U Nöthlings
Journal:  Eur J Clin Nutr       Date:  2014-01-08       Impact factor: 4.016

2.  Using Smartphone Sensors for Improving Energy Expenditure Estimation.

Authors:  Amit Pande; Jindan Zhu; Aveek K Das; Yunze Zeng; Prasant Mohapatra; Jay J Han
Journal:  IEEE J Transl Eng Health Med       Date:  2015-09-18       Impact factor: 3.316

Review 3.  A Digital Ecosystem of Diabetes Data and Technology: Services, Systems, and Tools Enabled by Wearables, Sensors, and Apps.

Authors:  Nathaniel D Heintzman
Journal:  J Diabetes Sci Technol       Date:  2015-12-20

4.  FOODCAM: A Novel Structured Light-Stereo Imaging System for Food Portion Size Estimation.

Authors:  Viprav B Raju; Edward Sazonov
Journal:  Sensors (Basel)       Date:  2022-04-26       Impact factor: 3.847

5.  Low Complexity Image Quality Measures for Dietary Assessment Using Mobile Devices.

Authors:  Chang Xu; Nitin Khanna; Carol J Boushey; Edward J Delp
Journal:  ISM       Date:  2012-01-09

6.  The CSIRO Healthy Diet Score: An Online Survey to Estimate Compliance with the Australian Dietary Guidelines.

Authors:  Gilly A Hendrie; Danielle Baird; Rebecca K Golley; Manny Noakes
Journal:  Nutrients       Date:  2017-01-09       Impact factor: 5.717

Review 7.  Validity of Dietary Assessment in Athletes: A Systematic Review.

Authors:  Louise Capling; Kathryn L Beck; Janelle A Gifford; Gary Slater; Victoria M Flood; Helen O'Connor
Journal:  Nutrients       Date:  2017-12-02       Impact factor: 5.717

Review 8.  Scaling up Dietary Data for Decision-Making in Low-Income Countries: New Technological Frontiers.

Authors:  Winnie Bell; Brooke A Colaiezzi; Cathleen S Prata; Jennifer C Coates
Journal:  Adv Nutr       Date:  2017-11-15       Impact factor: 8.701

9.  Validity of the Remote Food Photography Method Against Doubly Labeled Water Among Minority Preschoolers.

Authors:  Theresa Nicklas; Rabab Saab; Noemi G Islam; William Wong; Nancy Butte; Rebecca Schulin; Yan Liu; John W Apolzan; Candice A Myers; Corby K Martin
Journal:  Obesity (Silver Spring)       Date:  2017-07-31       Impact factor: 5.002

10.  Comparative Study of the Routine Daily Usability of FoodLog: A Smartphone-based Food Recording Tool Assisted by Image Retrieval.

Authors:  Kiyoharu Aizawa; Kazuki Maeda; Makoto Ogawa; Yohei Sato; Mayumi Kasamatsu; Kayo Waki; Hidemi Takimoto
Journal:  J Diabetes Sci Technol       Date:  2014-02-14
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