title: Inference of a nonlinear stochastic model of the cardiorespiratory interaction.
abstract: We reconstruct a nonlinear stochastic model of the cardiorespiratory interaction in terms of a set of polynomial basis functions representing the nonlinear force governing system oscillations. The strength and direction of coupling and noise intensity are simultaneously inferred from a univariate blood pressure signal. Our new inference technique does not require extensive global optimization, and it is applicable to a wide range of complex dynamical systems subject to noise.
authors.affiliation: NASA Ames Research Center, MS 269-2, Moffett Field, CA 94035, USA.
authors.forename: V N
authors.initials: VN
authors.lastname: Smelyanskiy
authors.forename: D G
authors.initials: DG
authors.lastname: Luchinsky
authors.forename: A
authors.initials: A
authors.lastname: Stefanovska
authors.forename: P V E
authors.initials: PV
authors.lastname: McClintock
mesh_terms: D001794:Blood Pressure / Q000502:physiology; D002320:Cardiovascular Physiological Phenomena; D008955:Models, Cardiovascular; D017711:Nonlinear Dynamics; D013269:Stochastic Processes