OBJECTIVES: The purpose of the study was to investigate the short- and long-term variations in the non-linear dynamics of heart rate variability, and to determine the relationships between conventional time and frequency domain methods and the newer non-linear methods of characterizing heart rate variability. METHODS: Twelve healthy subjects were investigated by 3-h ambulatory ECG recordings repeated on 3 separate days. Correlation dimension, non-linear predictability, mean heart rate, and heart rate variability in the time and frequency domains were measured and compared with the results from corresponding surrogate time series. RESULTS: A small significant amount of non-linear dynamics exists in heart rate variability. Correlation dimensions and non-linear predictability are relatively specific parameters for each individual examined. The correlation dimension is inversely correlated to the heart rate and describes mainly linear correlations. Non-linear predictability is correlated with heart rate variability measured as the standard deviation of the R-R intervals and the respiratory activity expressed as power of the high-frequency band. The dynamics of heart rate variability changes suddenly even during resting, supine conditions. The abrupt changes are highly reproducible within the individual subjects. CONCLUSIONS: The study confirms that the correlation dimension of the R-R intervals is mostly due to linear correlations in the R-R intervals. A small but significant part is due to non-linear correlations between the R-R intervals. The different measures of heart rate variability (correlation dimension, average prediction error, and the standard deviation of the R-R intervals) characterize different properties of the signal, and are therefore not redundant measures. Heart rate variability cannot be described as a single chaotic system. Instead heart rate variability consists of intertwined periods with different non-linear dynamics. It is hypothesized that the heart rate is governed by a system with multiple "strange" attractors.
Keywords: Adult; Electrocardiography, Ambulatory; Female; Heart Rate; Humans; Male; Models, Cardiovascular; Nonlinear Dynamics; Signal Processing, Computer-Assisted