Publications related to Electrocardiography

Who says you are so sick? An investigation on individual susceptibility to cybersickness triggers using EEG, EGG and ECG

In this research paper, we conducted a study to investigate the connection between three objective measures: Electrocardiogram(ECG), Electrogastrogram (EGG), and Electroencephalogram (EEG), and individuals' susceptibility to cybersickness. Our primary obje ...

2024

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

Silvestro Micera

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

Apparatus for non-invasively computing cardio-vasculature parameters using morphology of uncalibrated pressure wave signal

Nikolaos Stergiopoulos, Georgios Rovas, Vasiliki Bikia

Systems and apparatus are provided for using a non-invasively monitored uncalibrated pressure signal from a patient to compute cardiac output and other cardio-vascular parameters, thereby providing safe, effective, reliable and low cost monitoring of patie ...

2024

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

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

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, Georgios Rovas, Vasiliki Bikia

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

A Stand-Alone Augmented Reality Intervention for Chronic Pain using Embodied Systolic Stimulation

Sylvain Cardin, Andrea Serino, Robert Leeb, Oliver Alan Kannape, Skander Mensi, Fabien Bourban, Alexis Dorier

Chronic pain presents a tremendous personal, societal, and financial burden. Treatment options are often limited to managing symptoms as opposed to treating the causes, and the consequences of pharmacological treatments can be immensely harmful as evidence ...

IEEE2023

A comprehensive mathematical model for cardiac perfusion

Alfio Quarteroni, Francesco Regazzoni, Christian Vergara

The aim of this paper is to introduce a new mathematical model that simulates myocardial blood perfusion that accounts for multiscale and multiphysics features. Our model incorporates cardiac electrophysiology, active and passive mechanics, hemodynamics, v ...

Nature Portfolio2023

Effects of Electrode Design on the Melt Electrowriting of Sinusoidal Structures

Biranche Tandon

Melt electrowriting is a microscale manufacturing technique that uses polymer-based melts to create fibrous structures. An electric field is used to stabilize a continuous molten jet, which is then written onto a substrate as a microscale fiber. Herein, it ...

WILEY-V C H VERLAG GMBH2023

Efficient approximation of cardiac mechanics through reduced-order modeling with deep learning-based operator approximation

Alfio Quarteroni, Andrea Manzoni

Reducing the computational time required by high-fidelity, full-order models (FOMs) for the solution of problems in cardiac mechanics is crucial to allow the translation of patient-specific simulations into clinical practice. Indeed, while FOMs, such as th ...

Wiley2023

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

Jean-Marc Vesin, Adrian Luca, Vincent Schlageter

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

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

Jean-Marc Vesin, Adrian Luca, Etienne Pruvot

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

PDE-Aware Deep Learning for Inverse Problems in Cardiac Electrophysiology

Alfio Quarteroni, Simone Deparis, Riccardo Tenderini, Stefano Pagani

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

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, Adrian Luca, Yann Prudat, Sasan Yazdani, Etienne Pruvot

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

Active sites on copper-based catalysts for electrochemical CO2 reduction selectively to C2+ products

Jie Zhang

Electrochemical CO2 reduction (eCO2RR) towards value-added chemicals, powered by renewable electricity, is a promising technology for storing the intermittent renewable energy in the form of chemical bonds. Among the various products of eCO2RR, multi-carbo ...

EPFL2022

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

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

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

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

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

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

Jean-Marc Vesin, Adrian Luca, Etienne Pruvot

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