Publications de Elisabetta De Giovanni

Adaptive R-Peak Detection on Wearable ECG Sensors for High-Intensity Exercise

David Atienza Alonso, Elisabetta De Giovanni, Tomas Teijeiro Campo, Grégoire Millet

Objective: Continuous monitoring of biosignals via wearable sensors has quickly expanded in the medical and wellness fields. At rest, automatic detection of vital parameters is generally accurate. However, in conditions such as high-intensity exercise, sud ...

2022

System-level Design of Adaptive Wearable Sensors for Health and Wellness Monitoring

Elisabetta De Giovanni

In recent years, population aging and the consequent higher incidence of noncommunicable diseases, have increased the need for long-term health monitoring. Moreover, as healthcare cost is projected to grow substantially by 2030 in OECD countries, the deman ...

EPFL2021

Real-Time Personalized Atrial Fibrillation Prediction on Multi-Core Wearable Sensors

David Atienza Alonso, Amir Aminifar, Miguel Peon Quiros, Adriana Arza Valdes, Elisabetta De Giovanni

In the recent Internet-of-Things (IoT) era where biomedical applications require continuous monitoring of relevant data, edge computing keeps gaining more and more importance. These new architectures for edge computing include multi-core and parallel compu ...

2021

Modular Design and Optimization of Biomedical Applications for Ultra-Low Power Heterogeneous Platforms

David Atienza Alonso, Miguel Peon Quiros, Simone Machetti, Luca Benini, Benoît Walter Denkinger, Elisabetta De Giovanni, Fabio Montagna

In the last years, remote health monitoring is becoming an essential branch of health care with the rapid development of wearable sensors technology. To meet the demand of new more complex applications and ensuring adequate battery lifetime, wearable senso ...

2020

REWARD: Design, Optimization, and Evaluation of a Real-Time Relative-Energy Wearable R-Peak Detection Algorithm *

David Atienza Alonso, Jean-Marc Vesin, Sasan Yazdani, Lara Orlandic, Adriana Arza Valdes, Elisabetta De Giovanni

Wearable devices are an unobtrusive, cost-effective means of continuous ambulatory monitoring of chronic cardiovascular diseases. However, on these resource-constrained systems, electrocardiogram (ECG) processing algorithms must consume minimal power and m ...

2019

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

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

Ultra-Low Power Estimation of Heart Rate Under Physical Activity Using a Wearable Photoplethysmographic System

David Atienza Alonso, Francisco Javier Rincon Vallejos, Srinivasan Murali, Elisabetta De Giovanni

In the last years, the need for enhancing health and preventing problems with remote monitoring is increasing. A non-invasive low-cost technique for processing bio-signals and monitoring vital parameters, at rest and during physical activity, is the use of ...

IEEE Press2016