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Analysis of Mastication Sound for Development of Food Texture Inference System

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Advances on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC 2017)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 13))

Abstract

In this paper, a comparison between a bone and an air conduction sounds is described. The sounds when a human masticates cucumbers and cabbages are observed and analyzed, in order to identify essential sound for estimating a food texture. The sound detected by our food texture estimation equipment in the latest study contains a noise caused by resonance of the housing of the equipment. However such noise is not observed in a human. It is important to grasp actual bone and air conduction sounds by a human. In an experiment of the present paper, it is found that features of the bone and the air conduction sounds are different, and both of these sounds are necessary to assume the food texture. A neural network model is constructed which classifies the cucumber and the cabbage considering the bone and the air conduction sounds. The experimental result and future works are discussed.

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Authors and Affiliations

  1. Niihama College, National Institute of Technology, 7-1 Yagumo-Cho, Niihama, Ehime, 792-8580, Japan

    Shigeru Kato, Naoki Wada, Ryuji Ito, Rina Kondo & Tomomichi Kagawa

Authors
  1. Shigeru Kato
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  2. Naoki Wada
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  3. Ryuji Ito
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  4. Rina Kondo
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  5. Tomomichi Kagawa
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Corresponding author

Correspondence to Shigeru Kato .

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Editors and Affiliations

  1. Technical University of Catalonia, Barcelona, Spain

    Fatos Xhafa

  2. Open University of Catalonia, Barcelona, Spain

    Santi Caballé

  3. Fukuoka Institute of Technology (FIT), Fukuoka, Japan

    Leonard Barolli

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Kato, S., Wada, N., Ito, R., Kondo, R., Kagawa, T. (2018). Analysis of Mastication Sound for Development of Food Texture Inference System. In: Xhafa, F., Caballé, S., Barolli, L. (eds) Advances on P2P, Parallel, Grid, Cloud and Internet Computing. 3PGCIC 2017. Lecture Notes on Data Engineering and Communications Technologies, vol 13. Springer, Cham. https://doi.org/10.1007/978-3-319-69835-9_78

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  • DOI: https://doi.org/10.1007/978-3-319-69835-9_78

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-69834-2

  • Online ISBN: 978-3-319-69835-9

  • eBook Packages: EngineeringEngineering (R0)

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