Heart Instantaneous Frequency Based Estimation of HRV from Blood Pressure Waveforms

The heart rate variability (HRV) is a measure based on the time position of the electrocardiogram (ECG) R-waves. There is a discussion whether or not we can obtain the HRV pattern from blood pressure (BP). In this paper, we propose a method for estimating HRV from a BP signal based on a HIF algorithm and carrying out experiments to compare BP as an alternative measurement of ECG to calculate HRV. Based on the hypotheses that ECG and BP have the same harmonic behavior, we model an alternative HRV signal using a nonlinear algorithm, called heart instantaneous frequency (HIF). It tracks the instantaneous frequency through a rough fundamental frequency using power spectral density (PSD). A novelty in this work is to use fundamental frequency instead of wave-peaks as a parameter to estimate and quantify beat-to-beat heart rate variability from BP waveforms. To verify how the estimate HRV signals derived from BP using HIF correlates to the standard gold measures, i.e. HRV derived from ECG, we use a traditional algorithm based on QRS detectors followed by thresholding to localize the R-wave time peak. The results show the following: 1) The spectral error caused by misestimation of time by R-peak detectors is demonstrated by an increase in high-frequency bands followed by the loss of time domain pattern. 2) The HIF was shown to be robust against noise and nuisances. 3) By using statistical methods and nonlinear analysis no difference between HIF derived from BP and HRV derived from ECG was observed.