Poincar\'{e} parameters and principal component analysis of Heart rate variability of subjects with health disorder

Abstract

Heart rate variability,important marker for modulation of autonomic nervous system is studied for diabetic,hypertensive and control group of subjects.Lagged Poincar\'{e} plot of heart rate(HR),method of principal component analysis and auto-correlation of HR fluctuation are used to analyze HR obtained from ECG signal recorded over short time duration.The parameters $(SD1)$,$(SD2)$ and their ratio $(SD12)$,characterizing the Poincar\'{e} plot reveal a significant reduction of their values for diabetic and hypertensive subjects compared to the corresponding results of control one.The slope and the curvature of the plot of these parameters with lagged number exhibit similar trend.In particular,the curvature of $(SD12)$ for the control group differs widely from that of other groups.The principal component analysis is used for analysing multi-dimensional data set resulting from the Poincar\'{e} plot for all subjects.The correlation matrix points out significant correlation between slope and curvature.The analysis demonstrates that three groups are well separated in the domain of two significant principal components.The auto-correlation of HR fluctuation exhibits highly correlated pattern for subjects with health disorder compared to that of control subject.