Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Atrial Fibrillation-Basic Research and Clinical Applications is designed to provide a comprehensive review and to introduce outstanding and novel researches. This book contains 22 polished chapters and consists of five sections: 1. Basic mechanisms of initiation and maintenance of atrial fibrillation and its pathophysiology, 2. Mapping of atrial fibrillation and novel methods of signal detection. 3. Clinical prognostic predictors of atrial fibrillation and remodeling, 4. Systemic reviews of catheter-based/surgical treatment and novel targets for treatment of atrial fibrillation and 5. Atrial fibrillation in specific conditions and its complications. Each chapter updates the knowledge of atrial fibrillation, providing state-of-the art for not only scientists and clinicians who are interested in electrophysiology, but also general cardiologists.

Atrial fibrillation. --- Auricular fibrillation --- Atrial arrhythmias --- Cardiovascular medicine

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This work addresses major challenges of heart model personalization. Analysis techniques for clinical intracardiac electrograms determine wave direction and conduction velocity from single beats. Electrophysiological measurements are simulated to validate the models. Uncertainties in tissue conductivities impact on simulated ECGs. A minimal model of cardiac myocytes is adapted to the atria. This makes personalized cardiac models a promising technique to improve treatment of atrial arrhythmias.

Atrial fibrillation --- Intracardiac electrograms --- Model personalization --- Cardiac modelling --- Electroyphsiology

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

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.

atrial fibrillation --- P-wave --- Vorhof --- electrophysiology --- Computermodell --- Elektrophysiologie --- Vorhofflimmerncomputational modeling --- atria --- P-Welle

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This work provides methods to measure and analyze features of atrial electrograms - especially complex fractionated atrial electrograms (CFAEs) - mathematically. Automated classification of CFAEs into clinical meaningful classes is applied and the newly gained electrogram information is visualized on patient specific 3D models of the atria. Clinical applications of the presented methods showed that quantitative measures of CFAEs reveal beneficial information about the underlying arrhythmia.

Classification --- Catheter Ablation --- Complex Fractionated Atrial Electrograms --- Atrial Fibrillation --- Signal Processing

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

The atrial substrate undergoes electrical and structural remodeling during atrial fibrillation. Detailed multiscale models were used to study the effect of structural remodeling induced at the cellular and tissue levels. Simulated electrograms were used to train a machine-learning algorithm to characterize the substrate. Also, wave propagation direction was tracked from unannotated electrograms. In conclusion, in silico experiments provide insight into electrograms' information of the substrate.

Vorhofflimmern --- Fibrose --- maschinelles Lernen --- Bidomain --- Modellierung des Herzens --- atrial fibrillation --- fibrosis --- machine learning --- bidomain --- cardiac modeling