Modeling of Heart Rate Variability Using Time-Frequency Representations

Abstract

The heart rate variability signal is highly correlated with the respiration even at high workload exercise. It is also known that this phenomenon still exists during increasing exercise. In the current study, we managed to model this correlation during increasing exercise using the time varying integral pulse frequency modulation (TVIPFM) model that relates the mechanical modulation (MM) to the respiration and the cardiac rhythm. This modulation of the autonomic nervous system (ANS) is able to simultaneously decrease sympathetic and increase parasympathetic activity. The TVIPFM model takes into consideration the effect of the increasing exercise test, where the effect of a time-varying threshold on the heart period is studied. Our motivation is to analyze the heart rate variability (HRV) acquired by time varying integral pulse frequency modulation using time frequency representations. The estimated autonomic nervous system (ANS) modulating signal is filtered throughout the respiration using a time varying filtering, during exercise stress testing. And after summing power of the filtered signal, we compare the power of the filtered modulation of the ANS obtained with different time frequency representations: smoothed pseudo Wigner–Ville representation, spectrogram and their reassignments. After that, we used a student t-test to compare the power of heart rate variability in the frequency band of respiration and elsewhere.