  A new technique is introduced to reconstruct a nonlinear stochastic model of
the cardiorespiratory interaction. Its inferential framework uses a set of
polynomial basis functions representing the nonlinear force governing the
system oscillations. The strength and direction of coupling, and the noise
intensity are simultaneously inferred from a univariate blood pressure signal,
monitored in a clinical environment. The technique does not require extensive
global optimization and it is applicable to a wide range of complex dynamical
systems subject to noise.
