Applying fractal analysis to short sets of heart rate variability data
- 29 January 2009
- journal article
- Published by Springer Science and Business Media LLC in Medical & Biological Engineering & Computing
- Vol. 47 (7), 709-717
- https://doi.org/10.1007/s11517-009-0436-1
Abstract
The aim of this study was to explore the interchangeability of fractal scaling exponents derived from short- and long-term recordings of real and synthetic data. We compared the α1 exponents as obtained by detrended fluctuation analysis from RR-interval series (9 am to 6 pm) of 54 adults in normal sinus rhythm, and the α1 estimated from shorted segments of these series involving only 50, 100, 200 and 300 RR intervals. Three series of synthetic data were also analysed. The principal finding of this study is the lack of individual agreement between α1 derived from long and short segments of HRV data as indicated by the existence of bias and low intraclass correlation coefficient (r i = 0.158). The extent of variation in the estimation of α1 from real data does not only appear related to segments’ length, but also to different dynamics among subjects or lack of uniform scaling behaviour. However, we did find statistical agreement between the means of α1 exponents from long and short segments, even for segments involving just 50 RR intervals. According to results of synthetic series, the 95% confidence interval found for the variation of α1 using segments with 300 samples is [−0.1783 + 0.1828]. Caution should be taken concerning the use of short segments to obtain representative exponents of fractal RR dynamics; a circumstance not fully considered in several studies.Keywords
This publication has 52 references indexed in Scilit:
- Complexity of heartbeat interval series in young healthy trained and untrained menPhysiological Measurement, 2008
- Scaling Characteristics of Heart Rate Time Series Before the Onset of Ventricular TachycardiaAnnals of Biomedical Engineering, 2006
- Prenatal RR fluctuations dynamics: detecting fetal short-range fractal correlationsPrenatal Diagnosis, 2006
- Comparison of RR-interval scaling exponents derived from long and short segments at different wake periodsPhysiological Measurement, 2006
- Physiological Background of the Loss of Fractal Heart Rate DynamicsCirculation, 2005
- Effect of nonstationarities on detrended fluctuation analysisPhysical Review E, 2002
- Relationship between detrended fluctuation analysis and spectral analysis of heart-rate variabilityPhysiological Measurement, 2002
- What is physiologic complexity and how does it change with aging and disease?Neurobiology of Aging, 2001
- Scale Invariance in the Nonstationarity of Human Heart RatePhysical Review Letters, 2001
- STATISTICAL METHODS FOR ASSESSING AGREEMENT BETWEEN TWO METHODS OF CLINICAL MEASUREMENTThe Lancet, 1986