title: Reliable motion artifact detection for ECG monitoring systems with dry electrodes.
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.
authors.affiliation: Institute for Information Processing Technology, University of Karlsruhe, 76131, Germany. ottenbacher@itiv.uni-karlsruhe.de
authors.forename: Jörg
authors.initials: J
authors.lastname: Ottenbacher
authors.forename: Malte
authors.initials: M
authors.lastname: Kirst
authors.forename: Luciana
authors.initials: L
authors.lastname: Jatobá
authors.forename: Michal
authors.initials: M
authors.lastname: Huflejt
authors.forename: Ulrich
authors.initials: U
authors.lastname: Grossmann
authors.forename: Wilhelm
authors.initials: W
authors.lastname: Stork
mesh_terms: D000054:Acceleration; D000465:Algorithms; D001698:Biomedical Engineering; D017097:Electric Impedance; D004562:Electrocardiography / Q000295:instrumentation* / Q000706:statistics & numerical data*; D004566:Electrodes; D006801:Humans; D009038:Motion; D012372:ROC Curve; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted