Multi-scale analysis of HRV data

The inverse power-law or 1/f^α type attenuation of the normal Heart Rate Variability (HRV) spectrum suggests that HRV exhibits self-similar fluctuations over a multiplicity of scales. Such behavior is best characterized by measures which capture the scale-invariant nature of the signal. In this pilot study, the authors investigate the use of the discrete wavelet transform as a multi-scale decomposition tool to monitor the statistical scale-invariant properties of the healthy HRV expressed both versus beat number and time. The objective is to develop an understanding of the statistical scale-invariant structure of the signal in the wavelet domain for potential use in clinical applications