Detrended fluctuation analysis (DFA) is the most popular method for assessing the fractal characteristics of heart rate (HR). Traditionally, short-term and long-term scale coefficients, alpha(1) and alpha(2), are calculated from DFA. We recently showed that the traditional approach oversimplifies a more complex phenomenon better represented by a continuous spectrum of scale coefficients. In this paper we present a DFA based method for describing the HR fractal dynamics with a temporal spectrum of scale exponents, alpha(t), rather than by a model of lumped parameters, alpha(1) and alpha(2). Since alpha(t) is a function of the temporal scale, its interpretation is facilitated when conditions with different mean HR are compared. In this work, we reanalyze HR data, collected by our group in previous studies, by applying the proposed alpha(t) spectrum. We quantify the effects of gender, ageing, posture and activity level, and the alterations induced by exposure to high and very-high altitude hypoxia, on alpha(t). Most of the results may be interpreted in terms of changes of cardiac autonomic regulation, and indicate clearly that the new proposed DFA spectrum provides a more faithful and interpretable description of the HR fractal dynamics than traditional alpha(1) and alpha(2) scale coefficients.
Assessing the fractal structure of heart rate by the temporal spectrum of scale exponents: a new approach for detrended fluctuation analysis of heart rate variability
Castiglioni P;
2011-01-01
Abstract
Detrended fluctuation analysis (DFA) is the most popular method for assessing the fractal characteristics of heart rate (HR). Traditionally, short-term and long-term scale coefficients, alpha(1) and alpha(2), are calculated from DFA. We recently showed that the traditional approach oversimplifies a more complex phenomenon better represented by a continuous spectrum of scale coefficients. In this paper we present a DFA based method for describing the HR fractal dynamics with a temporal spectrum of scale exponents, alpha(t), rather than by a model of lumped parameters, alpha(1) and alpha(2). Since alpha(t) is a function of the temporal scale, its interpretation is facilitated when conditions with different mean HR are compared. In this work, we reanalyze HR data, collected by our group in previous studies, by applying the proposed alpha(t) spectrum. We quantify the effects of gender, ageing, posture and activity level, and the alterations induced by exposure to high and very-high altitude hypoxia, on alpha(t). Most of the results may be interpreted in terms of changes of cardiac autonomic regulation, and indicate clearly that the new proposed DFA spectrum provides a more faithful and interpretable description of the HR fractal dynamics than traditional alpha(1) and alpha(2) scale coefficients.
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