Dynamic modeling of respiratory sinus arrhythmia component from HRV with multivariate Kalman smoother

Abstract

The estimates of heart rate variability (HRV) low frequency (LF) and high frequency (HF) components with constant frequency bands may distort when the frequency of respiratory sinus arrhythmia induced HF component approaches the LF-HF frequency limit. In this study we present a method for dynamically estimating the LF-HF limit and dividing the spectrum to LF and HF components that can overlap. The method is based on multivariate autoregressive model which is solved dynamically with Kalman smoother algorithm. The spectra of each individual pole with all the zeros are calculated and then multiplied with a Hanning window on the pole frequency. These spectra are summed to LF or HF components. The method was applied to three subjects whose electrocardiogram and respiration was recorded during a controlled breathing protocol. The results show that the HF component power increases when breathing frequency decreases. Also the component powers obtained with the presented method are reliable even when LF and HF frequencies are close to each other.