Abstract
The analysis with the Hurst exponent (H) shows the degree of persistence or anti-persistence of the time series, which has allowed quantifying the correlation between the time series data. In this paper, the estimation of the Hurst exponent was based on two methods: the discrete second-order derivative (DSOD) and its Wavelet-based adaptation (WDSOD). The main purpose is to apply the H exponent estimation for the study of complexity in the physiological signals of heartbeat, in order to find information that allows us to evaluate sleep-wake phases in 54 healthy subjects and 44 patients with congestive heart failure (CHF), as well as qualitatively determine cardiac stress and physical condition in stress tests of 30 young subjects, 11 middle-aged adults, both groups with a sedentary lifestyle, and 10 normally active subjects, all without any apparent cardiovascular disease. This method could be considered acceptable to show changes in the dynamics of the cardiovascular system since the results indicate persistence in the RR series of healthy subjects in the sleep and wake phases, in sedentary healthy subjects at rest and in healthy active subjects, otherwise is observed in subjects with CHF in both phases and in sedentary young and adult subjects during physical activity, which showed antipersistence. Therefore, this parameter could be very useful to verify the health state and at least qualitatively determine the stress to which the heart is submitted and the tolerance to exercise during physical activity.
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