HRV Dynamical Analysis of Cardiac Autonomic Activity of Healthy Subjects with Age

Abstract

Human heart rate is not a constant phenomenon; it varies over time and is known as Heart rate variability (HRV). HRV is a predictor of cardiac health because several physiological activities regulate the heart rhythm. Electrocardiogram (ECG) is a non-invasive biomarker tool used to diagnose various cardiac problems by extracting hidden patterns. Cardiac health declines with age and the interbeat interval (RR) gives high-temporal resolution to assess Autonomic nervous system function in healthy patients (ANS). This study utilizes the ECG data of healthy neonates, infants, children, young adults, and middle-aged adults. The HRV indices, including the Time domain (SDNN, SDNNI, DC, AC, HRVti, TINN, Stress index), Frequency domain (VLF, LF, HF, Total power), and Nonlinear analysis (Poincare plot, Approximate entropy, Sample Entropy, Detrended fluctuation analysis, and Recurrence plot), are used to extract the linear and nonlinear physiology of the heart. The Kruskal-Wallis test is utilized to examine the correlations between these groups. The study demonstrates that the activity of the parasympathetic nervous system increases from neonates to children and then tends to diminish after 12 years. The activity of the Sympathetic nervous system tends to diminish in neonates and rise in adults. The autonomic nervous system imbalance in neonates tends to balance until age 12 and then grow. This study demonstrates how normal heart physiology's complexity, correlation, and temporal dimension vary with age.