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Complexity and Nonlinearity in Cardiovascular Signals

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Cover of 'Complexity and Nonlinearity in Cardiovascular Signals'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction to Complex Cardiovascular Physiology
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    Chapter 2 Symbolic Dynamics, Poincaré Plot Analysis and Compression Entropy Estimate Complexity in Biological Time Series
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    Chapter 3 Information Decomposition: A Tool to Dissect Cardiovascular and Cardiorespiratory Complexity
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    Chapter 4 Multiscale Entropy: Recent Advances
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    Chapter 5 Introduction to Complex Systems Analysis with Wavelets
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    Chapter 6 Intermittency-Driven Complexity in Signal Processing
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    Chapter 7 Self-Similarity and Detrended Fluctuation Analysis of Cardiovascular Signals
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    Chapter 8 Time-Varying Cardiovascular Complexity with Focus on Entropy and Lyapunov Exponents
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    Chapter 9 Time-Frequency Analysis of Cardiovascular Signals and Their Dynamic Interactions
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    Chapter 10 Measurements of Cardiovascular Signal Complexity for Advanced Clinical Applications
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    Chapter 11 Applications of Complexity Analysis in Clinical Heart Failure
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    Chapter 12 Heart Rate Complexity Associated with Diabetic Cardiac Neuropathy
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    Chapter 13 Applications of Heartbeat Complexity Analysis to Depression and Bipolar Disorder
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    Chapter 14 Cardiac Autonomic Changes in Epilepsy
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    Chapter 15 Applications of Nonlinear Methods to Atrial Fibrillation
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    Chapter 16 Complex and Nonlinear Analysis of Heart Rate Variability in the Assessment of Fetal and Neonatal Wellbeing
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    Chapter 17 ARFIMA-GARCH Modeling of HRV: Clinical Application in Acute Brain Injury
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    Chapter 18 Age and Gender Dependency of Complexity Measures of Short-Term Heart Rate Time Series
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    Chapter 19 Complexity and Nonlinearities in Cardiorespiratory Signals in Sleep and Sleep Apnea
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Title
Complexity and Nonlinearity in Cardiovascular Signals
Published by
Springer International Publishing, January 2017
DOI 10.1007/978-3-319-58709-7
ISBNs
978-3-31-958708-0, 978-3-31-958709-7
Editors

Dr. Riccardo Barbieri, Dr. Enzo Pasquale Scilingo, Dr. Gaetano Valenza

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 65 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 15 23%
Student > Ph. D. Student 13 20%
Student > Doctoral Student 6 9%
Other 6 9%
Student > Bachelor 5 8%
Other 13 20%
Unknown 7 11%
Readers by discipline Count As %
Engineering 21 32%
Medicine and Dentistry 8 12%
Neuroscience 5 8%
Psychology 4 6%
Mathematics 3 5%
Other 12 18%
Unknown 12 18%