Spectral analysis of cardiac rate variability

Abstract

In the last years relationship between autonomic nervous system (ANS) function and cardiovascular mortality has been recognized. This has motivated research to find quantitative markers of autonomic balance. Heart rate variability (HRV) is one of the most promising methods. HRV is defined as the variations occurred in the time interval between consecutive heartbeats and it is thought to depend on the ANS modulation. Tacogram (recording of cardiac frequency in time) is used to evaluate HRV. The study of HRV started 30 years ago and has gained importance in the last 10 years. There are several methods to evaluate HRV. The most accepted today are frequency domain methods (spectral analysis). Spectral analysis consists in the decomposition in order to obtain the spectral components. There are high frequency components (HF), related to vagal tone, low frequency (LF) components, related to the modulation of both sympathetic and vagal modulation, and very low frequency components which have not been related to any physiological variable. Time domain methods, are basically statistic and evaluate variability using means and standard deviations. These methods seem to have less advantages than spectral methods. HRV is correlated with physiological adaptations to changes in internal and external environment and to the presence of diseases. This article presents the main techniques in the time and frequency domains and their relationship with physiological changes and specific diseases.