Automatic Ingestion Monitor Version 2 - A Novel Wearable Device for Automatic Food Intake Detection and Passive Capture of Food Images

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dc.contributor.authorDoulah, Abul
dc.contributor.authorGhosh, Tonmoy
dc.contributor.authorHossain, Delwar
dc.contributor.authorImtiaz, Masudul H.
dc.contributor.authorSazonov, Edward
dc.contributor.otherUniversity of Alabama Tuscaloosa
dc.date.accessioned2023-09-28T19:31:07Z
dc.date.available2023-09-28T19:31:07Z
dc.date.issued2021
dc.description.abstractUse of food image capture and/or wearable sensors for dietary assessment has grown in popularity. Active - methods rely on the user to take an image of each eating episode. "Passive" methods use wearable cameras that continuously capture images. Most of "passively" captured images are not related to food consumption and may present privacy concerns. In this paper, we propose a novel wearable sensor (Automatic Ingestion Monitor. AIM-2) designed to capture images only during automatically detected eating episodes. The capture method was validated on a dataset collected from 30 volunteers in the community wearing the AIM-2 for 24h in pseudo-free-living and 24h in a free-living environment. The AIM-2 was able to detect food intake over 10-second epochs with a (mean and standard deviation) Fl-score of 81.8 +/- 10.1%. The accuracy of eating episode detection was 82.7%. Out of a total of 180,570 images captured, 8,929 (4.9%) images belonged to detected eating episodes. Privacy concerns were assessed by a questionnaire on a scale 1-7. Continuous capture had concern value of 5.0 +/- 1.6 (concerned) while image capture only during food intake had concern value of 1.9 +/- 1.7 (not concerned). Results suggest that AIM-2 can provide accurate detection of food intake, reduce the number of images for analysis and alleviate the privacy concerns of the users.en_US
dc.format.mediumelectronic
dc.format.mimetypeapplication/pdf
dc.identifier.citationDoulah, A., Ghosh, T., Hossain, D., Imtiaz, M. H., & Sazonov, E. (2021). “Automatic Ingestion Monitor Version 2” – A Novel Wearable Device for Automatic Food Intake Detection and Passive Capture of Food Images. In IEEE Journal of Biomedical and Health Informatics (Vol. 25, Issue 2, pp. 568–576). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/jbhi.2020.2995473
dc.identifier.doi10.1109/JBHI.2020.2995473
dc.identifier.orcidhttps://orcid.org/0000-0003-1460-2267
dc.identifier.orcidhttps://orcid.org/0000-0002-8161-6602
dc.identifier.urihttps://ir.ua.edu/handle/123456789/11357
dc.languageEnglish
dc.language.isoen_US
dc.publisherIEEE
dc.subjectFood intake detection
dc.subjectwearable sensors
dc.subjectdietary assessment
dc.subjectenergy intake
dc.subjectfood imagery
dc.subjectComputer Science, Information Systems
dc.subjectComputer Science, Interdisciplinary Applications
dc.subjectMathematical & Computational Biology
dc.subjectMedical Informatics
dc.titleAutomatic Ingestion Monitor Version 2 - A Novel Wearable Device for Automatic Food Intake Detection and Passive Capture of Food Imagesen_US
dc.typeArticle
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