Heart Rate Variability Analysis With The R Package Rhrv
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Heart Rate Variability Analysis with the R package RHRV
Author: Constantino Antonio García Martínez
language: en
Publisher: Springer Nature
Release Date: 2024-09-26
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.
Heart Rate Variability Analysis with the R package RHRV
Author: Constantino Antonio García Martínez
language: en
Publisher: Springer
Release Date: 2017-09-18
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.
Complex Systems and Computational Biology Approaches to Acute Inflammation
Author: Yoram Vodovotz
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-08-15
The difficulty in achieving effective translation of basic mechanistic biomedical knowledge into effective therapeutics, is the greatest challenge in biomedical research. Nowhere is this more apparent than in the reductionist approaches to understanding and manipulating the acute inflammatory response in the settings of sepsis, trauma/hemorrhage, wound healing, and related processes. This book discusses complex systems and computational biology methods and approaches that have advanced sufficiently to allow for knowledge generation, knowledge integration, and clinical translation in the settings of complex diseases related to the inflammatory response. Well-regulated, self-resolving inflammation is necessary for the appropriate communication and resolution of infection and trauma, and for maintenance of proper physiology and homeostasis. In contrast, self-sustaining inflammation drives the pathobiology of the aforementioned diseases. It is now increasingly recognized that controlling and reprogramming inflammation in order to reap the benefits of this evolutionarily-conserved process is preferred to simply abolishing indiscriminately.