Publications related to 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

Impact of individual differences in glucocorticoid adaptation to stress on behavior, neurophysiology and metabolism

Damien Sébastien Huzard

The stress system is a key modulator of homeostasis and allows organisms to adapt to environmental changes. Proper survival is dependent on the appropriate stress response, for example initiating food (energy) intake or provoking physical reaction. However ...

EPFL2018

A Novel Short-term Event Extraction Algorithm for Biomedical Signals

Jean-Marc Vesin, Sasan Yazdani, Sibylle Fallet

In this paper we propose a fast novel non-linear filtering method named Relative-Energy (Rel-En), for robust short-term event extraction from biomedical signals. We developed an algorithm that extracts short- and long-term energies in a signal and provides ...

2018

Sampling and Exact Reconstruction of Pulses with Variable Width

Martin Vetterli, Adam James Scholefield, Loïc Arnaud Baboulaz, Gilles Baechler

Recent sampling results enable the reconstruction of signals composed of streams of fixed-shaped pulses. These results have found applications in topics as varied as channel estimation, biomedical imaging and radio astronomy. However, in many real signals, ...

Institute of Electrical and Electronics Engineers2017

Hierarchical Cardiac-Rhythm Classification Based on Electrocardiogram Morphology

David Atienza Alonso, Amir Aminifar, Elisabetta De Giovanni, Dionisije Sopic

Atrial Fibrillation (AF) is a type of cardiac arrhythmia that significantly increases the risk of stroke and heart failure. In general, in the case of patients affected by AF, their electrocardiogram (ECG) shows a typical pattern of irregular RR intervals ...

2017

A Patient-Specific Methodology for Prediction of Paroxysmal Atrial Fibrillation Onset

David Atienza Alonso, Jean-Marc Vesin, Amir Aminifar, Adrian Luca, Sasan Yazdani, Elisabetta De Giovanni

In spite of the progress in management of Atrial Fibrillation (AF), this arrhythmia is one of the major causes of stroke and heart failure. The progression of this pathology from a silent paroxysmal form (PAF) into a sustained AF can be prevented by predic ...

2017

Usefulness of P-Wave Duration and Morphologic Variability to Identify Patients Prone to Paroxysmal Atrial Fibrillation

Jean-Marc Vesin, Adrian Luca, Sasan Yazdani, Lukas Kappenberger

Few data are available on the assessment of P-wave beat-to-beat morphology variability and its ability to identify patients prone to paroxysmal atrial fibrillation (AF) occurrence. Aim of this study was to determine whether electrocardiographic (ECG) param ...

Excerpta Medica Inc-Elsevier Science Inc2017

Subject-Independent Odor Pleasantness Classification Using Brain and Peripheral Signals

Touradj Ebrahimi, Jean-Marc Vesin, Eleni Kroupi

Enhanced sensation of reality from multimedia contents can be achieved by creating realistic multimedia environments, using visual, auditory, and olfactory information. Although the affective information from video and audio has been extensively studied, t ...

Ieee-Inst Electrical Electronics Engineers Inc2016

Exploiting Prior Knowledge in Compressed Sensing Wireless ECG Systems

Rafael Eduardo Carrillo Rangel

Recent results in telecardiology show that compressed sensing (CS) is a promising tool to lower energy consumption in wireless body area networks for electrocardiogram (ECG) monitoring. However, the performance of current CS-based algorithms, in terms of c ...

2015

Ultra-low-power ECG front-end design based on compressed sensing

Pierre Vandergheynst, Hossein Mamaghanian

Ultra-low-power design has been a challenging area for design of the sensor front-ends especially in the area of Wireless Body Sensor Nodes (WBSN), where a limited amount of power budget and hardware resources are available. Since introduction of Compresse ...

ACM/IEEE Press2015

Sleep Apnea Detection using Features from the Respiration and the ECG recorded with Smart-Shirts

Jean-Marc Vesin, Leila Mirmohamadsadeghi, Andréa Buttu, Grégoire Millet, Sibylle Fallet

The automatic detection of sleep apnea episodes, without the need of polysomnography and outside a clinical facility, could help facilitate the diagnosis of this disorder. In this work, features to detect sleep apnea events were computed from respiration a ...

2014