  We describe a method for analyzing the stochasticity in the non-stationary
data for the beat-to-beat fluctuations in the heart rates of healthy subjects,
as well as those with congestive heart failure. The method analyzes the returns
time series of the data as a Markov process, and computes the Markov time
scale, i.e., the time scale over which the data are a Markov process. We also
construct an effective stochastic continuum equation for the return series. We
show that the drift and diffusion coefficients, as well as the amplitude of the
returns time series for healthy subjects are distinct from those with CHF.
Thus, the method may potentially provide a diagnostic tool for distinguishing
healthy subjects from those with congestive heart failure, as it can
distinguish small differences between the data for the two classes of subjects
in terms of well-defined and physically-motivated quantities.
