2003
DOI: 10.1103/physreve.67.062901
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Long- and short-time analysis of heartbeat sequences: Correlation with mortality risk in congestive heart failure patients

Abstract: We analyze RR heartbeat sequences with a dynamic model that satisfactorily reproduces both the long-and the short-time statistical properties of heart beating. These properties are expressed quantitatively by means of two significant parameters, the scaling ␦ concerning the asymptotic effects of long-range correlation, and the quantity 1Ϫ establishing the amount of uncorrelated fluctuations. We find a correlation between the position in the phase space (␦,) of patients with congestive heart failure and their m… Show more

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Cited by 13 publications
(19 citation statements)
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“…NPR processes reflect a condition shared by the phenomenological models of glassy dynamics as shown by Bouchaud (1992), laser cooling as discussed by Bardou et al (2002) and models of atomic transport in optical lattices given by Lutz (2004). Other NPR processes have been found at the core of the correlations in DNA sequences by Mohanty and Narayana Rao (2000), heart-beat variability by Allegrini et al (2003a) and and earthquake statistics by Mega et al (2003).…”
Section: Introductionmentioning
confidence: 92%
“…NPR processes reflect a condition shared by the phenomenological models of glassy dynamics as shown by Bouchaud (1992), laser cooling as discussed by Bardou et al (2002) and models of atomic transport in optical lattices given by Lutz (2004). Other NPR processes have been found at the core of the correlations in DNA sequences by Mohanty and Narayana Rao (2000), heart-beat variability by Allegrini et al (2003a) and and earthquake statistics by Mega et al (2003).…”
Section: Introductionmentioning
confidence: 92%
“…DE is specially suitable for intermittent signals, i.e., for time series where bursts of activity are separated by periods of quiescent and regular behavior. The technique has been designed to study the time distribution of some markers (or events) along the time series and thus discover whether these events satisfy the independence condition τ i τ j = τ i τ j (i = j) where τ i is the time interval between the marker labeled i − 1 and the next one i [10,15,16,17]. As marker we use here a very simple definition: each trade in the time series is a marker.…”
Section: Diffusion Entropy Analysismentioning
confidence: 99%
“…It is important to note that this important conclusion is supported by the analytical treatment of Ref. [3]. The authors of Ref.…”
Section: Memory Beyond Memorymentioning
confidence: 65%
“…The authors of Ref. [3] shows that in the long-time limit the memory of the pseudo-events is lost, and the process under study becomes equivalent to a Lévy flight, corresponding to the power index µ of the crucial events.…”
Section: Memory Beyond Memorymentioning
confidence: 99%