Heart rate variability--a shape analysis of Lorenz plots

Area of Science:

• Cardiology
• Biomedical Engineering
• Quantitative Physiology

Background:

• Heart rate variability (HRV) analysis is crucial for assessing autonomic nervous system function.
• Traditional HRV methods may lack detailed geometrical insights into cardiac dynamics.
• Lorenz plots offer a visual representation of HRV, but quantitative geometrical analysis remains challenging.

Purpose of the Study:

• To introduce a new quantitative geometrical method for analyzing heart rate variability.
• To apply standard image analysis techniques to Lorenz plots for geometrical characterization.
• To develop a method for describing attractor region contours using mathematical descriptors.

Main Methods:

• Application of standard image analysis techniques to grayscale Lorenz plot images.
• Utilizing a contour following procedure, based on a maze walking algorithm, to determine attractor outlines.
• Describing the contours of attractor regions using Fourier coefficients for compact shapes.

Main Results:

• Successfully applied image analysis to derive geometrical features from Lorenz plots.
• The maze walking algorithm effectively identified attractor region boundaries.
• Fourier coefficients provided a concise mathematical description of attractor contours for simple shapes.

Conclusions:

• The proposed quantitative geometrical method offers a novel approach to HRV analysis.
• Image analysis of Lorenz plots, combined with contour following and Fourier descriptors, enables detailed geometrical characterization.
• This method has the potential to enhance the understanding of cardiac autonomic regulation.