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Body Surface Potential Mapping

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Noninvasive Personalization of a Cardiac Electrophysiology Model From Body Surface Potential Mapping.

IEEE transactions on bio-medical engineering
GOAL: We use noninvasive data (body surface potential mapping, BSPM) to personalize the main parameters of a cardiac electrophysiological (EP) model for predicting the response to different pacing conditions.

Impact of catheter ablation with remote magnetic navigation on procedural outcomes in patients with persistent and long-standing persistent atrial fibrillation.

Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing
BACKGROUND: The objectives of this study were to assess the procedural outcomes of persistent and long-standing persistent atrial fibrillation (PsAF and L-PsAF) ablation guided by remote magnetic navigation (RMN), and to detect factors predicting acu...

Deep learning formulation of electrocardiographic imaging integrating image and signal information with data-driven regularization.

Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
AIMS: Electrocardiographic imaging (ECGI) is a promising tool to map the electrical activity of the heart non-invasively using body surface potentials (BSP). However, it is still challenging due to the mathematically ill-posed nature of the inverse p...

Deep learning based estimation of heart surface potentials.

Artificial intelligence in medicine
Electrocardiographic imaging (ECGI) aims to noninvasively estimate heart surface potentials starting from body surface potentials. This is classically based on geometric information on the torso and the heart from imaging, which complicates clinical ...

Research on noninvasive electrophysiologic imaging based on cardiac electrophysiology simulation and deep learning methods for the inverse problem.

BMC cardiovascular disorders
BACKGROUND: The risk stratification and prognosis of cardiac arrhythmia depend on the individual condition of patients, while invasive diagnostic methods may be risky to patient health, and current non-invasive diagnostic methods are applicable to fe...