Abstract
The fluctuations of the cardiac interbeat series contain rich information because they reflect variations of other functions on different time scales (e.g., respiration or blood pressure control). Nonlinear measures such as complexity and fractal scaling properties derived from 24 h heart rate dynamics of healthy subjects vary from childhood to old age. In this study, the age-related variations during childhood and adolescence were addressed. In particular, the cardiac interbeat interval series was quantified with respect to complexity and fractal scaling properties. The R-R interval series of 409 healthy children and adolescents (age range: 1 to 22 years, 220 females) was analyzed with respect to complexity (Approximate Entropy, ApEn) and fractal scaling properties on three time scales: long-term (slope β of the power spectrum, log power vs. log frequency, in the frequency range 10−4 to 10−2 Hz) intermediate-term (DFA, detrended fluctuation analysis, α2) and short-term (DFA α1). Unexpectedly, during age 7 to 13 years β and ApEn were higher compared to the age <7 years and age >13 years (β: −1.06 vs. −1.21; ApEn: 0.88 vs. 0.74). Hence, the heart rate dynamics were closer to a 1/f power law and most complex between 7 and 13 years. However, DFA α1 and α2 increased with progressing age similar to measures reflecting linear properties. In conclusion, the course of long-term fractal scaling properties and complexity of heart rate dynamics during childhood and adolescence indicates that these measures reflect complex changes possibly linked to hormonal changes during pre-puberty and puberty.
Highlights
The fluctuations of the cardiac interbeat series exhibit a rich complexity because this series is modulated by different physiological functions under neural control such as respiration, blood pressure control or diurnal variations of activity [1]
After about 30 years of age do clear variations over time become apparent. These results suggest that measures derived from nonlinear dynamics are not affected during childhood in spite of the hormonal changes associated with the timing of pre-puberty and puberty [17,18]
The largest adjusted coefficients of determination were obtained for mean R-R interval (R2 = 0.40), very low frequency oscillations (VLF) (R2 = 0.33), detrended fluctuation analysis (DFA) a1 (R2 = 0.29) and the slope b (R2 = 0.23)
Summary
The fluctuations of the cardiac interbeat series exhibit a rich complexity because this series is modulated by different physiological functions under neural control such as respiration, blood pressure control or diurnal variations of activity [1]. Taking into account that each modulating function has specific temporal fluctuations (e.g. specific mean frequency and correlation properties) this series reflects the integration of many different characteristics of fluctuations and shows chaotic and multifractal properties [2,3]. Spectral analysis of heart rate variability (HRV) quantifies sinus wavelike oscillations of the cardiac interbeat series [4] whereas Approximate Entropy (ApEn) and Sample Entropy quantify irregularity (complexity) [5,6], and detrended fluctuation analysis (DFA) quantifies fractal properties (self-similarity on different time scales) analogous to spatial self-similarity [7,8]. A homeodynamic view of physiological functions is required [9]
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