Power law scaling behavior of physiological time series in marathon races using wavelet leaders and detrended fluctuation analysis

Eva Wesfreid; Véronique Billat

doi:10.1117/12.810641

27 January 2009 Power law scaling behavior of physiological time series in marathon races using wavelet leaders and detrended fluctuation analysis

Eva Wesfreid, Véronique Billat

Author Affiliations +

Proceedings Volume 7248, Wavelet Applications in Industrial Processing VI; 72480H (2009) https://doi.org/10.1117/12.810641
Event: IS&T/SPIE Electronic Imaging, 2009, San Jose, California, United States

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.

Citation Download Citation

Eva Wesfreid and Véronique Billat "Power law scaling behavior of physiological time series in marathon races using wavelet leaders and detrended fluctuation analysis", Proc. SPIE 7248, Wavelet Applications in Industrial Processing VI, 72480H (27 January 2009); https://doi.org/10.1117/12.810641

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