loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Hao Zhang 1 ; Guillaume Lopez 1 ; Ran Tao 2 ; Masaki Shuzo 1 ; Jean-Jacques Delaunay 1 and Ichiro Yamada 1

Affiliations: 1 The University of Tokyo, Japan ; 2 Université de Lyon and INSA-Lyon, France

Keyword(s): Eating habits monitoring, Sound analysis, Bone-conduction sensors, Wavelet features, Self-Organizing Maps (SOM), Hidden Markov Model (HMM).

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Business Analytics ; Clinical Problems and Applications ; Data Engineering ; Data Mining ; Databases and Information Systems Integration ; Datamining ; Devices ; Enterprise Information Systems ; Evaluation and Use of Healthcare IT ; Health Information Systems ; Human-Computer Interaction ; Pattern Recognition and Machine Learning ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Wearable Sensors and Systems

Abstract: In recent years, an increasing number of people have been suffering from over-weight, indicating the importance of a balanced dietetic lifestyle. Researches in nutrition and oral health have raised the importance of not only calorific consumption, but also eating habits quality such as the regularity of meals, eating speed, and food texture. A new model for the estimation of food texture by analyzing chewing sound collected from a wearable sensor is presented in this paper. The proposed model combining effective sound features extraction and classification methods make it possible to estimate quantitatively detailed texture of food a person is eating. The model has been implemented and shown being efficient (more than 90% accuracy) to estimate three food texture indices at eight detailed levels for each, with little influence of individual chewing differences.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 44.220.41.140

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Zhang, H.; Lopez, G.; Tao, R.; Shuzo, M.; Delaunay, J. and Yamada, I. (2012). FOOD TEXTURE ESTIMATION FROM CHEWING SOUND ANALYSIS. In Proceedings of the International Conference on Health Informatics (BIOSTEC 2012) - HEALTHINF; ISBN 978-989-8425-88-1; ISSN 2184-4305, SciTePress, pages 213-218. DOI: 10.5220/0003771802130218

@conference{healthinf12,
author={Hao Zhang. and Guillaume Lopez. and Ran Tao. and Masaki Shuzo. and Jean{-}Jacques Delaunay. and Ichiro Yamada.},
title={FOOD TEXTURE ESTIMATION FROM CHEWING SOUND ANALYSIS},
booktitle={Proceedings of the International Conference on Health Informatics (BIOSTEC 2012) - HEALTHINF},
year={2012},
pages={213-218},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003771802130218},
isbn={978-989-8425-88-1},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the International Conference on Health Informatics (BIOSTEC 2012) - HEALTHINF
TI - FOOD TEXTURE ESTIMATION FROM CHEWING SOUND ANALYSIS
SN - 978-989-8425-88-1
IS - 2184-4305
AU - Zhang, H.
AU - Lopez, G.
AU - Tao, R.
AU - Shuzo, M.
AU - Delaunay, J.
AU - Yamada, I.
PY - 2012
SP - 213
EP - 218
DO - 10.5220/0003771802130218
PB - SciTePress