Applying fractal analysis to short sets of heart rate variability data |
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Authors: | M?A?Pe?a J?C?Echeverría M?T?García R?González-Camarena |
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Institution: | (1) Electrical Engineering Department, Universidad Autónoma Metropolitana-Izt., San Rafael Atlixco #186, 09340 Mexico City, Mexico;(2) Health Science Department, Universidad Autónoma Metropolitana-Izt., San Rafael Atlixco #186, 09340 Mexico City, Mexico |
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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. |
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Keywords: | RR dynamics Detrended fluctuation analysis Scaling exponent Intraclass correlation Interchangeability |
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