Literature DB >> 20656101

Automated camera-phone experience with the frequency of imaging necessary to capture diet.

Lenore Arab1, Ashley Winter.   

Abstract

Camera-enabled cell phones provide an opportunity to strengthen dietary recall through automated imaging of foods eaten during a specified period. To explore the frequency of imaging needed to capture all foods eaten, we examined the number of images of individual foods consumed in a pilot study of automated imaging using camera phones set to an image-capture frequency of one snapshot every 10 seconds. Food images were tallied from 10 young adult subjects who wore the phone continuously during the work day and consented to share their images. Based on the number of images received for each eating experience, the pilot data suggest that automated capturing of images at a frequency of once every 10 seconds is adequate for recording foods consumed during regular meals, whereas a greater frequency of imaging is necessary to capture snacks and beverages eaten quickly. 2010 American Dietetic Association. Published by Elsevier Inc. All rights reserved.

Mesh:

Year:  2010        PMID: 20656101     DOI: 10.1016/j.jada.2010.05.010

Source DB:  PubMed          Journal:  J Am Diet Assoc        ISSN: 0002-8223


  7 in total

1.  An adaptive Hidden Markov model for activity recognition based on a wearable multi-sensor device.

Authors:  Zhen Li; Zhiqiang Wei; Yaofeng Yue; Hao Wang; Wenyan Jia; Lora E Burke; Thomas Baranowski; Mingui Sun
Journal:  J Med Syst       Date:  2015-03-19       Impact factor: 4.460

2.  Acceptability and feasibility of smartphone-assisted 24 h recalls in the Chinese population.

Authors:  Jiajie Zang; Jun Song; Zhengyuan Wang; Chunxia Yao; Jianhong Ma; Cuihua Huang; Zhenni Zhu; Lindsey P Smith; Shufa Du; Jenna Hua; Edmund Seto; Barry M Popkin; Shurong Zou
Journal:  Public Health Nutr       Date:  2015-04-10       Impact factor: 4.022

3.  Automatic food detection in egocentric images using artificial intelligence technology.

Authors:  Wenyan Jia; Yuecheng Li; Ruowei Qu; Thomas Baranowski; Lora E Burke; Hong Zhang; Yicheng Bai; Juliet M Mancino; Guizhi Xu; Zhi-Hong Mao; Mingui Sun
Journal:  Public Health Nutr       Date:  2018-03-26       Impact factor: 4.022

4.  Validation of an Automated Wearable Camera-Based Image-Assisted Recall Method and the 24-h Recall Method for Assessing Women's Time Allocation in a Nutritionally Vulnerable Population: The Case of Rural Uganda.

Authors:  Andrea L S Bulungu; Luigi Palla; Jan Priebe; Lora Forsythe; Pamela Katic; Gwen Varley; Bernice D Galinda; Nakimuli Sarah; Joweria Nambooze; Kate Wellard; Elaine L Ferguson
Journal:  Nutrients       Date:  2022-04-27       Impact factor: 6.706

5.  Feasibility testing of an automated image-capture method to aid dietary recall.

Authors:  L Arab; D Estrin; D H Kim; J Burke; J Goldman
Journal:  Eur J Clin Nutr       Date:  2011-05-18       Impact factor: 4.016

6.  Development and Evaluation of a Web-based Computer-Assisted Personal Interview System (CAPIS) for Open-ended Dietary Assessments among Koreans.

Authors:  Sangah Shin; Eunyoung Park; Dong Han Sun; Tae-Kyoung You; Myung-Joo Lee; Soochan Hwang; Hee Young Paik; Hyojee Joung
Journal:  Clin Nutr Res       Date:  2014-07-29

7.  Alterations in energy balance from an exercise intervention with ad libitum food intake.

Authors:  Katarina Melzer; Anne Renaud; Stefanie Zurbuchen; Céline Tschopp; Jan Lehmann; Davide Malatesta; Nicole Ruch; Yves Schutz; Bengt Kayser; Urs Mäder
Journal:  J Nutr Sci       Date:  2016-03-09
  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.