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Multimedia Data-Based Mobile Applications for Dietary Assessment

Multimedia Data-Based Mobile Applications for Dietary Assessment Diabetes mellitus (DM) and obesity are chronic medical conditions associated with significant morbidity and mortality. Accurate macronutrient and energy estimation could be beneficial in attempts to manage DM and obesity, leading to improved glycemic control and weight reduction, respectively. Existing dietary assessment methods are subject to major errors in measurement, are time consuming, are costly, and do not provide real-time feedback. The increasing adoption of smartphones and artificial intelligence, along with the advances in algorithms and hardware, allowed the development of technologies executed in smartphones that use food/beverage multimedia data as an input, and output information about the nutrient content in almost real time. Scope of this review was to explore the various image-based and video-based systems designed for dietary assessment. We identified 22 different systems and divided these into three categories on the basis of their setting for evaluation: laboratory (12), preclinical (7), and clinical (3). The major findings of the review are that there is still a number of open research questions and technical challenges to be addressed and end users—including health care professionals and patients—need to be involved in the design and development of such innovative solutions. Last, there is a clear need that these systems should be validated under unconstrained real-life conditions and that they should be compared with conventional methods for dietary assessment. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Diabetes Science and Technology SAGE

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References (48)

Publisher
SAGE
Copyright
© 2022 Diabetes Technology Society
ISSN
1932-2968
eISSN
1932-2968
DOI
10.1177/19322968221085026
Publisher site
See Article on Publisher Site

Abstract

Diabetes mellitus (DM) and obesity are chronic medical conditions associated with significant morbidity and mortality. Accurate macronutrient and energy estimation could be beneficial in attempts to manage DM and obesity, leading to improved glycemic control and weight reduction, respectively. Existing dietary assessment methods are subject to major errors in measurement, are time consuming, are costly, and do not provide real-time feedback. The increasing adoption of smartphones and artificial intelligence, along with the advances in algorithms and hardware, allowed the development of technologies executed in smartphones that use food/beverage multimedia data as an input, and output information about the nutrient content in almost real time. Scope of this review was to explore the various image-based and video-based systems designed for dietary assessment. We identified 22 different systems and divided these into three categories on the basis of their setting for evaluation: laboratory (12), preclinical (7), and clinical (3). The major findings of the review are that there is still a number of open research questions and technical challenges to be addressed and end users—including health care professionals and patients—need to be involved in the design and development of such innovative solutions. Last, there is a clear need that these systems should be validated under unconstrained real-life conditions and that they should be compared with conventional methods for dietary assessment.

Journal

Journal of Diabetes Science and TechnologySAGE

Published: Jul 1, 2023

Keywords: AI; apps; dietary assessment; mHealth; nutrition; smartphones

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