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Grant Details

Grant Number: 5R21CA172864-02 Interpret this number
Primary Investigator: Baranowski, Tom
Organization: Baylor College Of Medicine
Project Title: Minimizing Memory Errors in Child Diet Assessment
Fiscal Year: 2014
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DESCRIPTION (provided by applicant): Sun ASA24-Kids Accurate assessment of dietary intake is important for 1) evaluating the outcome of dietary change interventions, 2) assessing the relationship between diet and health outcomes (e.g., obesity, metabolic syndrome), 3) identifying factors (e.g. environmental, psychosocial) influencing dietary intake which could be targeted in change programs, and 4) assessing diet changes over time (called surveillance). Our research revealed 35% of the foods children reported consuming the previous day were imaginary (called intrusions: observers did not see those foods consumed) and 15% were forgotten (called omissions: foods observers recorded, but were not reported by the children). This level of error needs to be minimized to enhance children's dietary intake assessment accuracy. Pictures of actual meals served, and after consumption, should minimize intrusions and omissions. Problems with the smart phone method of taking meal pictures for children, however, are it requires remembering to carry and use the smart phone correctly at the right time, even in social circumstances (e.g., with certain friends) when child reticence, even embarrassment, may minimize some children's willingness to draw that kind of attention to themselves. Dr. Mingui Sun (U Pittsburgh) has developed a multisensory unit, the e.button, attached to the shirt, which includes a camera, battery and storage to record pictures of everything in front of a child at 2 to 10 second intervals throughout the day. The Sun System requires a trained research assistant to identify the foods, and use of an on screen malleable wire mesh feature to estimate amounts consumed (taking about 10 min/day of images), which are in turn verified by a nutrition/dietetics professional (taking about five min/day of images). Limits of this system are that many foods are hard to recognize in a photo (e.g., poor lighting, odd angle, unusual food, unusual preparation or presentation of the food). Similar problems will occur with an automated system using pattern recognition to identify the foods. The child who consumed the foods, alternatively, should be able to recognize an image of the foods without much difficulty. The ASA24-Kids, adapted to children's abilities from the Automated Self-Administered 24 hour recall (ASA24) for adults, enables children to self-report what they consumed the previous day. Combining the Sun System with ASA24-Kids may permit recording children's dietary intake that minimizes the limitations of child's 24 hour memory by providing images of the foods consumed, yet allows child review of foods in the images. While the feasibility of using an automated image capture method for dietary assessment has been established among adults, parallel work has not been done among children. As a result, we propose creating Sun-ASA24-Kids, adapting it to child abilities, and validating it in a field study. The Sun-ASA24-Kids system could minimize two major sources of child reporting error, and unclear picture errors.

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A Hierarchical Deep Fusion Framework for Egocentric Activity Recognition Using a Wearable Hybrid Sensor System.
Authors: Yu H. , Pan G. , Pan M. , Li C. , Jia W. , Zhang L. , Sun M. .
Source: Sensors (Basel, Switzerland), 2019-01-28; 19(3), .
EPub date: 2019-01-28.
PMID: 30696100
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Utility of eButton images for identifying food preparation behaviors and meal-related tasks in adolescents.
Authors: Raber M. , Patterson M. , Jia W. , Sun M. , Baranowski T. .
Source: Nutrition journal, 2018-02-24; 17(1), p. 32.
EPub date: 2018-02-24.
PMID: 29477143
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Application of Intelligent Recommendation Techniques for Consumers' Food Choices in Restaurants.
Authors: Li X. , Jia W. , Yang Z. , Li Y. , Yuan D. , Zhang H. , Sun M. .
Source: Frontiers in psychiatry, 2018; 9, p. 415.
EPub date: 2018-09-04.
PMID: 30233432
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Improved method of step length estimation based on inverted pendulum model.
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Source: International journal of distributed sensor networks, 2017 Apr; 13(4), .
EPub date: 2017-04-10.
PMID: 29910697
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Testing the effects of narrative and play on physical activity among breast cancer survivors using mobile apps: study protocol for a randomized controlled trial.
Authors: Lyons E.J. , Baranowski T. , Basen-Engquist K.M. , Lewis Z.H. , Swartz M.C. , Jennings K. , Volpi E. .
Source: BMC cancer, 2016-03-09; 16, p. 202.
EPub date: 2016-03-09.
PMID: 26960972
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Authors: Xin M. , Zhang H. , Wang H. , Sun M. , Yuan D. .
Source: Neurocomputing, 2016-02-20; 178, p. 87-102.
EPub date: 2015-11-10.
PMID: 29290647
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Might Video Games Help Remedy Childhood Obesity?
Authors: Baranowski T. .
Source: Childhood obesity (Print), 2015 Aug; 11(4), p. 331-4.
EPub date: 2015-05-15.
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Cross-trees, Edge and Superpixel Priors-based Cost aggregation for Stereo matching.
Authors: Cheng F. , Zhang H. , Sun M. , Yuan D. .
Source: Pattern recognition, 2015-07-01; 48(7), p. 2269-2278.
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Source: The American journal of clinical nutrition, 2015 Jun; 101(6), p. 1107-8.
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Authors: Li Z. , Wei Z. , Yue Y. , Wang H. , Jia W. , Burke L.E. , Baranowski T. , Sun M. .
Source: Journal of medical systems, 2015 May; 39(5), p. 57.
EPub date: 2015-03-19.
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A FPGA Implementation of JPEG Baseline Encoder for Wearable Devices.
Authors: Li Y. , Jia W. , Luan B. , Mao Z.H. , Zhang H. , Sun M. .
Source: Proceedings of the IEEE ... annual Northeast Bioengineering Conference. IEEE Northeast Bioengineering Conference, 2015 Apr; 2015, .
PMID: 26190911
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Assessing Physical Performance in Free-Living Older Adults with a Wearable Computer.
Authors: Zhao Q. , Wang J. , Feng W. , Jia W. , Burke L.E. , Zgibor J.C. , Sun M. .
Source: Proceedings of the IEEE ... annual Northeast Bioengineering Conference. IEEE Northeast Bioengineering Conference, 2015 Apr; 2015, .
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SIFT-Based Indoor Localization for Older Adults Using Wearable Camera.
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A Low Power, Parallel Wearable Multi-Sensor System for Human Activity Evaluation.
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Source: Proceedings of the IEEE ... annual Northeast Bioengineering Conference. IEEE Northeast Bioengineering Conference, 2015 Apr; 2015, .
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Saliency-aware food image segmentation for personal dietary assessment using a wearable computer.
Authors: Chen H.C. , Jia W. , Sun X. , Li Z. , Li Y. , Fernstrom J.D. , Burke L.E. , Baranowski T. , Sun M. .
Source: Measurement science & technology, 2015 Feb; 26(2), .
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An exploratory study on a chest-worn computer for evaluation of diet, physical activity and lifestyle.
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How to engage children in self-administered dietary assessment programmes.
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Source: Journal of human nutrition and dietetics : the official journal of the British Dietetic Association, 2014 Jan; 27 Suppl 1, p. 5-9.
EPub date: 2012-05-18.
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