Accepted for/Published in: JMIR Formative Research
Date Submitted: Jul 8, 2021
Date Accepted: Nov 22, 2021
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Validity of nutrient and food group contents estimated automatically by an image recognition system: A smartphone application for health promotion
ABSTRACT
Background:
A smartphone image recognition application is expected to be a novel tool to measure nutrients and food intake, but its performance has not been well evaluated.
Objective:
We assessed the performance of an image recognition application called CALO mama in terms of the nutrient and food group contents automatically estimated by the application.
Methods:
We prepared 120 sample meals for which the nutrients and food groups were already calculated. Next, we predicted the nutrients and food groups included in the meals from their photographs using 1) automated image recognition only and 2) manual modification after automatic identification.
Results:
Predictions using only image recognition were similar to the actual data in weight of meals, 11 out of 30 nutrients, and 4 out of 15 food groups; it underestimated energy, 19 nutrients, and 9 food groups; it overestimated dairy products and confectioneries. After manual modification, predictions were similar in energy, 29 out of 30 nutrients, and 10 out of 15 food groups; it underestimated pulses, fruits, and meats; it overestimated weight, vitamin C, vegetables, and confectioneries.
Conclusions:
The results of this study suggest that manual modification after prediction using image recognition improves the performance of the assessment of nutrients and food intake. Our findings suggest the potential of image recognition to achieve a description of the dietary intakes of populations using “precision nutrition” (a comprehensive and dynamic approach to develop tailored nutritional recommendations) for individuals.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.