V.S. Kublanov - Dr. Sc. (Eng), Professor, Head of the Research of Medical and Biological Engineering High-Tech Center, Ural Federal University named after first President of Russia B.N. Yeltsin (Ekaterinburg, Russia). E-mail: kublanov@mail.ru
V.I. Borisov - Dr. Sc. (Eng), Professor, Head of the Department of Radio Electronics Information Systems, Ural Federal University named after first President of Russia B.N. Yeltsin. E-mail: sergey_porshnev@mail.ru
S.V. Porshnev - Post-Graduate Student, Department of Radio Electronics Information Systems, Ural Federal University named after first President of Russia B.N. Yeltsin. E-mail: vi.borisov.official@gmail.com

In this article we considered the possibility of an approach identifying the status of patients different groups, using the Hurst exponents calculated for short-term series of heart rate variability (HRV). To solve this problem we examined the change of the Hurst exponent depending on the length of the time series to assess the adequacy of a time series of dynamic chaos model. We estimate the change Hurst exponent of HRV time series at rest andfunctional studiesfor the analysis of time series for different groups of patients of various nosological statuses. It is shown that the parameters of probability density functions changes in the values of Hurst exponent correspond to change the functional state of the patients. This indicates there is compliance between the distributions of changes Hurst exponent and changes in functional status of patients. The results are valid for time series with independent Hurst exponent from the length of the time scale interval. If the value of Hurst exponent depends on the value of scale, it is a sign of the multifractal nature of the signal. Estimates are obtained using the multifractal analysis of time series of groups of healthy patients and in patients with arterial hypertension II - III degree (before treatment and after treatment course). Vector of changes in distribution the width of multifractal spectrum of time scales of the spectral components of HRV ill patients after treatment has a direction toward the corresponding indicators of healthy patients. This dynamics corresponds to changes in clinical parameters.