Engineering Approaches To Study Cardiovascular Physiology Modeling Estimation And Signal Processing
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Engineering Approaches to Study Cardiovascular Physiology: Modeling, Estimation, and Signal Processing
With cardiovascular diseases being one of the main causes of death in the world, quantitative modeling, assessment and monitoring of the cardiovascular control system plays a critical role in bringing important breakthroughs to cardiovascular care. Quantification of cardiovascular physiology and its control dynamics from physiological recordings and by use of mathematical models and algorithms has been proved to be of important value in understanding the causes of cardiovascular diseases and assisting the prognostic or diagnostic process. Nowadays, development of new recording technologies (e.g., electrophysiology, imaging, ultrasound, etc) has enabled us to improve and expand acquisition of a wide spectrum of physiological measures related to cardiovascular control. An emerging challenge is to process and interpret such increasing amount of information by using state-of-the-art approaches in systems modeling, estimation and control, and signal processing, which would lead to further insightful scientific findings. In particular, multi-disciplinary engineering-empowered approaches of studying cardiovascular systems would greatly deepen our understanding of cardiovascular functions (e.g., heart rate variability, baroreflex sensitivity) and autonomic control, as it would also improve the knowledge about heart pathology, cardiovascular rehabilitation and therapy. Meanwhile, developing cardiovascular biomedical devices or heart-machine interface for either clinical monitoring or rehabilitation purpose is of greater and greater interest for both scientific advancement and potential medical benefits. This Research Topic will bring together established experts whose areas of research cover a wide range of studies and applications. Contributions include but are not limited to state-of-the-art modeling methodologies, algorithmic development in signal processing and estimation, as well as applications in cardiovascular rehabilitation, and clinical monitoring. The Research Topic will consider both invited reviews and original research.
Cyber-Physical-Human Systems
Author: Anuradha M. Annaswamy
language: en
Publisher: John Wiley & Sons
Release Date: 2023-06-27
Cyber–Physical–Human Systems A comprehensive edited volume exploring the latest in the interactions between cyber–physical systems and humans In Cyber–Physical–Human Systems: Fundamentals and Applications, a team of distinguished researchers delivers a robust and up-to-date volume of contributions from leading researchers on Cyber–Physical–Human Systems, an emerging class of systems with increased interactions between cyber–physical, and human systems communicating with each other at various levels across space and time, so as to achieve desired performance related to human welfare, efficiency, and sustainability. The editors have focused on papers that address the power of emerging CPHS disciplines, all of which feature humans as an active component during cyber and physical interactions. Articles that span fundamental concepts and methods to various applications in engineering sectors of transportation, robotics, and healthcare and general socio-technical systems such as smart cities are featured. Together, these articles address challenges and opportunities that arise due to the emerging interactions between cyber–physical systems and humans, allowing readers to appreciate the intersection of cyber–physical system research and human behavior in large-scale systems. In the book, readers will also find: A thorough introduction to the fundamentals of cyber–physical–human systems In-depth discussions of cyber–physical–human systems with applications in transportation, robotics, and healthcare A comprehensive treatment of socio-technical systems, including social networks and smart cities Perfect for cyber–physical systems researchers, academics, and graduate students, Cyber–Physical–Human Systems: Fundamentals and Applications will also earn a place in the libraries of research and development professionals working in industry and government agencies.
Pervasive Cardiovascular and Respiratory Monitoring Devices
Pervasive Cardiac and Respiratory Monitoring Devices: Model-Based Design is the first book to combine biomedical instrumentation and model-based design. As the scope is limited to cardiac and respiratory devices only, this book offers more depth of information on these devices; focusing in on signals used for home monitoring and offering additional analysis of these devices. The author offers an insight into new industry and research trends, including advances in contactless monitoring of breathing and heart rate. Each chapter presents a section on current trends. As instrumentation as a field is becoming increasingly smart, basic signal processing is also discussed. Real case-studies for each modelling approach are used, primarily covering blood pressure, ECG and radar-based devices. This title is ideal for teaching and supporting learning as it is written in an accessible style and a solutions manual for the problem sets is provided. It will be useful to 4th year undergraduate students, graduate/masters/PhD students, early career researchers and professionals working on an interdisciplinary project; as it introduces the field and provides real world applications. For engineers this book solves the problem of how to assess and calibrate a medical device to ensure the data collected is trustworthy. For students, this book allows for trying concepts and circuits via simulations and learning modeling techniques. Students will learn concepts from this book and be ready to design bioinstrumentations devices based on specifications/requirements. - Focuses on model-based design using Simscape/MATLAB; learn how to design a system and how to evaluate how different choices affect the output of the system - Covers pervasive monitoring: shows how to design optimal solutions for pervasive and personalized healthcare monitoring - Explores uncertainty and sensitivity analysis; understand your model better