Towards a fully automatic food intake recognition system using acoustic, image capturing and glucose measurements
File(s)
Accepted version
Author(s)
Rosa, Bruno Gil
Anastasova-Ivanova, Salzitsa
Lo, Benny
Yang, Guang Zhong
Type
Conference Paper
Abstract
Food intake is a major healthcare issue in developed countries that has become an economic and social burden across all sectors of society. Bad food intake habits lead to increased risk for development of obesity in children, young people and adults, with the latter more prone to suffer from health diseases such as diabetes, shortening the life expectancy. Environmental, cultural and behavioural factors have been appointed to be responsible for altering the balance between energy intake and expenditure, resulting in excess body weight. Methods to counteract the food intake problem are vast and include self-reported food questionnaires, body-worn sensors that record the sound, pressure or movements in the mouth and GI tract or image-based approaches that recognize the different types of food being ingested. In this paper we present an ear-worn device to track food intake habits by recording the acoustic signal produced by the chewing movements as well as the glucose level amperiometrically. Combined with a small camera on a future version of the device, we hope to deliver a complete system to control dietary habits with caloric intake estimation during satiation and deficit during satiety periods, which can be adapted to the physiology of each user.
Date Issued
2019-07-25
Date Acceptance
2019-07-01
Citation
2019 IEEE 16TH INTERNATIONAL CONFERENCE ON WEARABLE AND IMPLANTABLE BODY SENSOR NETWORKS (BSN), 2019
ISSN
2376-8886
Publisher
IEEE
Journal / Book Title
2019 IEEE 16TH INTERNATIONAL CONFERENCE ON WEARABLE AND IMPLANTABLE BODY SENSOR NETWORKS (BSN)
Copyright Statement
© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor
Engineering & Physical Science Research Council (EPSRC)
Engineering & Physical Science Research Council (E
Bill and Melinda Gates Foundation
Bill & Melinda Gates Foundation
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000492872400012&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Grant Number
EP/L014149/1
540213 SeNTH plus
OPP1171395
OPP1171395
Source
IEEE 16th International Conference on Wearable and Implantable Body Sensor Networks (BSN)
Subjects
Science & Technology
Technology
Computer Science, Interdisciplinary Applications
Engineering, Electrical & Electronic
Computer Science
Engineering
Publication Status
Published
Start Date
2019-05-19
Finish Date
2019-05-22
Coverage Spatial
Univ Illinois Chicago, Chicago, IL
Date Publish Online
2019-07-25