NDLI: Reliable motion artifact detection for ECG monitoring systems with dry electrodes

Content Provider	IEEE Xplore Digital Library
Author	Ottenbacher, Jorg Kirst, Malte Jatoba, Luciana Huflejt, Michal Grossmann, Ulrich Stork, Wilhelm
Copyright Year	2008
Description	Author affiliation: Department of Computer Science, University of Hamburg, Germany (Huflejt, Michal) \|\| Institute for Information Processing Technology, University of Karlsruhe, 76131, Germany (Ottenbacher, Jorg; Jatoba, Luciana; Grossmann, Ulrich; Stork, Wilhelm) \|\| FZI Research Center for Information Technology, 76131 Karlsruhe, Germany (Kirst, Malte)
Abstract	Reliable signals are the basic prerequisite for most mobile ECG monitoring applications. Especially when signals are analyzed automatically, capable motion artifact detection algorithms are of great importance. This article presents different artifact detection algorithms for ECG systems with dry electrodes. The algorithms are based on the measurement of additional parameters that are correlated with the artifacts. We describe a mobile measurement system and the procedure used for the evaluation of these algorithms. The algorithms are assessed based upon their effect on QRS detection. The best algorithm improved sensitivity (Se) from 98.7% to 99.8% and positive predictive value (+P) from 98.3% to 99.9%, while 15% of the signal was marked as artifact. This corresponds to a decrease in false positive and false negative detected beats by 89.9%. Different metrics to evaluate the performance of an artifact detection algorithm are presented.
Starting Page	1695
Ending Page	1698
File Size	207847
Page Count	4
File Format	PDF
ISBN	9781424418145
ISSN	1557170X
DOI	10.1109/IEMBS.2008.4649502
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-08-20
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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