Personalized computational electro-mechanics simulations to optimize cardiac resynchronization therapy

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Background and Objectives: The massive storage of cardiac arrhythmic episodes from Implantable Cardioverter Defibrillators (ICD) and the advent of new artificial intelligence algorithms are opening up new opportunities for electrophysiological knowledge ex ...

In this work, we present a PDE-aware deep learning model for the numerical solution to the inverse problem of electrocardiography. The model both leverages data availability and exploits the knowledge of a physically based mathematical model, expressed by ...

Nanogenerators are a recently emerging technology which is able to cost-effectively harvest energy from renewable and clean energy sources at the micro/nano-scale. Their applications in the field of self-powered sensing systems and portable power supplying ...

Recently, flexible and soft bioelectronic interfaces have been proposed as a solution to improve existing neural interfaces that currently present mechanical mismatch with the soft tissue. These are devices fabricated with thin polymeric or elastomeric bac ...

With the emergence of wearable and non-intrusive med- ical devices, one major challenge is the real-time analysis of the acquired signals in real-life and ambulatory con- ditions. This paper presents a lightweight algorithm for on-line heart beat classific ...

Although many studies have elucidated the neurocognitive mechanisms supporting the processing of externally generated sensory signals, less is known about the processing of interoceptive signals related to the viscera. Drawing a parallel with research on a ...

Aims While successful termination by pacing of organized atrial tachycardias has been observed in patients, single site rapid pacing has not yet led to conclusive results for the termination of atrial fibrillation (AF). The purpose of this study was to eva ...

The aim of this work is to present different markers resulting from the analysis of a single ECG lead recorded during sinus rhythm. To this purpose, the ECGs from three populations were compared: healthy subjects, patients subject to paroxysmal AF selected ...

Early recognition of patients at high risk for atrial fibrillation may help to minimize potential health risks. The detection of susceptibility to develop atrial fibrillation is thus a real clinical challenge. Whereas many studies have used the signal-aver ...

Personalized computational electro-mechanics simulations to optimize cardiac resynchronization therapy

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PDE-Aware Deep Learning for Inverse Problems in Cardiac Electrophysiology

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Suppression of the auditory N1-component for heartbeat-related sounds reflects interoceptive predictive coding

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