Abstract
Physiological rhythms or oscillations are the manifestation of a complex physiological system. The clinical community has long recognized that alterations in physiological rhythms are associated with disease and therefore have clinical value. Oscillations in cardiovascular systems are reflected in electrocardiogram (ECG) time series variability. For example, beat to beat variability in heart rate or heart rate variability (HRV) analysis has experienced a tremendous increase in interest from both the engineering community and medical profession, as well as from the social science, economic, and health sectors. What follows is a brief overview of the chapters included in this book, noting that each chapter was a team effort by the various laboratories around the globe that work in this field. This book is organized to provide a historical overview of the domain by Andreas Voss in Chapter 2 and a basic overview of HRV analysis and review of the basics of biosignal processing by Dragana Bajić and her coauthors in Chapter 3. Chapter 4 is aimed at readers who are new to this field or who need an overview of the basic concepts. From these introductory chapters, the book moves on to provide some groundbreaking computational applications by Gaetano Valenza and colleagues (Chapter 4) as well as the laboratory of Alberto Porta and colleagues in Chapter 5. Danuta Makowiec and coauthors discuss how graph theory may be applied to HRV analysis in Chapter 6. Many of these applications require on-site coding and Mika Tarvainen introduces Kubios in Chapter 7, which is a shareware program available from the World Wide Web that provides the opportunity to investigate biosignals processing and obtain the fundamental time and frequency domain measures as well as some nonlinear attributes of the biosignals. This software includes preprocessing options and time and frequency domain analysis as well as nonlinear HRV analysis options, for those that require a user-friendly application for HRV analysis. The remainder of the book then concentrates on several areas of clinical applications with the aim to introduce the reader to the utility of HRV. In some cases, other biosignal variability analysis methods are discussed, such as blood pressure and electroencephalogram (EEG) analysis, which can be 2coupled to heart rate tachograms. An important aspect of the clinical chapters is the inclusion by the authors of explanations of why they used the algorithms and they also propose more advanced methods that address the research problem better.
Original language | British English |
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Title of host publication | ECG Time Series Variability Analysis |
Subtitle of host publication | Engineering and Medicine |
Pages | 1-12 |
Number of pages | 12 |
ISBN (Electronic) | 9781482243482 |
DOIs | |
State | Published - 1 Jan 2017 |