Markov model and entropy of sequences in isodistributional surrogate data

Surrogate data method is commonly required to confirm the non-accidental nature of simultaneous fluctuations of heart rate (HR) and blood pressure (BP) due to the spontaneous baroreceptor reflex (sBRR) mechanism. Previously proposed finite, ergodic Markov model with memory, enables derivation of all BRR temporal parameters for isodistributional (ID) surrogate data in closed form, thus eliminating the need for surrogate generation and analysis. The goodness of fit for surrogate time series of 37 healthy humans is tested. The expected values provided by the model showed excellent accordance with calculated time averages. Besides, the study introduces a new feature of sBRR entropy.