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Heart rate variability analysis with...

Garcia Martinez, Constantino Antonio.

Heart rate variability analysis with the R package RHRV

Record Type:	Electronic resources : Monograph/item
Title/Author:	Heart rate variability analysis with the R package RHRVby Constantino Antonio Garcia Martinez ... [et al.].
other author:	Garcia Martinez, Constantino Antonio.
Published:	Cham :Springer International Publishing :2017.
Description:	xvi, 157 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Heart beat.
Online resource:	http://dx.doi.org/10.1007/978-3-319-65355-6
ISBN:	9783319653556$q(electronic bk.)

Heart rate variability analysis with the R package RHRV
Heart rate variability analysis with the R package RHRV[electronic resource] /by Constantino Antonio Garcia Martinez ... [et al.]. - Cham :Springer International Publishing :2017. - xvi, 157 p. :ill., digital ;24 cm. - Use R!,2197-5736. - Use R!.

Foreword -- Preface -- 1 Introduction to Heart Rate Variability -- 2 Loading, Plotting and Filtering RR Intervals -- 3 Time Domain Analysis -- 4 Frequency Domain Analysis -- 5 Nonlinear and Fractal Analysis -- 6 Comparing HRV Variability across Different Segments of a Recording -- 7 Putting it All Together, a Practical Example -- A Installing RHRV -- B How do I Get a Series of RR Intervals from a Clinical/Biological Experiment?

This book introduces readers to the basic concepts of Heart Rate Variability (HRV) and its most important analysis algorithms using a hands-on approach based on the open-source RHRV software. HRV refers to the variation over time of the intervals between consecutive heartbeats. Despite its apparent simplicity, HRV is one of the most important markers of the autonomic nervous system activity and it has been recognized as a useful predictor of several pathologies. The book discusses all the basic HRV topics, including the physiological contributions to HRV, clinical applications, HRV data acquisition, HRV data manipulation and HRV analysis using time-domain, frequency-domain, time-frequency, nonlinear and fractal techniques. Detailed examples based on real data sets are provided throughout the book to illustrate the algorithms and discuss the physiological implications of the results. Offering a comprehensive guide to analyzing beat information with RHRV, the book is intended for masters and Ph.D. students in various disciplines such as biomedical engineering, human and veterinary medicine, biology, and pharmacy, as well as researchers conducting heart rate variability analyses on both human and animal data.

ISBN: 9783319653556$q(electronic bk.)

Standard No.: 10.1007/978-3-319-65355-6doiSubjects--Topical Terms:

514083
Heart beat.

LC Class. No.: QP113 / .H437 2017

Dewey Class. No.: 612.171

Heart rate variability analysis with the R package RHRV
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245 0 0 $a Heart rate variability analysis with the R package RHRV $h [electronic resource] / $c by Constantino Antonio Garcia Martinez ... [et al.].
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505 0 $a Foreword -- Preface -- 1 Introduction to Heart Rate Variability -- 2 Loading, Plotting and Filtering RR Intervals -- 3 Time Domain Analysis -- 4 Frequency Domain Analysis -- 5 Nonlinear and Fractal Analysis -- 6 Comparing HRV Variability across Different Segments of a Recording -- 7 Putting it All Together, a Practical Example -- A Installing RHRV -- B How do I Get a Series of RR Intervals from a Clinical/Biological Experiment?
520 $a This book introduces readers to the basic concepts of Heart Rate Variability (HRV) and its most important analysis algorithms using a hands-on approach based on the open-source RHRV software. HRV refers to the variation over time of the intervals between consecutive heartbeats. Despite its apparent simplicity, HRV is one of the most important markers of the autonomic nervous system activity and it has been recognized as a useful predictor of several pathologies. The book discusses all the basic HRV topics, including the physiological contributions to HRV, clinical applications, HRV data acquisition, HRV data manipulation and HRV analysis using time-domain, frequency-domain, time-frequency, nonlinear and fractal techniques. Detailed examples based on real data sets are provided throughout the book to illustrate the algorithms and discuss the physiological implications of the results. Offering a comprehensive guide to analyzing beat information with RHRV, the book is intended for masters and Ph.D. students in various disciplines such as biomedical engineering, human and veterinary medicine, biology, and pharmacy, as well as researchers conducting heart rate variability analyses on both human and animal data.
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