title: Independent component analysis of parameterized ECG signals.
abstract: Independent component analysis (ICA) of measured signals yields the independent sources, given certain fulfilled requirements. Properly parameterized signals provide a better view to the considered system aspects, while reducing the amount of data. It is little acknowledged that appropriately parameterized signals may be subjected to ICA, yielding independent components (ICs) displaying more clearly the investigated properties of the sources. In this paper, we propose ICA of parameterized signals, and demonstrate the concept with ICA of ST and R parameterizations of electrocardiogram (ECG) signals from ECG exercise test measurements from two coronary artery disease (CAD) patients.
authors.affiliation: Ragnar Granit Institute, Tampere University of Technology, Tempere, Finland. tanskanen@ieee.org
authors.forename: Jarno M A
authors.initials: JM
authors.lastname: Tanskanen
authors.forename: Jari J
authors.initials: JJ
authors.lastname: Viik
authors.forename: Jari A K
authors.initials: JA
authors.lastname: Hyttinen
mesh_terms: D001331:Automation; D003324:Coronary Artery Disease / Q000175:diagnosis*; D003627:Data Interpretation, Statistical; D004562:Electrocardiography / Q000295:instrumentation* / Q000379:methods*; D004867:Equipment Design; D005080:Exercise Test; D005163:Factor Analysis, Statistical; D006801:Humans; D015233:Models, Statistical; D009206:Myocardium / Q000473:pathology; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors