Publications

Methods for Detection and Classification of Normal Swallowing from Muscle Activation and Sound

Publication Type Conference Paper
Authors Oliver Amft, Gerhard Tröster
Title Methods for Detection and Classification of Normal Swallowing from Muscle Activation and Sound
Abstract Swallowing is an important part of the dietary process. This paper presents an investigation to detect and classify normal swallowing during eating and drinking from electromyography and microphone sensors. The non-invasive sensors are selected in order to integrate them into a collar-like fabric for continuous monitoring of swallowing activity over a day. We compare methods for the detection of individual swallowing events from continuous sensor data. Furthermore we present a classifier comparison for the swallowing event properties volume and viscosity. The methods are evaluated on experimental data and a performance analysis is shown. Moreover we present a class skew analysis based on the metrics precision and recall.
Date November 2006
Proceedings Title PHC 2006: Proceedings of the First International Conference on Pervasive Computing Technologies for Healthcare
Publisher ICST
Pages 1–10
DOI 10.1109/PCTHEALTH.2006.361624
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Friedrich-Alexander-Universität Erlangen-Nürnberg