title: Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series.
abstract: The healthy heartbeat is traditionally thought to be regulated according to the classical principle of homeostasis whereby physiologic systems operate to reduce variability and achieve an equilibrium-like state [Physiol. Rev. 9, 399-431 (1929)].  However, recent studies [Phys. Rev. Lett. 70, 1343-1346 (1993); Fractals in Biology and Medicine (Birkhauser-Verlag, Basel, 1994), pp. 55-65] reveal that under normal conditions, beat-to-beat fluctuations in heart rate display the kind of long-range correlations typically exhibited by dynamical systems far from equilibrium [Phys. Rev. Lett. 59, 381-384 (1987)].  In contrast, heart rate time series from patients with severe congestive heart failure show a breakdown of this long-range correlation behavior.  We describe a new method--detrended fluctuation analysis (DFA)--for quantifying this correlation property in non-stationary physiological time series.  Application of this technique shows evidence for a crossover phenomenon associated with a change in short and long-range scaling exponents.  This method may be of use in distinguishing healthy from pathologic data sets based on differences in these scaling properties.
authors.affiliation: Cardiovascular Division, Harvard Medical School, Boston, Massachusetts 02215, USA.
authors.forename: C K
authors.initials: CK
authors.lastname: Peng
authors.forename: S
authors.initials: S
authors.lastname: Havlin
authors.forename: H E
authors.initials: HE
authors.lastname: Stanley
authors.forename: A L
authors.initials: AL
authors.lastname: Goldberger
mesh_terms: D006331:Heart Diseases / Q000503:physiopathology; D006333:Heart Failure / Q000503:physiopathology*; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D008433:Mathematics; D015233:Models, Statistical; D017711:Nonlinear Dynamics; D013269:Stochastic Processes; D013599:Systole / Q000502:physiology*; D013997:Time Factors