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Proceedings Paper

Power law scaling behavior of physiological time series in marathon races using wavelet leaders and detrended fluctuation analysis
Author(s): Eva Wesfreid; Véronique Billat
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Paper Abstract

Data power law scaling behavior is observed in many fields. Velocity of fully developed turbulent flow, telecommunication traffic in networks, financial time series are some examples among many others. The goal of the present contribution is to show the scaling behavior of physiological time series in marathon races using wavelet leaders and the Detrended Fluctuation Analysis. Marathon race is an exhausting exercise, it is referenced as being a model for studying the limits of human ambulatory abilities. We analyzed the athlete's heart rate and speed time series recorded simultaneously. We find that the heart cost time series, number of heart beats per meter, increases with the fatigue appearing during the marathon race, its tendency grows in the second half of the race for all athletes. For most physiological time series, we observed a concave behavior of the wavelet leaders scaling exponents which suggests a multifractal behavior. Otherwise, the Detrended Fluctuation Analysis shows short and long range time-scale power law exponents with the same break point for each physiological time series and each athlete. The short range time-scale exponent increases with fatigue in most physiological signals.

Paper Details

Date Published: 28 January 2009
PDF: 6 pages
Proc. SPIE 7248, Wavelet Applications in Industrial Processing VI, 72480H (28 January 2009); doi: 10.1117/12.810641
Show Author Affiliations
Eva Wesfreid, CMLA, Ecole Normale Supérieure de Cachan (France)
LMPA, Univ. du Littoral (France)
Véronique Billat, Unité INSERM 902, Génopole-Univ. d'Evry Val d'Essonne (France)


Published in SPIE Proceedings Vol. 7248:
Wavelet Applications in Industrial Processing VI
Frederic Truchetet; Olivier Laligant, Editor(s)

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