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Atrial Fibrillation from an Engineering Perspective provides an up-to-date overview of techniques developed for acquisition, modeling, and analysis of noninvasive, bioelectrical signals reflecting this common arrhythmia. Special emphasis is put on emerging technologies for monitoring of atrial fibrillation in connection with ischemic stroke, interventional ablation procedures, and pharmacological treatment, applications which all depend on the availability of techniques for detecting and characterizing episodes of paroxysmal atrial fibrillation. Detectors exploring both rhythm and morphology are described, as well as detectors confined to rhythm and better suited for low power implementation. A wide variety of approaches to modeling and characterization of atrial activity are described, emanating from a statistical and deterministic starting points. This book is suitable for graduate students, researchers, and engineers who want a comprehensive treatise of atrial fibrillation from an engineering perspective. It may be used for self-study, as a supplement to courses in signal processing, or as a modern monograph by researchers in the field of atrial fibrillation.
Since the introduction of balloon angioplasty for the relief of coronary artery stenoses and of anginal symptoms in patients with coronary artery disease by Andreas Griintzig in 1977, the field of interventional technology and treatment strategies has grown enormously. For the reduction of hemodynamically significant coronary artery stenoses balloon angioplasty is the standard and reference method with a high primary success and low complication rate. Because of the relatively high recurrence rates of 30-40% of balloon angioplasty a whole family of different angioplasty techniques has been developed since then. Among those are atherectomy devices, laser angioplasty, radiofrequency angioplast...
This book illustrates applications of mathematics to various processes (physiological or artificial) involving flowing blood, including hemorheology, microcirculation, coagulation, kidney filtration and dialysis, offering a historical overview of each topic. Mathematical models are used to simulate processes normally occurring in flowing blood and to predict the effects of dysfunctions (e.g. bleeding disorders, renal failure), as well as the effects of therapies with an eye to improving treatments. Most of the models have a completely new approach that makes patient-specific simulations possible. The book is mainly intended for mathematicians interested in medical applications, but it is also useful for clinicians such as hematologists, nephrologists, cardio-surgeons, and bioengineers. Some parts require no specific knowledge of mathematics. The book is a valuable addition to mathematics, medical, biology, and bioengineering libraries.
Half of the patients suffering from atrial fibrillation (AF) cannot be treated adequately, today. This book presents multi-scale computational methods to advance our understanding of patho-mechanisms, to improve the diagnosis of patients harboring an arrhythmogenic substrate, and to tailor therapy. The modeling pipeline ranges from ion channels on the subcellular level up to the ECG on the body surface. The tailored therapeutic approaches carry the potential to reduce the burden of AF.
Catheter ablation has become a mainstay in the therapy of cardiac arrhythmias. The development of electroanatomical mapping technologies (such as CARTO) has facilitated more complex ablation procedures. This brand new book encompasses cardiac arrhythmias and practical tips for users of electroanatomical mapping, providing a color atlas of different arrhythmias, presented as cases, that have been carefully mapped and correlated with clinical and electrogram data. Including maps from all the major mapping systems such as CARTO, NAVX, ESI, RPM as well as activation maps and voltage maps, this book is an ideal reference book and learning tool for electrophysiologists, electrophysiology fellows and electrophysiology laboratory staff.
Addresses the mathematical and numerical modelling of the human cardiovascular system, from patient data to clinical applications.
This special issue of the Handbook of Experimental Pharmacology on Heart Failure covers the entire spectrum of the field, from the current understanding and definitions of heart failure, to epidemiology and the importance of co-morbidities, clinical trial design and biomarkers, as well as imaging technologies. The main focus of this book is to review current and emerging heart failure therapies and potential targets for treatment.
This book targets three fields of computational multi-scale cardiac modeling. First, advanced models of the cellular atrial electrophysiology and fiber orientation are introduced. Second, novel methods to create patient-specific models of the atria are described. Third, applications of personalized models in basic research and clinical practice are presented. The results mark an important step towards the patient-specific model-based atrial fibrillation diagnosis, understanding and treatment.
This book addresses the tough clinical issues faced by electrophysiologists and cardiologists who treat patients with Cardiac Implantable Electrical Devices (CIEDs) in real-world practice. With contributions from widely recognized international leaders in the field, this 10-chapter resource covers a variety of controversies with CIEDs, from discerning what device is appropriate to use for heart failure to ethical issues in their use at the end of a patient’s life. To supplement these discussions, chapters review opposing positions on both sides of a controversy and present clinical material to illustrate the different perspectives. Clinical Controversies in Device Therapy for Cardiac Arrhythmias is an essential resource not only for physicians, residents, and fellows in cardiac electrophysiology and cardiology but also for associated professionals including nurses and technicians who work with CIEDs.
An early detection and diagnosis of atrial fibrillation sets the course for timely intervention to prevent potentially occurring comorbidities. Electrocardiogram data resulting from electrophysiological cohort modeling and simulation can be a valuable data resource for improving automated atrial fibrillation risk stratification with machine learning techniques and thus, reduces the risk of stroke in affected patients.