Threshold modeling of autonomic control of heart rate variability

Even in the absence of external perturbation to the human cardiovascular sy stem, measures of cardiac function, such as heart rate, vary with time in n ormal physiology. The primary source of the variation is constant regulatio n by a complex control system which modulates cardiac function through the autonomic nervous system, Here, we present methods of characterizing the st atistical properties of the underlying processes that result in variations in ECG R-ware event times within the framework of an integrate-and-fire mod el. We first present techniques for characterizing the noise processes that result in heart rate variability even in the absence of autonomic input. A relationship is derived that relates the spectrum of R-R intervals to the spectrum of the underlying noise process. We then develop a technique for t he characterization of the dynamic nature of autonomically related variabil ity resulting from exogenous inputs, such as respiratory-related modulation . A method is presented for the estimation of the transfer function that re lates the respiratory-related input to the variations in R-wave event times . The result is a very direct analysis of autonomic control of heart rate v ariability through noninvasive measures, which provides a method for assess ing autonomic function in normal and pathological states.