Publications associées à Signal-averaged electrocardiogram

Finding information-rich electrocardiographic biomarkers to characterize atrial fibrillation

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

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

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

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

Jean-Marc Vesin, Vincent Schlageter

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

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

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

Compressed sensing with signal averaging for improved sensitivity and motion artifact reduction in fluorine-19 MRI

Tobias Kober, Tom Hilbert, Jérôme Yerly, Ruud van Heeswijk, Elena Najdenovska

Fluorine-19 (F-19) MRI of injected perfluorocarbon emulsions (PFCs) allows for the non-invasive quantification of inflammation and cell tracking, but suffers from a low signal-to-noise ratio and extended scan time. To address this limitation, we tested the ...

WILEY2020

Denoising ECG Signal by CSTFM Algorithm: Monitoring During Motorbike and Car Races

Guglielmo Frigo

mHealth technology, by using habitual devices, i.e., smartphones, improves prevention, diagnosis, treatment, monitoring, and management of health. Monitoring heart profile during intense sports activities allows to diagnose pathologies, not identifiable wi ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2019

Robust ECG Denoising for eHealth Applications

Guglielmo Frigo

Portable monitoring devices have provided an important cost-effective solution in the development of eHealth applications, providing opportunities for population-wide promotion of physical activity. Monitoring heart profile parameters during extensive acti ...

IEEE2018

A modular low-complexity ECG delineation algorithm for real-time embedded systems

David Atienza Alonso, Francisco Javier Rincon Vallejos, Roman Hermida Correa

This work presents a new modular and lowcomplexity algorithm for the delineation of the different ECG waves (QRS, P and T peaks, onsets and end). Involving a reduced number of operations per second and having a small memory footprint, this algorithm is int ...

2018