Heart rate analysis in normal subjects of various age groups

Area of Science:

• Cardiology
• Biomedical Engineering
• Physiology

Background:

• Heart rate variability (HRV) is a noninvasive tool for assessing autonomic nervous system (ANS) activity.
• HRV analysis incorporates both linear and nonlinear parameters to capture sympathetic and vagal influences.
• Aging is associated with decreased heart rate variability, indicating altered ANS function.

Purpose of the Study:

• To present the normal ranges of linear and nonlinear HRV parameters across four age groups.
• To evaluate the accuracy of HRV parameters in reflecting age-related changes.
• To confirm the nonlinearity of HRV signals using surrogate data analysis.

Main Methods:

• Analysis of heart rate using time domain, frequency domain, and nonlinear parameters.
• Inclusion of nonlinear indices: Poincare plot geometry (SD1, SD2), Approximate Entropy (ApEn), Largest Lyapunov Exponent (LLE), and Detrended Fluctuation Analysis (DFA).
• Surrogate data analysis to test for signal nonlinearity.

Main Results:

• Normal ranges for linear and nonlinear HRV parameters were established for different age groups with >89% accuracy.
• Significant differences were observed in ApEn, LLE, SD1/SD2, and DFA between actual HRV data and surrogate data, confirming signal nonlinearity.
• HRV parameters showed distinct ranges for various cardiac abnormalities.

Conclusions:

• Heart rate variability (HRV) serves as a reliable indicator of cardiac state.
• Aging leads to decreased randomness (increased predictability) in HRV, as evidenced by nonlinear parameter changes.
• Established nonlinear parameter ranges for different age groups provide valuable insights into age-related physiological changes.