Quantifying Chaotic Behavior in Noisy Dynamical Systems: A Study on Heartbeat Dynamics.

Area of Science:

• Cardiovascular physiology
• Dynamical systems theory
• Nonlinear dynamics

Background:

• Heart rate variability (HRV) reflects cardiovascular system dynamics.
• The cardiovascular system exhibits nonlinear and complex dynamics.
• Previous assumptions of chaotic behavior were challenged by physiological noise.

Purpose of the Study:

• Introduce a novel framework to quantify regular or chaotic dynamics in noisy systems.
• Characterize cardiovascular system dynamics, considering noise inputs.
• Differentiate between regular and chaotic patterns in physiological data.

Main Methods:

• Estimate asymptotic growth rate of noisy mean square displacement in 2D phase space.
• Model cardiac oscillations using an Inverse-Gaussian function.
• Validate the method with synthetic data and apply to real HRV series from healthy subjects and patients.

Main Results:

• Synthetic data confirmed the method's accuracy.
• Cardiac pathology did not affect chaotic behavior.
• Atrial fibrillation demonstrated increased sensitivity to input changes.

Conclusions:

• The framework quantitatively characterizes physiological dynamics as regular or chaotic.
• HRV series originates from a non-chaotic system driven by dynamical noise.
• The findings offer new insights into cardiovascular system regulation.