1.Investigations that assess cardiac autonomic function include non-linear techniques such as fractal dimension and approximate entropy in addition to the common time and frequency domain measures of both heart period and heart rate. This article evaluates the differences in using heart rate versus heart period to estimate fractal dimensions and approximate entropies of these time series.
2.Twenty-four-hour ECG was recorded in 23 normal subjects using Holter records. Time series of heart rate and heart period were analysed using fractal dimensions, approximate entropies and spectral analysis for the quantification of absolute and relative heart period variability in bands of ultra low (< 0.0033 ;Hz), very low (0.0033–0.04 ;Hz), low (0.04–0.15 ;Hz) and high (0.15–0.5 ;Hz) frequency.
3.Linear detrending of the time series did not significantly change the fractal dimension or approximate entropy values. We found significant differences in the analyses using heart rate versus heart period between waking up and sleep conditions for fractal dimensions, approximate entropies and absolute spectral powers, especially for the power in the band of 0.0033–0.5 ;Hz. Log transformation of the data revealed identical fractal dimension values for both heart rate and heart period. Mean heart period correlated significantly better with fractal dimensions and approximate entropies of heart period than did corresponding heart rate measures.
4.Studies using heart period measures should take the effect of mean heart period into account even for the analyses of fractal dimension and approximate entropy. As the sleep–awake differences in fractal dimensions and approximate entropies are different between heart rate and heart period, the results should be interpreted accordingly.
- approximate entropy
- fractal dimension
- heart period
- heart rate
- spectral analysis
- The Biochemical Society and the Medical Research Society © 1998