A Practical Approach for Recognizing Eating Moments with Wrist-Mounted Inertial Sensing

Recognizing when eating activities take place is one of the key challenges in automated food intake monitoring. Despite progress over the years, most proposed approaches have been largely impractical for everyday usage, requiring multiple on-body sensors or specialized devices such as neck collars f...

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Published inProceedings of the ... ACM International Conference on Ubiquitous Computing . UbiComp (Conference) Vol. 2015; p. 1029
Main Authors Thomaz, Edison, Essa, Irfan, Abowd, Gregory D
Format Journal Article Conference Proceeding
LanguageEnglish
Published United States 01.09.2015
Subjects
Automated Dietary Assessment
Activity recognition
Inertial Sensors
Food Journaling
Dietary Intake
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DOI10.1145/2750858.2807545

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Summary:Recognizing when eating activities take place is one of the key challenges in automated food intake monitoring. Despite progress over the years, most proposed approaches have been largely impractical for everyday usage, requiring multiple on-body sensors or specialized devices such as neck collars for swallow detection. In this paper, we describe the implementation and evaluation of an approach for inferring eating moments based on 3-axis accelerometry collected with a popular off-the-shelf smartwatch. Trained with data collected in a semi-controlled laboratory setting with 20 subjects, our system recognized eating moments in two free-living condition studies (7 participants, 1 day; 1 participant, 31 days), with F-scores of 76.1% (66.7% Precision, 88.8% Recall), and 71.3% (65.2% Precision, 78.6% Recall). This work represents a contribution towards the implementation of a practical, automated system for everyday food intake monitoring, with applicability in areas ranging from health research and food journaling.
DOI:10.1145/2750858.2807545