Publications associées à Adaptive Frequency Tracking on the ECG Used to Predict the Success of Electrical Cardioversion of Atrial Fibrillation

Implementation of an epicardial implantable MEMS sensor for continuous and real-time postoperative assessment of left ventricular activity in adult minipigs over a short- and long-term period

The sensing of left ventricular (LV) activity is fundamental in the diagnosis and monitoring of cardiovascular health in high-risk patients after cardiac surgery to achieve better short- and long-term outcome. Conventional approaches rely on noninvasive me ...

Aip Publishing2024

Finding information-rich electrocardiographic biomarkers to characterize atrial fibrillation

Anna Mary Mc Cann

Atrial fibrillation (AF) is the most common cardiac arrhythmia; it will affect one in four adults worldwide in their lifetime. AF has serious consequences, including drastically increased risk of stroke. Catheter ablation surgery is an established treatmen ...

EPFL2023

Left cardiac vagotomy rapidly reduces contralateral cardiac vagal electrical activity in anesthetized Gottingen minipigs

Silvestro Micera, Ivo Strauss

Background: The impact of acute unilateral injury on spontaneous electrical activity in both vagus nerves at the heart level is poorly understood. We investigated the immediate neuroelectrical response after right or left cardiac vagal nerve transection (V ...

Elsevier Ireland Ltd2023

A single-beat algorithm to discriminate farfield from nearfield bipolar voltage electrograms from the pulmonary veins

Vincent Schlageter, Jean-Marc Vesin, Adrian Luca

Background Superimposition of farfield (FF) and nearfield (NF) bipolar voltage electrograms (BVE) complicates the confirmation of pulmonary vein (PV) isolation after catheter ablation of atrial fibrillation. Our aim was to develop an automatic algorithm ba ...

SPRINGER2023

Single-arm diagnostic electrocardiography with printed graphene on wearable textiles

Ata Jedari Golparvar

Stimulated by the COVID-19 outbreak, the global healthcare industry better acknowledges the necessity of innovating novel methods for remote healthcare monitoring and treating patients outside clinics. Here we report the development of two different types ...

ELSEVIER SCIENCE SA2023

Cardiovascular response to closed-loop intraneural stimulation of the right vagus nerve: a proof-of-concept study

Silvestro Micera

Vagus nerve stimulation (VNS) is an FDA-approved technique for the neuromodulation of the autonomic nervous system. There are many therapeutic applications where VNS could be used as a therapy, such as cardiovascular diseases, epilepsy, depression, and inf ...

IEEE2023

Flexible Silk-Based Graphene Bioelectronics For Wearable Multimodal Physiological Monitoring

Ata Jedari Golparvar

We introduce a skin-inspired epidermal bioelectronic patch (EBP) with unprecedented integration of graphene on silk with a facile and cost-effective fabrication process, excluding complex ink formulation. We advance the state-of-the-art by directly screen- ...

IEEE2023

Cardiac output estimated from an uncalibrated radial blood pressure waveform: validation in an in-silico-generated population

Nikolaos Stergiopoulos, Vasiliki Bikia, Georgios Rovas

Background: Cardiac output is essential for patient management in critically ill patients. The state-of-the-art for cardiac output monitoring bears limitations that pertain to the invasive nature of the method, high costs, and associated complications. Hen ...

FRONTIERS MEDIA SA2023

Novel spatiotemporal processing tools for body-surface potential map signals for the prediction of catheter ablation outcome in persistent atrial fibrillation

Jean-Marc Vesin, Etienne Pruvot, Adrian Luca

Background: Signal processing tools are required to efficiently analyze data collected in body-surface-potential map (BSPM) recordings. A limited number of such tools exist for studying persistent atrial fibrillation (persAF). We propose two novel, spatiot ...

FRONTIERS MEDIA SA2022

Evaluation and optimization of novel extraction algorithms for the automatic detection of atrial activations recorded within the pulmonary veins during atrial fibrillation

Jean-Marc Vesin, Yann Prudat, Etienne Pruvot, Sasan Yazdani, Adrian Luca

Background and objective The automated detection of atrial activations (AAs) recorded from intracardiac electrograms (IEGMs) during atrial fibrillation (AF) is challenging considering their various amplitudes, morphologies and cycle length. Activation time ...

BMC2022

Correlation between conduction velocity and frequency analysis in patients with atrial fibrillation using high-density charge mapping

Lam Dang, Jean-Marc Vesin

Spectral analysis of atrial signals has been used to identify regions of interest in atrial fibrillation (AF). However, the relationship to the atrial substrate is unclear. In this study, we compare regions with dominant frequency (DF), simultaneously dete ...

SPRINGER HEIDELBERG2022

Active force generation contributes to the complexity of spontaneous activity and to the response to stretch of murine cardiomyocyte cultures

Stéphanie Lacour

Cardiomyocyte cultures exhibit spontaneous electrical and contractile activity, as in a natural cardiac pacemaker. In such preparations, beat rate variability exhibits features similar to those of heart rate variability in vivo. Mechanical deformations and ...

WILEY2022

Impact of atrial fibrillation on left atrium haemodynamics: A computational fluid dynamics study

Alfio Quarteroni, Luca Dede'

We analyse the haemodynamics of the left atrium, highlighting differences between healthy individuals and patients affected by atrial fibrillation. The computational study is based on patient-specific geometries of the left atria to simulate blood flow dyn ...

PERGAMON-ELSEVIER SCIENCE LTD2022

PDE-Aware Deep Learning for Inverse Problems in Cardiac Electrophysiology

Alfio Quarteroni, Simone Deparis, Stefano Pagani, Riccardo Tenderini

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 ...

2022

ECG-Based Indices to Characterize Persistent Atrial Fibrillation Before and During Stepwise Catheter Ablation

Jean-Marc Vesin, Etienne Pruvot, Adrian Luca

Background: Consistently successful patient outcomes following catheter ablation (CA) for treatment of persistent atrial fibrillation (pers-AF) remain elusive. We propose an electrocardiogram (ECG) analysis designed to (1) refine selection of patients most ...

2021

A Computational Study of the Electrophysiological Substrate in Patients Suffering From Atrial Fibrillation

Alfio Quarteroni, Andrea Manzoni

In the context of cardiac electrophysiology, we propose a novel computational approach to highlight and explain the long-debated mechanisms behind atrial fibrillation (AF) and to reliably numerically predict its induction and sustainment. A key role is pla ...

FRONTIERS MEDIA SA2021

Dynamics of Intraprocedural Dominant Frequency Identifies Ablation Outcome in Persistent Atrial Fibrillation

Jean-Marc Vesin, Andréa Buttu, Etienne Pruvot, Alain Pithon, Adrian Luca

Background: The role of dominant frequency (DF) in tracking the efficiency of a stepwise catheter ablation (step-CA) in persistent atrial fibrillation (peAF) remains poorly studied. We hypothesized that the DF time-course during step-CA displays divergent ...

2021

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

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