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Authors: Hao Zhang ; Guillaume Lopez ; Masaki Shuzo ; Jean-Jacques Delaunay and Ichiro Yamada

Affiliation: The University of Tokyo, Japan

Keyword(s): Eating habits monitoring, Wearable sensor, Mastication counting, Chewing sound, Life-style diseases prevention.

Related Ontology Subjects/Areas/Topics: Biomedical Engineering ; Biomedical Signal Processing ; Cardiovascular Technologies ; Clinical Problems and Applications ; Computing and Telecommunications in Cardiology ; Development of Assistive Technology ; Devices ; Evaluation and Use of Healthcare IT ; Health Engineering and Technology Applications ; Health Information Systems ; Human-Computer Interaction ; Medical and Nursing Informatics ; Physiological Computing Systems ; Wearable Sensors and Systems

Abstract: In recent years, an increasing number of people have been suffering from over-weight, reminding the importance of a balanced dietetic lifestyle. Researches in nutrition and oral health have reported that not only the calorie intake amount, but also eating speed and the number of chews per bite were also important factors in obesity. Automatic mastication counting systems based on chewing sound processing have been proposed, though most of them have difficulties in detecting chewing strokes for various food types, and often require training logic or threshold that need to be customized for each user. To overcome these problems, we have developed a new model for automatic mastication counting based on new chew feature extraction and detection methods from natural chewing sound. Chewing sounds collected from 15 persons eating six different food types were recorded using a wearable bone-conduction microphone placed in ear. The chewing sound analysis model combining proposed chew feature extraction and detection methods was applied on the collected data set, showing a good overall accuracy while having better stability to different individuals and food types comparing to conventional models. (More)

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Paper citation in several formats:
Zhang, H.; Lopez, G.; Shuzo, M.; Delaunay, J. and Yamada, I. (2012). MASTICATION COUNTING METHOD ROBUST TO FOOD TYPE AND INDIVIDUAL. In Proceedings of the International Conference on Health Informatics (BIOSTEC 2012) - HEALTHINF; ISBN 978-989-8425-88-1; ISSN 2184-4305, SciTePress, pages 374-377. DOI: 10.5220/0003771903740377

@conference{healthinf12,
author={Hao Zhang. and Guillaume Lopez. and Masaki Shuzo. and Jean{-}Jacques Delaunay. and Ichiro Yamada.},
title={MASTICATION COUNTING METHOD ROBUST TO FOOD TYPE AND INDIVIDUAL},
booktitle={Proceedings of the International Conference on Health Informatics (BIOSTEC 2012) - HEALTHINF},
year={2012},
pages={374-377},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003771903740377},
isbn={978-989-8425-88-1},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the International Conference on Health Informatics (BIOSTEC 2012) - HEALTHINF
TI - MASTICATION COUNTING METHOD ROBUST TO FOOD TYPE AND INDIVIDUAL
SN - 978-989-8425-88-1
IS - 2184-4305
AU - Zhang, H.
AU - Lopez, G.
AU - Shuzo, M.
AU - Delaunay, J.
AU - Yamada, I.
PY - 2012
SP - 374
EP - 377
DO - 10.5220/0003771903740377
PB - SciTePress