Atrial fibrillation (AF) is the most common sustained arrhythmia. It often leads to severe complications such as heart failure and stroke. Rotors are mechanisms characterized by a rotational activity that controls the surrounding activation and that can perpetuate AF. Nowadays to know how to best treat these pathologies, it is needed to discriminate with high precision which type of AF the subject is affected. To do this, invasive methods of signal acquisition are required, such as intracardiac catheters. It would be best to try to identify with more precision the type of AF, the location of the AF source, using non-invasive methods, such as 12-lead-ECG and body surface potential maps (BSPM), in order to avoid the use of invasive methods, or in any case to decrease the procedure time of the ablation therapy.
The aim of this work is to identify the patterns characterizing the rotors through the use of 12-lead-ECG and BSPM signals. To do this, it will be necessary to produce rotor simulations on atrial models and solve the forward problem in order to obtain the respective BSPMs. These maps will be used to extract the ECG and BSP signals. These signals will be analyzed with biosignal processing methods to extract relevant features, used to identify the type of mechanism.
The work to be done goes through both the fields of cardiac modeling and biosignal processing.
- Prior knowledge in MATLAB is essential
- Programming skills in Python/C++ are desirable
- English is required