MASTICATION COUNTING METHOD ROBUST TO FOOD TYPE AND INDIVIDUAL

Hao Zhang, Guillaume Lopez, Masaki Shuzo, Jean-Jacques Delaunay, Ichiro Yamada

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.

References

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Paper Citation


in Harvard Style

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 - Volume 1: HEALTHINF, (BIOSTEC 2012) ISBN 978-989-8425-88-1, pages 374-377. DOI: 10.5220/0003771903740377


in Bibtex Style

@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 - Volume 1: HEALTHINF, (BIOSTEC 2012)},
year={2012},
pages={374-377},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003771903740377},
isbn={978-989-8425-88-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2012)
TI - MASTICATION COUNTING METHOD ROBUST TO FOOD TYPE AND INDIVIDUAL
SN - 978-989-8425-88-1
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