Estimation of Power Spectral Density in Different Frequency Bands

Abstract

Heart Rate (HR) in human being keeps on changing and meets with the requirements of body giving rise to Heart Rate Variability. This variability is therefore indicating of adaptability of heart rate variability (HRV). Heart Rate Variability signal analysis has become a widely employed tool in the diagnosis process of cardiovascular disease and powerful means of observing interplay between the sympathetic and parasympathetic nervous system. Over many years researchers have worked upon various techniques to gauge the variability in the Heart Rate and the selection of sampling frequency plays a critical role in obtaining the Power Spectral density. This work presents an algorithm to obtain the Power Spectral Density of Heart Rate Variability without linear interpolation and with linear interpolation using MATLAB software tool and also helps us to determine the Power Spectral Density of RR interval sequence to quantify Heart Rate Variability (HRV) into well defined and well documented frequency bands. This work is done with 34 healthy subjects taken randomly from MIT-BIH Normal Sinus Rhythm Database (nsrdb), Normal Sinus Rhythm RR interval Database (nsr2db), MIT-BIH Arrhythmia Database (mitdb) with variation in age from 20 years to 76 years and the power is calculated in different frequency bands VLF, LF, HF and the variation in powers is estimated with the help of scatter plots between standard deviation (σ) and the Relative Band Power Difference (RBPD). The obtained plots show the appropriate selection of sampling frequency. The results obtained from the visual inspection of scatter plots and from Pearson‘s correlated values are same.