  We investigate the Markov nature, Cascade of information from large time
scale to small scale and extended self similarity properties of the beat to
beat fluctuations of healthy subjects as well as those with congestive heart
failure. To check the Markov nature, we use a novel inverse method that
utilizes a set of data to construct a simple equation that governs the
stochastic process for which the data have been measured, hence enabling us to
reconstruct the stochastic process. The inverse method provides a novel
technique for distinguishing the two classes of subjects in terms of a drift
and a diffusion coefficients which behave completely differently for the two
classes of subjects.To investigate the cascade of information from large to
small time scales we also analyze the statistical properties of interbeat
intervals cascade by considering the joint probability distribution for two
interbeat increments. As a result, the joint probability distributions of the
increments in the interbeat intervals obey a Fokker-Planck equation. Finally we
analyze the extended self-similarity (ESS) in the beat-to-beat fluctuations in
the heart rates of healthy and congestive heart failure subjects.The proposed
methods provide the novel techniques for distinguishing the two classes of
subjects in terms of the drift and diffusion coefficients, intermittency
exponents which behave differently for two classes of the subjects, namely,
healthy subjects and those with congestive heart failure.
