Detection of nonlinearity in cardiovascular variability signals using cyclostationary analysis.

Abstract

A novel approach for detection of polynomial nonlinearity in the neuro-cardiovascular system based on cyclostationary analysis is presented. Metronome breathing is employed to provide a sinusoidal input to the neuro-cardiovascular system in which Heart Rate Variability (HRV) and Blood Pressure Variation (BPV) are considered as its outputs. The presence of new harmonics of the main respiratory rate in the HRV and BPV is investigated by using the concept of (self) phase and (self) frequency coupling. It is shown that a second order polynomial nonlinear system is actually involved in producing the HRV and BPV. The strength of this nonlinearity decreases with increasing the breathing rate.