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Journal Achievements of Modern Radioelectronics №5 for 2011 г.
Article in number:
Analysis of Persistent and Antipersistent Correlations in Biomedical Signals
Keywords: biomedical signals persistent and anti-persistent correlations normalized range method "generalized" (local) Hurst exponent
Authors:
S.A. Demin, B.N. Galimzyanov, O.Yu. Panischev
Abstract:
We analyze a long-range and short-range correlation dynamics in human physiological signals on the basis of normalized range method (R/S analysis). We calculate the Hurst exponent by the "fast algorithm" and as well as the window-time averaging algorithm with the following linear approximation and piecewise-linear approximation. The Hurst exponent allows dividing time signals depending on correlation properties at minimum information about the studied system. Hurst exponent has been calculated for a Parkinsonian tremor velocity, a human brain bioelectric activity at epilepsy, neuromagnetic responses to chromatic flickering stimuli from epileptic patients, an epidemic dynamics of ARD and grippe. In case of nonstationary time series in addition to using the «fast» and «slow» algorithm we analyze the Hurst exponent local behavior. Essence of the Hurst exponent localization procedure consists in extracting information about the local persistent and antipersistent features of time signals as well as studying their local structure. Actually the generalized (local) Hurst exponent is the more sensitive criterion and it allows obtaining additional information about the trend stability in local sample. The behavior of Hurst exponent varies not only because of the signal representation as sequence of samples, but also because of slow variations of correlation noise (for natural processes). We have calculated generalized Hurst exponent for human EEG at the epileptic seizure and for ARD epidemic dynamics in social networks. Within the frameworks of R/S analysis we have divided the biomedical signals depending on the degree of stochasticity or/and determinancy of physiological processes. We have revealed the increasing persistent correlations in case of the treatment of Parkinsonian patient. We have discovered the reverse character (decrease/increase) of correlation dynamics during the epileptic seizure and the similar character of ARD and grippe epidemic dynamics in social networks. The Hurst exponent time behavior demonstrates alternation of the persistent and anti-persistent correlations in local areas of human EEG at epileptic seizure, and also in ARD and grippe epidemic dynamics in Vahitov district of Kazan. The findings demonstrate the unique capabilities in detecting the correlation dynamics variations in live systems and allows us to speak that we need in creation of the «individual medicine of future».
Pages: 61-71
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