Heart Rate Variability Analysis for Abnormality Detection Using Time Frequency Distribution – Smoothed Pseudo Winger Ville Method

Heart rate variability (HRV) is derived from the time duration between consecutive heart beats. The HRV is to reflect the heart’s ability to adapt to changing circumstances by detecting and quickly responding to unpredictable stimuli to cardiac system. Depressed HRV is a powerful predictor of mortality and of arrhythmic complications in patients after diseases like acute Myocardial Infarction. The degree of variability in the HR provides information about the nervous system control on the HR and the heart’s ability to respond .Spectral analysis of HRV is a frequency domain approach to assess the cardiac condition. In this paper one such method for analyzing HRV signals known as smoothed pseudo Wigner Ville distribution (SPWVD) is applied, The sub-band decomposition technique used in SPWVD, based on Instantaneous Autocorrelation (IACR) of the signal provides time-frequency representation for very lowfrequency (VLF), low-frequency (LF) and high-frequency (HF) regions identified in HRV spectrum. Results suggest that SPWVD analysis provides useful information for the assessment of dynamic changes and patterns of HRV during cardiac abnormalities.