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The Use of Mobile Devices in Aiding Dietary Assessment and Evaluation
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There is a growing concern about chronic diseases and other health problems related to diet including obesity and cancer. The need to accurately measure diet (what foods a person consumes) becomes imperative. Dietary intake provides valuable insights for mounting intervention programs for prevention of chronic diseases. Measuring accurate dietary intake is considered to be an open research problem in the nutrition and health fields. In this paper, we describe a novel mobile telephone food record that will provide an accurate account of daily food and nutrient intake. 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. The mobile device provides a unique vehicle for collecting dietary information that reduces the burden on respondents that are obtained using more classical approaches for dietary assessment. We describe our approach to image analysis that includes the segmentation of food items, features used to identify foods, a method for automatic portion estimation, and our overall system architecture for collecting the food intake information.
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“Smartphones and photography can be used to make self-monitoring easy and convenient [6-9].”
From Factors related to sustained use of a free mobile app for dietary self-monitoring with photography and peer feedback: retrospective cohort study (2014) · cites this paper as [9]
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Shoneye, C. L., Dhaliwal, S. S., Pollard, C. M., Boushey, C. J., Delp, E. J., Harray, A. J., Howat, P. A., Hutchesson, M., Rollo, M. E., Zhu, F. M., et al. (2019) · Nutrients · doi:10.3390/nu11020435 · Cited by 15
Self-citationContext based food image analysis
He, Y., Xu, C., Khanna, N., Boushey, C. J., & Delp, E. J. (2013) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2013.6738566 · Cited by 15
Self-citationBoushey, C. J., Delp, E. J., Ahmad, Z., Wang, Y., Roberts, S. M., & Grattan, L. M. (2016) · Harmful Algae · doi:10.1016/j.hal.2016.03.013 · Cited by 14
Self-citationThornton, L. K., Osman, B., Champion, K. E., Green, O., Wescott, A., Gardner, L. A., Stewart, C., Visontay, R., Whife, J., Parmenter, B. J., et al. (2021) · JMIR mhealth and uhealth · doi:10.2196/27337 · Cited by 12
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Bilinear CNN Models for Food Recognition
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An Open-Source Approach to Solving the Problem of Accurate Food-Intake Monitoring
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An AI Based Approach for Personalized Nutrition and Food Menu Planning
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Cognition in the Attention Economy
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Self-citation
Metadata
- Authors
- Zhu, F., Bosch, M., Woo, I., Kim, S., Boushey, C. J., Ebert, D. S., & Delp, E. J.
- Affiliations
- Purdue University West Lafayette (US)
- Venue
- IEEE Journal of Selected Topics in Signal Processing
- Published
- 2010-08
- Volume
- 4
- Issue
- 4
- Pages
- 756-766
- ISSN
- 1932-4553 (ISSN-L)
- 1941-0484
- PMC
- PMC2941896
- OpenAlex
- W2109257383
- Cited by
- 355
- References
- 61
- Citations by year
- 2026: 4 · 2025: 10 · 2024: 11 · 2023: 18 · 2022: 23 · 2021: 28 · 2020: 15 · 2019: 23 · 2018: 28 · 2017: 40 · 2016: 30 · 2015: 36 · 2014: 29 · 2013: 23 · 2012: 20
- FWCI
- 34.17
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- IEEE Journal of Selected Topics in Signal Processing (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Purdue University
- National Cancer Institute (U01CA130784)
- National Institute of Diabetes and Digestive and Kidney Diseases (R01DK073711)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Health Professions › Health Information Management › Innovation in Digital Healthcare Systems
- Health Sciences › Nursing › Nutrition and Dietetics › Nutrition, Health and Food Behavior
- Keywords
- dietary assessment, food intake estimation, image analysis, food segmentation, food recognition, mobile health, chronic disease prevention, obesity, cancer prevention, nutrient intake
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