CASPIAN JOURNAL
MANAGEMENT AND HIGH TECHNOLOGIES
Using multifractal analysis of short-termobjectives of heart rate variability in the treatment of hypertension
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Read | Borisov Vasiliy I., Kublanov Vladimir Semenovich Using multifractal analysis of short-termobjectives of heart rate variability in the treatment of hypertension // Caspian journal : management and high technologies. — 2014. — №3. — pp. 134-143. |
Borisov Vasiliy I. - postgraduate student, Ural Federal University named after first President of Russia B.N. Yeltsin, 19 ul. Mira, Yekaterinburg, 620002, Russian Federation, vi.borisov.official@gmail.com
Kublanov Vladimir Semenovich - D.Sc. (Engineering), Professor, Ural Federal University named after first President of Russia B.N. Yeltsin, 19 ul. Mira, Yekaterinburg, 620002, Russian Federation, kublanov@mail.ru
The object of this article is to study the informativeness and efficiency of the multifractal formalism and methods of fuzzy logic in the analysis of time series of heart rate variability. These series were obtained for during short-term (five-minute) functional studies to identify patients belonging to the groups of different nosological status. The studies were used: the method of multifractal analysis of the fluctuation; theory of fuzzy sets; software package MATLAB. The obtained results are the widths of the multifractal spectrum's of two functional states (nosological status) of the patients. They were analyzed using the fuzzy clustering algorithm. Changes in the centers of clusters allow us to identify differences of patients nosological status on the basis of data for the series of heart rate variability, obtained by performing the passive orthostatic test. These nosological status correspond to the characteristics of healthy and sick patients with II-III degree of hypertension for which there is a clinically proven improvement after treatment.
Key words: биомедицинские сигналы, анализ вариабельности сердечного ритма, методы нелинейной динамики, методы нечеткой логики, временные ряды, мультифрактальный анализ, алгоритм нечеткой кластеризации, результаты функциональных исследований, biomedical signals, anal