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Book
Heart Rate Variability Analysis with the R package RHRV
Authors: --- --- --- --- --- et al.
ISBN: 3319653555 3319653547 9783319653549 Year: 2017 Publisher: Cham : Springer International Publishing : Imprint: Springer,

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Abstract

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.

Keywords

Statistics. --- Cardiac imaging. --- Cardiology. --- Biostatistics. --- Biomedical engineering. --- Statistics for Life Sciences, Medicine, Health Sciences. --- Signal, Image and Speech Processing. --- Biomedical Engineering. --- Cardiac Imaging. --- Clinical engineering --- Medical engineering --- Biological statistics --- Biology --- Biometrics (Biology) --- Biostatistics --- Cardiac diagnostic imaging --- Cardiac imaging --- Diagnostic cardiac imaging --- Heart --- Imaging of the heart --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Diseases --- Imaging --- Statistical methods. --- Heart beat. --- Internal medicine --- Cardiac cycle --- Cycle, Cardiac --- Heart cycle --- Heart rate --- Heart conduction system --- Hemodynamics --- Pulse --- Contraction --- Biomedical Engineering and Bioengineering. --- Mathematics --- Econometrics --- Bioengineering --- Biophysics --- Engineering --- Medicine --- Statistics . --- Signal processing. --- Image processing. --- Speech processing systems. --- Biomathematics --- Statistics --- Computational linguistics --- Electronic systems --- Information theory --- Modulation theory --- Oral communication --- Speech --- Telecommunication --- Singing voice synthesizers --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication) --- R (Computer program language). --- GNU-S (Computer program language) --- Domain-specific programming languages


Digital
Heart Rate Variability Analysis with the R package RHRV

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Abstract

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.


Book
Heart Rate Variability Analysis with the R package RHRV
Authors: --- --- --- --- --- et al.
ISBN: 9783031657535 3031657535 Year: 2024 Publisher: Cham : Springer International Publishing : Imprint: Springer,

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Export citation

Choose an application

Bookmark

Abstract

This book introduces readers to the fundamental 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 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. The second edition of the book has been updated to RHRV version 5.0. This version introduces a functionality to perform heart rate variability analysis on entire populations. This functionality automates and streamlines both the calculation of HRV indices in the time, frequency, and nonlinear domains, as well as the subsequent statistical analysis.

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