Changes in multifractality with aging and heart failure in heartbeat interval time series

Area of Science:

• Cardiology
• Complex Systems Analysis
• Physiological Monitoring

Background:

• Heart rate variability (HRV) reflects autonomic nervous system function.
• Aging and congestive heart failure (CHF) are associated with altered cardiac autonomic control.
• Multifractal analysis offers a sophisticated method to characterize complex time series like HRV.

Purpose of the Study:

• To investigate the impact of aging and CHF on the multifractal properties of diurnal heart interbeat time series.
• To assess the diagnostic potential of multifractal parameters in differentiating between healthy young, healthy elderly, and CHF patients.

Main Methods:

• Collection of diurnal heart interbeat time series from three distinct groups: healthy young adults, healthy elderly adults, and patients with CHF.
• Application of multifractal analysis to quantify the complexity and scaling properties of the time series.
• Analysis of the multifractal spectrum, focusing on the degree of multifractality and its asymmetry.

Main Results:

• Both aging and CHF were associated with a significant loss of multifractality in heart interbeat time series.
• The multifractal spectrum asymmetry parameter showed distinct patterns across the studied groups.
• Joint analysis of multifractality degree and asymmetry successfully differentiated between young and elderly healthy subjects.
• This combined analysis also effectively separated healthy individuals from those with CHF.

Conclusions:

• Multifractal analysis provides valuable insights into the physiological changes in heart rate dynamics associated with aging and CHF.
• The degree of multifractality and spectrum asymmetry are sensitive biomarkers for detecting cardiac autonomic dysfunction.
• This analytical approach holds promise for non-invasive differentiation of cardiac health status.