• DOI:10.1017/S0029665116002913
• Corpus ID: 206244628

New mobile methods for dietary assessment: review of image-assisted and image-based dietary assessment methods

@article{Boushey2016NewMM,
  title={New mobile methods for dietary assessment: review of image-assisted and image-based dietary assessment methods},
  author={Carol Jo Boushey and Melissa Spoden and Fengqing Maggie Zhu and Edward J. Delp and Deborah Anne Kerr},
  journal={Proceedings of the Nutrition Society},
  year={2016},
  volume={76},
  pages={283 - 294}
}

• C. Boushey, M. Spoden, +2 authors D. Kerr
• Published 12 December 2016
• Medicine
• Proceedings of the Nutrition Society

For nutrition practitioners and researchers, assessing dietary intake of children and adults with a high level of accuracy continues to be a challenge. Developments in mobile technologies have created a role for images in the assessment of dietary intake. The objective of this review was to examine peer-reviewed published papers covering development, evaluation and/or validation of image-assisted or image-based dietary assessment methods from December 2013 to January 2016. Images taken with handheld devices or wearable cameras have been used to assist traditional dietary assessment methods for portion size estimations made by dietitians (image-assisted methods). Image-assisted approaches can supplement either dietary records or 24-h dietary recalls. In recent years, image-based approaches integrating application technology for mobile devices have been developed (image-based methods). Image-based approaches aim at capturing all eating occasions by images as the primary record of dietary intake, and therefore follow the methodology of food records. The present paper reviews several image-assisted and image-based methods, their benefits and challenges; followed by details on an image-based mobile food record. Mobile technology offers a wide range of feasible options for dietary assessment, which are easier to incorporate into daily routines. The presented studies illustrate that image-assisted methods can improve the accuracy of conventional dietary assessment methods by adding eating occasion detail via pictures captured by an individual (dynamic images). All of the studies reduced underreporting with the help of images compared with results with traditional assessment methods. Studies with larger sample sizes are needed to better delineate attributes with regards to age of user, degree of error and cost.