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  3. The Nutritional Content of Meal Images in Free-Living Conditions-Automatic Assessment with goFOODTM.
 

The Nutritional Content of Meal Images in Free-Living Conditions-Automatic Assessment with goFOODTM.

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BORIS DOI
10.48350/186190
Publisher DOI
10.3390/nu15173835
PubMed ID
37686866
Description
A healthy diet can help to prevent or manage many important conditions and diseases, particularly obesity, malnutrition, and diabetes. Recent advancements in artificial intelligence and smartphone technologies have enabled applications to conduct automatic nutritional assessment from meal images, providing a convenient, efficient, and accurate method for continuous diet evaluation. We now extend the goFOODTM automatic system to perform food segmentation, recognition, volume, as well as calorie and macro-nutrient estimation from single images that are captured by a smartphone. In order to assess our system's performance, we conducted a feasibility study with 50 participants from Switzerland. We recorded their meals for one day and then dietitians carried out a 24 h recall. We retrospectively analysed the collected images to assess the nutritional content of the meals. By comparing our results with the dietitians' estimations, we demonstrated that the newly introduced system has comparable energy and macronutrient estimation performance with the previous method; however, it only requires a single image instead of two. The system can be applied in a real-life scenarios, and it can be easily used to assess dietary intake. This system could help individuals gain a better understanding of their dietary consumption. Additionally, it could serve as a valuable resource for dietitians, and could contribute to nutritional research.
Date of Publication
2023-09-02
Publication Type
Article
Subject(s)
500 Science > 570 Life sciences; biology
600 Technology > 610 Medicine & health
Keyword(s)
artificial intelligence automatic dietary assessment computer vision food recognition food segmentation nutrient calculation portion estimation volume estimation
Language(s)
en
Contributor(s)
Papathanail, Ioannis
ARTORG Center for Biomedical Engineering Research - AI in Health and Nutrition
ARTORG Center for Biomedical Engineering Research
Abdur Rahman, Lubnaa
ARTORG Center for Biomedical Engineering Research
ARTORG Center for Biomedical Engineering Research - AI in Health and Nutrition
Brigato, Lorenzo
ARTORG Center for Biomedical Engineering Research - AI in Health and Nutrition
ARTORG Center for Biomedical Engineering Research
Bez, Natalie S
Vasiloglou, Maria
ARTORG Center for Biomedical Engineering Research - AI in Health and Nutrition
van der Horst, Klazine
Mougiakakou, Stavroula
ARTORG Center for Biomedical Engineering Research
ARTORG Center for Biomedical Engineering Research - AI in Health and Nutrition
Additional Credits
ARTORG Center for Biomedical Engineering Research - AI in Health and Nutrition
ARTORG Center for Biomedical Engineering Research
Series
Nutrients
Publisher
MDPI
ISSN
2072-6643
Access(Rights)
open.access
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