Wavelet Transform based HRV Analysis

Heart rate variability (HRV) is a measure of variations of the successive heart beats. It is usually calculated by analyzing the time series of beat-to-beat intervals from ECG signal. HRV is considered as an indicator of the activity of autonomic regulation of circulatory function and as the one of the most significant methods of analyzing the activity of the autonomic nervous system. In this study a Wavelet Packet Transform (WPT) based HRV feature extraction method is presented and compared with the Fourier transformed based one. The results show that a good WPT decomposition gives a significant index of sympathovagal balance, which is the variance (or power) of the ECG signal changes as a function of frequency.