Fractal Nature of Chewing Sounds

V. Papapanagiotou, C. Diou, Z. Lingchuan, J.H.W. van den Boer, M. Mars, A. Delopoulos

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

8 Citations (Scopus)

Abstract

monitoring has been investigated by many researchers. For this purpose, one of the most promising modalities is the acoustic signal captured by a common microphone placed inside the outer ear canal. Various chewing detection algorithms for this type of signals exist in the literature. In this work, we perform a systematic analysis of the fractal nature of chewing sounds, and find that the Fractal Dimension is substantially different between chewing and talking. This holds even for severely down-sampled versions of the recordings. We derive chewing detectors based on the the fractal dimension of the recorded signals that can clearly discriminate chewing from non-chewing sounds. We experimentally evaluate snacking detection based on the proposed chewing detector, and we compare our approach against well known counterparts. Experimental results on a large dataset of 10 subjects and total recordings duration of more than 8 hours demonstrate the high effectiveness of our method. Furthermore, there exists indication that discrimination between different properties (such as crispness) is possible.
Original languageEnglish
Title of host publicationNew Trends in Image Analysis and Processing -- ICIAP 2015 Workshops
EditorsV. Murino, E. Puppo, D. Sona, M. Cristani, C. Sansone
Pages401-408
DOIs
Publication statusPublished - 2015

Publication series

NameLecture Notes in Computer Science
PublisherSpringer International Publishing
Number9281

Fingerprint Dive into the research topics of 'Fractal Nature of Chewing Sounds'. Together they form a unique fingerprint.

Cite this