Food intake recognition conception for wearable devices

Authors:
Sebastian Päßler;Matthias Wolff;Wolf-Joachim Fischer
Affiliations:
Fraunhofer IPMS, Maria-Reiche-Straße, Dresden;IAS, Technische Universität Dresden, Helmholtzstraße, Dresden;Fraunhofer IPMS, Maria-Reiche-Straße, Dresden
Venue:
MobileHealth '11 Proceedings of the First ACM MobiHoc Workshop on Pervasive Wireless Healthcare
Year:
2011

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Abstract

Obesity is a growing healthcare challenge in present days. Objective automated methods of food intake monitoring are necessary to face this challenge in future. A method for non-invasive monitoring of human food intake behavior by the evaluation of chewing and swallowing sounds has been developed. A wearable food intake sensor has been created by integrating in-ear microphone and a reference microphone in a hearing aid case. A concept for food intake monitoring requiring low computational cost is presented. After the detection of food intake activity periods, signal recognition algorithms based on Hidden Markov Models distinguish several types of food based on the sound properties of their chewing sounds. Algorithms are developed using manual labeled records of the food intake sounds of 40 participants.