DocumentCode :
105160
Title :
Automatic Ingestion Monitor: A Novel Wearable Device for Monitoring of Ingestive Behavior
Author :
Fontana, J.M. ; Farooq, M. ; Sazonov, Edward
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Alabama, Tuscaloosa, AL, USA
Volume :
61
Issue :
6
fYear :
2014
fDate :
Jun-14
Firstpage :
1772
Lastpage :
1779
Abstract :
Objective monitoring of food intake and ingestive behavior in a free-living environment remains an open problem that has significant implications in study and treatment of obesity and eating disorders. In this paper, a novel wearable sensor system (automatic ingestion monitor, AIM) is presented for objective monitoring of ingestive behavior in free living. The proposed device integrates three sensor modalities that wirelessly interface to a smartphone: a jaw motion sensor, a hand gesture sensor, and an accelerometer. A novel sensor fusion and pattern recognition method was developed for subject-independent food intake recognition. The device and the methodology were validated with data collected from 12 subjects wearing AIM during the course of 24 h in which both the daily activities and the food intake of the subjects were not restricted in any way. Results showed that the system was able to detect food intake with an average accuracy of 89.8%, which suggests that AIM can potentially be used as an instrument to monitor ingestive behavior in free-living individuals.
Keywords :
accelerometers; biomedical equipment; medical disorders; patient monitoring; pattern recognition; sensor fusion; smart phones; accelerometer; automatic ingestion monitor; eating disorder treatment; free-living environment; hand gesture sensor; ingestive behavior monitoring; jaw motion sensor; obesity treatment; pattern recognition method; sensor fusion; smartphone; subject-independent food intake recognition; time 24 h; wearable device; wearable sensor system; Biomedical monitoring; Feature extraction; Monitoring; Obesity; Pattern recognition; Smart phones; Wearable sensors; Automatic ingestion monitor (AIM); chewing; eating disorders; food intake (FI) detection; obesity; pattern recognition; wearable sensors;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2014.2306773
Filename :
6742586
Link To Document :
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