Heart Rate Variability Analysis with the R package RHRV


Book Description

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


Book Description

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


Book Description

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.




New Knowledge in Information Systems and Technologies


Book Description

This book includes a selection of articles from The 2019 World Conference on Information Systems and Technologies (WorldCIST’19), held from April 16 to 19, at La Toja, Spain. WorldCIST is a global forum for researchers and practitioners to present and discuss recent results and innovations, current trends, professional experiences and challenges in modern information systems and technologies research, together with their technological development and applications. The book covers a number of topics, including A) Information and Knowledge Management; B) Organizational Models and Information Systems; C) Software and Systems Modeling; D) Software Systems, Architectures, Applications and Tools; E) Multimedia Systems and Applications; F) Computer Networks, Mobility and Pervasive Systems; G) Intelligent and Decision Support Systems; H) Big Data Analytics and Applications; I) Human–Computer Interaction; J) Ethics, Computers & Security; K) Health Informatics; L) Information Technologies in Education; M) Information Technologies in Radiocommunications; and N) Technologies for Biomedical Applications.




Computational Science – ICCS 2020


Book Description

The seven-volume set LNCS 12137, 12138, 12139, 12140, 12141, 12142, and 12143 constitutes the proceedings of the 20th International Conference on Computational Science, ICCS 2020, held in Amsterdam, The Netherlands, in June 2020.* The total of 101 papers and 248 workshop papers presented in this book set were carefully reviewed and selected from 719 submissions (230 submissions to the main track and 489 submissions to the workshops). The papers were organized in topical sections named: Part I: ICCS Main Track Part II: ICCS Main Track Part III: Advances in High-Performance Computational Earth Sciences: Applications and Frameworks; Agent-Based Simulations, Adaptive Algorithms and Solvers; Applications of Computational Methods in Artificial Intelligence and Machine Learning; Biomedical and Bioinformatics Challenges for Computer Science Part IV: Classifier Learning from Difficult Data; Complex Social Systems through the Lens of Computational Science; Computational Health; Computational Methods for Emerging Problems in (Dis-)Information Analysis Part V: Computational Optimization, Modelling and Simulation; Computational Science in IoT and Smart Systems; Computer Graphics, Image Processing and Artificial Intelligence Part VI: Data Driven Computational Sciences; Machine Learning and Data Assimilation for Dynamical Systems; Meshfree Methods in Computational Sciences; Multiscale Modelling and Simulation; Quantum Computing Workshop Part VII: Simulations of Flow and Transport: Modeling, Algorithms and Computation; Smart Systems: Bringing Together Computer Vision, Sensor Networks and Machine Learning; Software Engineering for Computational Science; Solving Problems with Uncertainties; Teaching Computational Science; UNcErtainty QUantIficatiOn for ComputationAl modeLs *The conference was canceled due to the COVID-19 pandemic.




Organizational Neuroscience


Book Description

This volume aims to introduce organizational researchers and practitioners to the role of neuroscience in building theory, research methodologies and practical applications. The volume introduces the field of organizational neuroscience and explores its influence on topics such as leadership, ethics and moral reasoning.




Applying Bio-Measurements Methodologies in Science Education Research


Book Description

This book illustrates the problems of using eye tracking technology and other bio-measurements in science education research. It examines the application of bio-measurements in researching cognitive processes, motivation for learning science concepts, and solving science problems. Most chapters of this book use the eye-tracking method, which enables following the focus of the students’ attention and drawing conclusions about the strategies they used to solve the problem. This book consists of a total of fifteen chapters. Authors from eight countries emphasise the same trends despite their cultural and educational differences. The book begins with general chapters describing cognitive processes and how these processes are measured using eye-tracking methods and other psychophysiology parameters and motivation. Finally, the book concludes the chapters presenting studies in specific scientific fields from chemistry, biology, physics and geology.




Sleep and Combat-Related Post Traumatic Stress Disorder


Book Description

There are few clinical problems in the sleep medicine field that are more challenging than the sleep difficulties experienced by individuals suffering from post-traumatic stress disorder (PTSD). This book offers a unique, complete resource addressing all the basic concepts and clinical applications in sleep medicine in settings where combat-related PTSD is commonplace. Authored by leading international experts in the field of sleep/military medicine, Sleep and Combat-Related Post Traumatic Stress Disorder is organized in six sections and provides a broad perspective of the field, from the established theories to the most recent developments in research, including the latest neuroscientific perspectives surrounding sleep and PTSD. The result is a full assessment of sleep in relation to combat-related PTSD and a gold standard volume that is the first of its kind. This comprehensive title will be of great interest to a wide range of clinicians -- from academics and clinicians working within or in partnership with the military health care system to veteran hospital physicians and all health personnel who work with war veterans.




Mathematical Foundations of Neuroscience


Book Description

This book applies methods from nonlinear dynamics to problems in neuroscience. It uses modern mathematical approaches to understand patterns of neuronal activity seen in experiments and models of neuronal behavior. The intended audience is researchers interested in applying mathematics to important problems in neuroscience, and neuroscientists who would like to understand how to create models, as well as the mathematical and computational methods for analyzing them. The authors take a very broad approach and use many different methods to solve and understand complex models of neurons and circuits. They explain and combine numerical, analytical, dynamical systems and perturbation methods to produce a modern approach to the types of model equations that arise in neuroscience. There are extensive chapters on the role of noise, multiple time scales and spatial interactions in generating complex activity patterns found in experiments. The early chapters require little more than basic calculus and some elementary differential equations and can form the core of a computational neuroscience course. Later chapters can be used as a basis for a graduate class and as a source for current research in mathematical neuroscience. The book contains a large number of illustrations, chapter summaries and hundreds of exercises which are motivated by issues that arise in biology, and involve both computation and analysis. Bard Ermentrout is Professor of Computational Biology and Professor of Mathematics at the University of Pittsburgh. David Terman is Professor of Mathematics at the Ohio State University.