title: Model based analysis of the heart rate and blood pressure relationship.
abstract: The main intention of this contribution is to measure the coupling between bivariate time series using the dual sequence method to estimate the baroreflex as well as a nonlinear regression approach, namely the maximal correlation method, to get a better understanding of the underlying processes. The data we analyse are heart rate and blood pressure variability time series from 27 patients with dilated cardiomyopathy as well as from a control group of 27 age- and sex-matched healthy subjects. The results strongly indicate and confirm the mechanisms of respiratory sinus arrhythmia in heart rate. Revealing the coupling direction and the strength of coupling between heart rate and blood pressure via optimal transformations in addition to the baroreflex estimation seems to be a very promising approach.
authors.affiliation: Institute of Physics, University of Potsdam, Germany.
authors.forename: N
authors.initials: N
authors.lastname: Wessel
authors.forename: H
authors.initials: H
authors.lastname: Malberg
authors.forename: U
authors.initials: U
authors.lastname: Meyerfeldt
authors.forename: A
authors.initials: A
authors.lastname: Schirdewan
authors.forename: J
authors.initials: J
authors.lastname: Kurths
mesh_terms: D000328:Adult; D000368:Aged; D001146:Arrhythmia, Sinus / Q000145:classification / Q000503:physiopathology; D017704:Baroreflex / Q000502:physiology*; D001794:Blood Pressure / Q000502:physiology*; D002311:Cardiomyopathy, Dilated / Q000145:classification / Q000503:physiopathology; D005260:Female; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D008297:Male; D008875:Middle Aged; D018670:Monitoring, Ambulatory / Q000706:statistics & numerical data; D017711:Nonlinear Dynamics; D011379:Prognosis; D012016:Reference Values; D012044:Regression Analysis; D012815:Signal Processing, Computer-Assisted