Atrial tachycardia, such as atrial fibrillation or atrial flutter, is a major burden for both patients and health care systems worldwide. Considering that the prevalence of atrial fibrillation significantly increases with age, the group of patients will further grow due to demographic changes. Although supraventricular tachycardia is not lethal itself, it entails further health hazards such as an increased prevalence for thromboembolic events or heart failure. For these and other reasons, it is essential to effectively and sustainably treat and stop atrial fibrillation. As electrical and biomedical engineers, we focus on designing tools for signal and data analysis that facilitate the extraction and visualization of relevant, but possibly complex multichannel information for physicians.
Besides antiarrhythmic drug therapy, catheter ablation is the most common method in the treatment of atrial fibrillation. During an electrophysiological study, the electrical activity of the atria is mapped in order to characterize the arrhythmia. Standard ablation lesions are then delivered beginning with pulmonary vein isolation. Finally, patient specific lesion sets can be deduced from the acquired electroanatomical maps to complete the procedure. However, there is a lack of profound knowledge and guidelines for ablation strategies beyond pulmonary vein isolation. Despite major efforts in the past decades, success rates remain poor and patients need to be hospitalized for second and third ablation procedures.
Several hypotheses coexist that describe the driving forces of atrial fibrillation ranging from re-entrant circuits and focal sources to endo-epicardial dissociation effects. The exact mechanism yet remains unclear. This work aims at gaining a more detailed comprehension of supraventricular tachycardia, in particular atrial fibrillation. The characterization and classification of activation patterns, electrogram morphology, or atrial substrate are only examples. We also investigate the effect of different catheter and electrode geometries on the mapping result. For these purposes, intracardiac electrograms are analyzed with mathematical tools in alignment with a patient’s heart geometry. Secondly, possible ablation strategies leading to an optimal patient outcome are deduced. The results could be used to further develop clinical tools towards assisting physicians during electrophysiological studies. Besides strong collaborations with leading biomedical engineering companies, we work in close cooperation with electrophysiologists to ensure the clinical applicability and relevance of all research projects.