Complexity and Nonlinearity in Cardiovascular Signals

Part I: Introduction.- 1. Introducing Complex Cardiovascular Physiology.- Part II: Methods.- 2. Symbolic Dynamics, Poincaré Plot Analysis and Compression Entropy Estimate Complexity in Biological Time Series.- 3. Information Decomposition: A tool to Dissect Cardiovascular and Cardiorespiratory Complexity.- 4. Multiscale Entropy: Recent Advances.- 5. Introduction to Complex Systems Analysis with Wavelets.- 6. Intermittency-Driven Complexity in Signal Processing.- 7. Self-Similarity and Detrended Fluctuation Analysis of Cardiovascular Signals.- 8. Time-varying Cardiovascular Complexity with focus on Entropy and Lyapunov Exponents.- 9. Time-frequency analysis of cardiovascular signals and their dynamic interactions.- Part III: Applications.- 10. Measurements of Cardiovascular Signal Complexity for Advanced Clinical Applications.- 11. Applications of Complexity Analysis in Clinical Heart Failure.- 12. Heart Rate Complexity Associated with Diabetic Cardiac Neuropathy.- 13. Applications of Heartbeat Complexity Analysis to Depression and Bipolar Disorder.- 14. Cardiac Autonomic changes in Epilepsy.- 15. Applications of Nonlinear Methods to Atrial Fibrillation.- 16. Complex and Nonlinear Analysis of Heart Rate Variability in the Assessment of Fetal and Neonatal Wellbeing .- 17. ARFIMA-GARCH Modelling of HRV: Clinical Application in Acute Brain Injury.- 18. Age and Gender Dependency of Complexity Measures of Short-term Heart Rate Time Series.- 19. Complexity and Nonlinearities in Cardiorespiratory Signals in Sleep and Sleep Apnea.

Riccardo Barbieri is a Professor in the Department of Electronics, Informatics and Bioengineering at the Politecnico di Milano, in Milan, Italy.
Enzo P. Scilingo and Gaetano Valenza are both Professors at the Department of Information Engineering & Bioengineering and Robotics Research Center "E. Piaggio", at University of Pisa School of Engineering, in Pisa, Italy.