ECG Time Series Variability Analysis : Engineering and Medicine book cover
1st Edition

ECG Time Series Variability Analysis
Engineering and Medicine

ISBN 9780367870157
Published December 10, 2019 by CRC Press
496 Pages

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Book Description

Divided roughly into two sections, this book provides a brief history of the development of ECG along with heart rate variability (HRV) algorithms and the engineering innovations over the last decade in this area. It reviews clinical research, presents an overview of the clinical field, and the importance of heart rate variability in diagnosis. The book then discusses the use of particular ECG and HRV algorithms in the context of clinical applications.

Table of Contents




1. Introduction to ECG Time Series Variability Analysis: A Simple Overview

Herbert F. Jelinek, David J. Cornforth, and Ahsan H. Khandoker

2. Historical Development of HRV Analysis

Andreas Voss

3. A Descriptive Approach to Signal Processing

Dragana Bajić, Goran Dimić, Tatjana Lončar-Turukalo, Branislav Milovanović, and Nina Japundžić-Žigon

4. Linear and Nonlinear Parametric Models in Heart Rate Variability Analysis

Gaetano Valenza, Luca Citi, and Riccardo Barbieri

5. Assessing Complexity and Causality in Heart Period Variability through a Model-Free Data-Driven Multivariate Approach

Alberto Porta, Luca Faes, Giandomenico Nollo, Anielle C. M. Takahashi, and Aparecida M. Catai

6. Visualization of Short-Term Heart Period Variability with Network Tools as a Method for Quantifying Autonomic Drive

Danuta Makowiec, Beata Graff, Agnieszka Kaczkowska, Grzegorz Graff, Dorota Wejer, Joanna Wdowczyk, Marta Żarczyńska-Buchowiecka, Marcin Gruchała, and Zbigniew R. Struzik

7. Analysis and Preprocessing of HRV—Kubios HRV Software

Mika P. Tarvainen, Jukka A. Lipponen, and Pekka Kuoppa

8. Multiscale Complexity Measures of Heart Rate Variability—A Window on the Autonomic Nervous System Function

David J. Cornforth and Herbert F. Jelinek

9. BP and HR Interactions: Assessment of Spontaneous Baroreceptor Reflex Sensitivity

Tatjana Lončar-Turukalo, Nina Japundžić-Žigon, Olivera Šarenac, and Dragana Bajić

10. Tone–Entropy Analysis of Heart Rate Variability in Cardiac Autonomic Neuropathy

Chandan Karmakar, Ahsan H. Khandoker, Herbert F. Jelinek, and Marimuthu Palanis

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Associate Professor Herbert Jelinek received the B.Sc. (Hons.) degree in human genetics from the University of New South Wales, Sydney, Australia, followed by a Graduate Diploma in neuroscience from the Australian National University, Canberra, Australia, and his PhD. degree in medicine from the University of Sydney, Australia. He is a honorary Clinical Associate Professor with the Australian School of Advanced Medicine, Macquarie University, Sydney, Australia, and a member of the Centre for Research in Complex Systems, Charles Sturt University, Albury, Australia. Dr Jelinek has been organizing a rural diabetes complications screening research project for over ten years in Australia and has published widely in ECG signal processing and diabetic retinopathy image analysis as well as data mining applications of biomarkers associated with diabetes disease progression. His current research interests include neurogenetics of diabetes and cognitive function. He is a member of the IEEE Biomedical Engineering Society and the Australian Diabetes Association.


"This book presents a comprehensive view of ECG time series variability analysis, covering many relevant aspects from descriptive approaches and modelling to advanced signal processing methods. The different clinical applications of the techniques are covered in detail, with examples including, but not limited to, foetal heart rate variability, heart rate variability in psychiatric disorders, schizophrenia, or chronic kidney disease. Therefore, it is likely to become a well-received book by those who already have an interest in the topic, those who might be interested in the possible usefulness of heart rate variability analysis in different conditions, and those wanting to get started in ECG time series variability analysis."
—Daniel Abasolo, University of Surrey, United Kingdom