Felix Plappert defends his thesis: 
Computational Modeling and Analysis of Electrophysiology and Hemodynamics During Atrial Fibrillation.

Thesis in LUCRIS (external).

Atrial fibrillation (AF) is the most common arrhythmia globally and is characterized by uncoordinated atrial activation and ineffective atrial contraction. Atrial fibrillation is associated with an impaired quality of life and an increased risk of stroke, heart failure, and death. Changes in the autonomic nervous system (ANS) control of cardiac function are a known pathophysiological mechanism in AF, but methods for estimating autonomic activity during AF are lacking. Moreover, although AF is primarily an electrophysiological disease, its detrimental effects are mainly due to its hemodynamic consequences and are challenging to predict. Computational modeling offers a mechanistic framework that holds the potential to address both of these issues.