Fractal analysis of cardiac dynamicsthe application of detrended fluctuation analysis on short-term heart rate variability

Resumen

Fractal measures of heart rate variability have been proposed as comple- mentary to time and frequency domain indices and, in many cases, have proven to be valid predictors of cardiovascular disease. However, their re- lationship with respiratory parameters and more common health indicators such as vagal tone is still not clear. In this doctoral dissertation, we examine the effect of breathing frequency, average heart period and pharmacological parasympathetic blockade on the fractal properties of short-term cardiac dynamics. Heart period analysis is performed with a mathematical soft- ware (KARDIA) developed for the purpose of our studies, which is also presented in this thesis. The results of our first study revealed that: 1) the periodical properties of RSA produce a change of the correlation ex- ponent in HRV at a scale corresponding to the respiratory period, 2) the short-term DFA exponent is significantly reduced when breathing frequency rises from 0.1Hz to 0.2Hz. In the second study atropine was administered to six healthy males in a controlled laboratory setting. Parasympathetic blockade produced a significant increase in the ¿1 scaling exponent assessed by detrended fluctuation analysis. We showed that this was produced by smooth local trends in the data, rather than an alteration in underlining dynamics. Our results call attention to a methodological and conceptual problem related to the application of fractal measures to a limited range of scales in which single physiological control mechanisms exert a dominant influence.