Analysis of Mastication Sound for Development of Food Texture Inference System

Autor:	Naoki Wada, Tomomichi Kagawa, Ryuji Ito, Shigeru Kato, Rina Kondo
Rok vydání:	2017
Předmět:	Sound (medical instrument) Noise Air conduction Artificial neural network Computer science Inference system Acoustics Food texture Mastication
Zdroj:	Advances on P2P, Parallel, Grid, Cloud and Internet Computing ISBN: 9783319698342 3PGCIC
DOI:	10.1007/978-3-319-69835-9_78
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::82c22448f6db648e61eac2b2b08f5653 https://doi.org/10.1007/978-3-319-69835-9_78 Zobrazit plný text záznamu