Nonivasive atrial fibrillation diagnosis, characterization, prediction, and risk stratification from the ECG, including:
- Development of ECG-based automatic AF detection.
- Development of signal processing and mathematical modelling techniques for the characterization of AF episode patterns in paroxysmal AF.
- Identification of ECG-based biomarkers for AF / stroke risk stratification.
- Identification of ECG-based markers associated with the presence of other atrial cardiomyopathies including fibrosis and atrial hypertrophy.
- ECG-based ventricular vulnerability risk markers measurable during AF rhythm
with the ultimate goal of improving risk assessment as well as better understanding arrhythmia progression.
