Abstract
The paper mainly introduces a method combining detrended fluctuation analysis (DFA) with moving fitting window to analyze the heartbeat time series in different pathologic states. Compared to traditional approaches, the estimation of the local scale exponent method shows more details of scale properties and provides a reliable analysis. We also quantify the effects of outliers, subseries length and gender on scale spectrum α(s). Comparing the results of the healthy subjects, patients with congestive heart failure (CHF), and patients with atrial fibrillation (AF) indicate clearly that at small scales, the exponents show great volatility and they all have their own scale pattern. In addition, the length of the series should be relatively longer to avoid properties losing. For the effect of gender, contrary to healthy results, the scale exponents of CHF male subjects are continuously greater than female. The spectrum of DFA scale exponents provides a new way to measure the heartbeat series and distinguishes healthy and pathologic groups.
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The financial supports from the funds of the China National Science (61071142, 61371130), the Beijing National Science (4122059), and the National High Technology Research Development Program of China (863 Program) (2011AA110306) are gratefully acknowledged.
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Xia, J., Shang, P. & Wang, J. Estimation of local scale exponents for heartbeat time series based on DFA. Nonlinear Dyn 74, 1183–1190 (2013). https://doi.org/10.1007/s11071-013-1033-2
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DOI: https://doi.org/10.1007/s11071-013-1033-2