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

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

Fast-Response Variable-Stiffness Magnetic Catheters for Minimally Invasive Surgery

Dario Floreano, Jun Shintake, Yi Sun, Yegor Piskarev, Matteo Righi

In minimally invasive surgery, such as cardiac ablation, magnetically steered catheters made of variable-stiffness materials can enable higher dexterity and higher force application to human tissue. However, the long transition time between soft and rigid ...

2024

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Arnout Jan J Devos

Machine learning (ML) enables artificial intelligent (AI) agents to learn autonomously from data obtained from their environment to perform tasks. Modern ML systems have proven to be extremely effective, reaching or even exceeding human intelligence. Altho ...

EPFL2024

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

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

lifex-ep: a robust and efficient software for cardiac electrophysiology simulations

Alfio Quarteroni, Francesco Regazzoni, Marco Fedele, Stefano Pagani

Background: Simulating the cardiac function requires the numerical solution of multi-physics and multi-scale mathematical models. This underscores the need for streamlined, accurate, and high-performance computational tools. Despite the dedicated endeavors ...

BMC2023

Towards Robust Monitoring of the Laser Powder Bed Fusion Process based on Acoustic Emission combined with Machine Learning Solutions

Rita Drissi Daoudi

Laser Powder Bed Fusion (LPBF) is an Additive Manufacturing (AM) process consolidating parts layer by layer, from a metallic powder bed. It allows no limitation in terms of geometry and is therefore of particular interest to various industries. Metallic LP ...

EPFL2023

Euclid preparation XXII. Selection of quiescent galaxies from mock photometry using machine learning

Georges Meylan, Frédéric Courbin, Fabio Finelli, Richard Massey, Maurizio Martinelli, Gianluca Castignani, Marcello Farina, Austin Chandler Peel, Yi Wang

The Euclid Space Telescope will provide deep imaging at optical and near-infrared wavelengths, along with slitless near-infrared spectroscopy, across similar to 15 000deg(2) of the sky. Euclid is expected to detect similar to 12 billion astronomical source ...

EDP SCIENCES S A2023

RMAML: Riemannian meta-learning with orthogonality constraints

Soumava Kumar Roy

Meta-learning is the core capability that enables intelligent systems to rapidly generalize their prior ex-perience to learn new tasks. In general, the optimization-based methods formalize the meta-learning as a bi-level optimization problem, that is a nes ...

ELSEVIER SCI LTD2023

Deriving Major Ion Concentrations at High Resolution from Continuous Electrical Conductivity Measurements in Karst Systems

Paolo Benettin

Time series of hydrochemical parameters support the investigation of dominant karst hydrological processes and conceptual model structures. Nevertheless, high costs for sample collection and analyses cause hydrochemical data to be rarely available at a suf ...

SPRINGER INTERNATIONAL PUBLISHING AG2023

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

A Variable Stiffness Magnetic Catheter Made of a Conductive Phase-Change Polymer for Minimally Invasive Surgery

Dario Floreano, Jun Shintake, Yegor Piskarev

Variable stiffness (VS) is an important feature that significantly enhances the dexterity of magnetic catheters used in minimally invasive surgeries. Existing magnetic catheters with VS consist of sensors, heaters, and tubular structures filled with low me ...

2022

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

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

Using Machine Learning to Predict Mortality for COVID-19 Patients on Day 0 in the ICU

Sahand Jamal Rahi, Nahal Mansouri

Rationale: Given the expanding number of COVID-19 cases and the potential for new waves of infection, there is an urgent need for early prediction of the severity of the disease in intensive care unit (ICU) patients to optimize treatment strategies.Objecti ...

FRONTIERS MEDIA SA2022

Latent Space Slicing for Enhanced Entropy Modeling in Learning-Based Point Cloud Geometry Compression

Touradj Ebrahimi, Davi Nachtigall Lazzarotto

The growing adoption of point clouds as an imaging modality has stimulated the search for efficient solutions for compression. Learning-based algorithms have been reporting increasingly better performance and are drawing the attention from the research com ...

IEEE2022

Prognostic Implications of the Novel Pulmonary Hypertension Definition in Patients with Aortic Stenosis after Transcatheter Valve Replacement

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

Introduction: Pulmonary hypertension (PH), traditionally defined as a mean pulmonary artery pressure (PAP) >= 25 mmHg, is associated with poor outcomes in patients undergoing a transcatheter aortic valve replacement (TAVR) for severe aortic stenosis (AS). ...

MDPI2022