• 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