title: Non-uniform multivariate embedding to assess the information transfer in cardiovascular and cardiorespiratory variability series.
abstract: The complexity of the short-term cardiovascular control prompts for the introduction of multivariate (MV) nonlinear time series analysis methods to assess directional interactions reflecting the underlying regulatory mechanisms. This study introduces a new approach for the detection of nonlinear Granger causality in MV time series, based on embedding the series by a sequential, non-uniform procedure, and on estimating the information flow from one series to another by means of the corrected conditional entropy. The approach is validated on short realizations of linear stochastic and nonlinear deterministic processes, and then evaluated on heart period, systolic arterial pressure and respiration variability series measured from healthy humans in the resting supine position and in the upright position after head-up tilt.
authors.affiliation: Lab. Biosegnali, Department of Physics and BIOtech, University of Trento, via delle Regole 101, 38123 Mattarello, Trento, Italy. luca.faes@unitn.it
authors.forename: Luca
authors.initials: L
authors.lastname: Faes
authors.forename: Giandomenico
authors.initials: G
authors.lastname: Nollo
authors.forename: Alberto
authors.initials: A
authors.lastname: Porta
mesh_terms: D000465:Algorithms; D001794:Blood Pressure / Q000502:physiology; D002320:Cardiovascular Physiological Phenomena; D006801:Humans; D008955:Models, Cardiovascular; D015999:Multivariate Analysis; D017711:Nonlinear Dynamics; D011187:Posture; D015203:Reproducibility of Results; D012119:Respiration; D012815:Signal Processing, Computer-Assisted