Asymmetric multiscale multifractal analysis (AMMA) of heart rate variability

Dorota Kokosińska1, Jan Jacek Żebrowski1, Teodor Buchner1

  • 1Faculty of Physics, Warsaw University of Technology, Complex Systems, Warsaw 00-662, Poland.

Insights

New asymmetric multiscale multifractal analysis (AMMA) reveals significant differences in heart rate variability (HRV) patterns between healthy individuals and various cardiac conditions. Heart rate decelerations are key to understanding multifractal properties and improving medical screening.

Area of Science:

  • Cardiology
  • Physiology
  • Complex Systems Analysis

Background:

  • Heart rate variability (HRV) reflects autonomic nervous system modulation of cardiac activity.
  • Traditional HRV analysis often overlooks asymmetric patterns in heart rate fluctuations.
  • Existing multiscale multifractal analysis (MMA) provides insights but can be enhanced by asymmetry.

Purpose of the Study:

  • Introduce and evaluate the asymmetric multiscale multifractal analysis (AMMA) for HRV.
  • Investigate HRV asymmetry in healthy individuals and patients with cardiovascular diseases.
  • Determine if AMMA can differentiate between various cardiac conditions based on HRV patterns.

Main Methods:

  • Developed and applied the asymmetric multiscale multifractal analysis (AMMA) method.
  • Analyzed HRV data from six groups: healthy controls, aortic valve stenosis, hypertrophic cardiomyopathy, atrial fibrillation, coronary artery disease (CAD), and congestive heart failure.
  • Compared Hurst surfaces for heart rate accelerations and decelerations using AMMA.

Main Results:

  • Significant differences were observed in AMMA-derived Hurst surfaces between healthy individuals and cardiac patient groups.
  • These differences were particularly evident for large fluctuations (multifractal parameter q > 0).
  • Heart rate decelerations (lengthening RR intervals) significantly influence the overall Hurst surface shape and multifractal properties, showing similarity across all groups.

Conclusions:

  • AMMA provides a novel approach to HRV analysis, highlighting distinct patterns in cardiac conditions.
  • Separating analysis of accelerations and decelerations enhances the visibility of differences between groups, especially for CAD, hypertrophic cardiomyopathy, and aortic valve stenosis.
  • AMMA holds potential for improved medical screening and a new paradigm in HRV-based diagnostics.