Methods for detection and classification of normal swallowing from muscle activation and sound

O.D. Amft, G. Tröster

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

61 Citations (Scopus)
209 Downloads (Pure)

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 collarlike 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.
Original languageEnglish
Title of host publicationProceedings 2006 Pervasive Health Conference and Workshops, PervasiveHealth, 29 November 2006 through 1 December 2006, Innsbruck
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Pages4205194-
ISBN (Print)1-4244-1085-1
DOIs
Publication statusPublished - 2007

Fingerprint Dive into the research topics of 'Methods for detection and classification of normal swallowing from muscle activation and sound'. Together they form a unique fingerprint.

Cite this