title: Noise sensitivity of a principal component regression based RT interval variability estimation method.
abstract: Ventricular repolarization duration (VRD) is controlled by neural regulatory system same way as heart rate and, thus, also VRD varies in time. Traditionally, VRD variability is assessed by determining the time differences between successive R and T-waves, i.e. RT intervals. We have recently proposed a method based on principal component regression (PCR) for quantifying RT variability. The main benefit of the method is that it does not necessitate T-wave detection. In this paper, the noise sensitivity of the PCR based method is evaluated by examining the effect of simulated Gaussian noise on the spectral characteristics of the estimated RT variability series.
authors.affiliation: Dept. of Phys., Kuopio Univ., Kuopio, Finland. mika.tarvainen@uku.fi
authors.forename: Mika P
authors.initials: MP
authors.lastname: Tarvainen
authors.forename: Juha-Pekka
authors.initials: JP
authors.lastname: Niskanen
authors.forename: Pasi A
authors.initials: PA
authors.lastname: Karjalainen
authors.forename: Tomi
authors.initials: T
authors.lastname: Laitinen
authors.forename: Tiina
authors.initials: T
authors.lastname: Lyyra-Laitinen
mesh_terms: D000465:Algorithms; D001698:Biomedical Engineering; D004562:Electrocardiography / Q000706:statistics & numerical data*; D006339:Heart Rate / Q000502:physiology; D006801:Humans; D025341:Principal Component Analysis; D012044:Regression Analysis; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted