Termination of atrial fibrillation by catheter ablation can be successfully predicted from baseline ECG

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Publications associées (31)

Association of Heart Rate Variability With Silent Brain Infarcts in Patients With Atrial Fibrillation

Vincent Schlageter, Jean-Marc Vesin

Purpose: Silent brain infarcts (SBI) are frequently detected in patients with atrial fibrillation (AF), but it is unknown whether SBI are linked to autonomic dysfunction. We aimed to explore the association of autonomic dysfunction with SBI in AF patients. ...

FRONTIERS MEDIA SA2021

Implantable Fiber Bragg Grating Sensor for Continuous Heart Activity Monitoring: Ex-Vivo and In-Vivo Validation

Silvestro Micera

Continuous and reliable cardiac function monitoring could improve medication adherence in patients at risk of heart failure. This work presents an innovative implantable Fiber Bragg Grating-based soft sensor designed to sense mechanical cardiac activity. T ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

POD-Enhanced Deep Learning-Based Reduced Order Models for the Real-Time Simulation of Cardiac Electrophysiology in the Left Atrium

Alfio Quarteroni, Andrea Manzoni

The numerical simulation of multiple scenarios easily becomes computationally prohibitive for cardiac electrophysiology (EP) problems if relying on usual high-fidelity, full order models (FOMs). Likewise, the use of traditional reduced order models (ROMs) ...

FRONTIERS MEDIA SA2021

In vivo application and validation of a novel noninvasive method to estimate the end-systolic elastance

Nikolaos Stergiopoulos, Stamatia Zoi Pagoulatou, Vasiliki Bikia, Georgios Rovas

Accurate assessment of the left ventricular (LV) systolic function is indispensable in the clinic. However, estimation of a precise index of cardiac contractility, i.e., the end-systolic elastance (E-es), is invasive and cannot be established as clinical r ...

2021

Estimation of Left Ventricular End-Systolic Elastance From Brachial Pressure Waveform via Deep Learning

Nikolaos Stergiopoulos, Stamatia Zoi Pagoulatou, Vasiliki Bikia, Marija Lazaroska, Georgios Rovas

Determination of left ventricular (LV) end-systolic elastance (E- es ) is of utmost importance for assessing the cardiac systolic function and hemodynamical state in humans. Yet, the clinical use of E- es is not established due to the invasive nature and h ...

FRONTIERS MEDIA SA2021

Hardware-oriented pruning and quantization of Deep Learning models to detect life-threatening arrhythmias

Alexandre Schmid, Lizeth Gonzalez Carabarin

Wearable solutions based on Deep Learning (DL) for real-time ECG monitoring are a promising alternative to detect life-threatening arrhythmias. However, DL models suffer of a large memory footprint, which hampers their adoption in portable technologies. Th ...

IEEE2021

Heart Rate Variability Triangular Index as a Predictor of Cardiovascular Mortality in Patients With Atrial Fibrillation

Vincent Schlageter, Jean-Marc Vesin

Background Impaired heart rate variability (HRV) is associated with increased mortality in sinus rhythm. However, HRV has not been systematically assessed in patients with atrial fibrillation (AF). We hypothesized that parameters of HRV may be predictive o ...

2020

Outer loop and isthmus in ventricular tachycardia circuits: Characteristics and implications

Alfio Quarteroni, Luca Dede', Andrea Manzoni, Stefano Pagani

BACKGROUND The isthmus of ventricular tachycardia (VT) circuits has been extensively characterized. Few data exist regarding the contribution of the outer loop (OL) to the VT circuit. OBJECTIVE The purpose of this study was to characterize the electrophysi ...

2020

Ventricular response regularity in atrial fibrillation and its relationship to successful catheter ablation

Jean-Marc Vesin, Etienne Pruvot, Adrian Luca

Atrial rate is known to modulate ventricular response during atrial fibrillation (AF). The resulting pulse irregularity translates into widely varying inter-beat intervals (IBIs) extracted from recorded surface electrocardiogram (ECG) activity. In AF, the ...

IEEE2020

Automatic 12-lead ECG Classification Using a Convolutional Network Ensemble

Manoel Horta Ribeiro

The 12-lead electrocardiogram (ECG) is a major diagnostic test for cardiovascular diseases and enhanced automated analysis tools might lead to more reliable diagnosis and improved clinical practice. Deep neural networks are models composed of stacked trans ...

IEEE2020

Monitoring of Cardiovascular and Neurological Diseases Using Wearable Devices

Dionisije Sopic

In this thesis, I focus on monitoring of patients suffering from cardiovascular and neurological diseases through the use of wearable devices. The main diseases considered in this thesis are atrial fibrillation (AF), myocardial infarction (MI), and epileps ...

EPFL2020

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