Non-Linear Dynamics of Cardiovascular Variability Signals

• DOI: 10.1055/s-0038-1634981
• Publication Date: 2018-03-20T03:50:48Z
• Authors: S. Cerutti; S. Guzzetti; R. Parola; M.G. Signorini
• Keywords: Dynamics

Long-term regulation of beat-to-beat variability involves several different kinds controls. A linear approach performed by parametric models enhances the short-term autonomic nervous system. Some non-linear long-term can be assessed chaotic deterministic applied to discrete RR-interval series, extracted from ECG. For systems, trajectories state vector describe a strange attractor characterized fractal dimension D. Signals are supposed generated and finite dimensional but dynamic system with in multi-dimensional space-state. We estimated through Grassberger Procaccia algorithm Self-Similarity approaches 24-h heart-rate (HRV) signal physiological pathological conditions such as severe heat failure, or after heart transplantation. State-space representations Return Maps also obtained. Differences between cases have been generally decrease complexity is correlated conditions.