Multimedia Data-Based Mobile Applications for Dietary Assessment.

Vasiloglou, Maria F; Marcano, Isabel; Lizama, Sergio; Papathanail, Ioannis; Spanakis, Elias K; Mougiakakou, Stavroula (2023). Multimedia Data-Based Mobile Applications for Dietary Assessment. Journal of diabetes science and technology, 17(4), pp. 1056-1065. Sage 10.1177/19322968221085026

Full text not available from this repository.

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.

Item Type:	Journal Article (Review Article)
Division/Institute:	10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research 04 Faculty of Medicine > Department of Intensive Care, Emergency Medicine and Anaesthesiology (DINA) > University Emergency Center 10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - AI in Health and Nutrition
UniBE Contributor:	Vasiloglou, Maria, Papathanail, Ioannis, Mougiakakou, Stavroula
Subjects:	500 Science > 570 Life sciences; biology 600 Technology > 610 Medicine & health
ISSN:	1932-2968
Publisher:	Sage
Language:	English
Submitter:	Pubmed Import
Date Deposited:	30 Mar 2022 09:41
Last Modified:	03 Jul 2023 00:11
Publisher DOI:	10.1177/19322968221085026
PubMed ID:	35348398
Uncontrolled Keywords:	AI apps dietary assessment mHealth nutrition smartphones
URI:	https://boris.unibe.ch/id/eprint/168407