Papathanail, Ioannis; Abdur Rahman, Lubnaa; Brigato, Lorenzo; Bez, Natalie S; Vasiloglou, Maria F; van der Horst, Klazine; Mougiakakou, Stavroula (2023). The Nutritional Content of Meal Images in Free-Living Conditions-Automatic Assessment with goFOODTM. Nutrients, 15(17) Molecular Diversity Preservation International MDPI 10.3390/nu15173835
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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.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - AI in Health and Nutrition 10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research |
UniBE Contributor: |
Papathanail, Ioannis, Abdur Rahman, Lubnaa, Brigato, Lorenzo, Vasiloglou, Maria, Mougiakakou, Stavroula |
Subjects: |
500 Science > 570 Life sciences; biology 600 Technology > 610 Medicine & health |
ISSN: |
2072-6643 |
Publisher: |
Molecular Diversity Preservation International MDPI |
Language: |
English |
Submitter: |
Pubmed Import |
Date Deposited: |
12 Sep 2023 11:42 |
Last Modified: |
12 Sep 2023 11:51 |
Publisher DOI: |
10.3390/nu15173835 |
PubMed ID: |
37686866 |
Uncontrolled Keywords: |
artificial intelligence automatic dietary assessment computer vision food recognition food segmentation nutrient calculation portion estimation volume estimation |
BORIS DOI: |
10.48350/186190 |
URI: |
https://boris.unibe.ch/id/eprint/186190 |
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