Performance evaluation of multi-component instantaneous frequency estimation techniques for heart rate variability analysis

Abstract

Accurate instantaneous frequency (IF) estimation of the non-stationary heart rate signal is important in quantifying the heart rate variability (HRV) measures. This study compares the effectiveness of four IF estimation methods in analyzing HRV signals. Specifically, they are the direct localization of the maximal peaks in the signal time-frequency distribution (TFD), IF estimation based on component linking technique in the TFD, IF estimation using the TFD with optimal windows based on intersection of confidence intervals rule and complex demodulation. Results of applying the IF estimation methods to synthesized and real piglet HRV signals reveal that, the approach using component linking technique outperform the other techniques with respect to the accuracy and implementation. It provides new insights in studying the evolution of the autonomic nervous regulation of the cardiovascular function over time.