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

Publications associées (33)

Less Conservatism, Stronger Robustness: Iterative Robust Gain-Scheduled Path Following Control of Autonomous Bus With Unstructured and Changing Dynamics

Path-following control is a critical technology for autonomous vehicles. However, time-varying parameters, parametric uncertainties, external disturbances, and complicated environments significantly challenge autonomous driving. We propose an iterative rob ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Tracking single hiPSC-derived cardiomyocyte contractile function using CONTRAX an efficient pipeline for traction force measurement

Gaspard Pardon

Cardiomyocytes derived from human induced pluripotent stem cells (hiPSC-CMs) are powerful in vitro models to study the mechanisms underlying cardiomyopathies and cardiotoxicity. Quantification of the contractile function in single hiPSC-CMs at high-through ...

Nature Research2024

Neutron-Gamma Noise Measurements in a Zero-Power Reactor Using Organic Scintillators

Andreas Pautz, Vincent Pierre Lamirand, Oskari Ville Pakari

Noise measurements in light water reactor systems aid in generating validation data for integral point kinetic parameter predictions and generating monitoring parameters for reactor safety and safeguards. The CROCUS zero-power reactor has been used to supp ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Data-Driven Control and Optimization under Noisy and Uncertain Conditions

Baiwei Guo

Control systems operating in real-world environments often face disturbances arising from measurement noise and model mismatch. These factors can significantly impact the perfor- mance and safety of the system. In this thesis, we aim to leverage data to de ...

EPFL2023

Data for: "A Neural-Network-Based Convex Regularizer for Inverse Problems"

Michaël Unser, Alexis Marie Frederic Goujon, Pakshal Narendra Bohra, Sebastian Jonas Neumayer, Stanislas Ducotterd

Data for: "A Neural-Network-Based Convex Regularizer for Inverse Problems". The corresponding scripts can be accessed on GitHub (https://github.com/axgoujon/convex_ridge_regularizers). The data is organized as follows: - ct_data_sets.tar.gz: contains prepr ...

Zenodo2023

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

From Nano to Macro An overview of the IEEE Bio Image and Signal Processing Technical Committee

Michaël Unser, Dimitri Nestor Alice Van De Ville, Michael Stefan Daniel Liebling

The Bio Image and Signal Processing (BISP) Technical Committee (TC) of the IEEE Signal Processing Society (SPS) promotes activities within the broad technical field of biomedical image and signal processing. Areas of interest include medical and biological ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Observation of non-reciprocal harmonic conversion in real sounds

Romain Christophe Rémy Fleury, Hervé Lissek, Xinxin Guo

Reciprocity guarantees that in most media, sound transmission is symmetric between two points of space when the location of the source and receiver are interchanged. This fundamental law can be broken in non-linear media, often at the cost of detrimental i ...

2023

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

Optimal digital filter selection for remote photoplethysmography (rPPG) signal conditioning

Ata Jedari Golparvar

Remote photoplethysmography (rPPG) using camera-based imaging has shown excellent potential recently in vital signs monitoring due to its contactless nature. However, the optimum filter selection for pre-processing rPPG data in signal conditioning is still ...

IOP Publishing Ltd2023

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

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

Deep learning-based galaxy image deconvolution

Frédéric Courbin, Pascale Jablonka, Utsav Akhaury

With the onset of large-scale astronomical surveys capturing millions of images, there is an increasing need to develop fast and accurate deconvolution algorithms that generalize well to different images. A powerful and accessible deconvolution method woul ...

FRONTIERS MEDIA SA2022

On the reconstruction of the attenuation function of a return-stroke current from the Fourier Transform of finite-duration measurements

Farhad Rachidi-Haeri, Marcos Rubinstein

A correct representation of the lightning current is crucial when the electromagnetic field radiated to a point of interest has to be computed. Based on the engineering models of Transmission Line type, such representation involves the knowledge of the ret ...

2022

A Noise-Resistant Mixed-Discrete Particle Swarm Optimization Algorithm for the Automatic Design of Robotic Controllers

Alcherio Martinoli, Cyrill Silvan Baumann

The automatic design of well-performing robotic controllers is still an unsolved problem due to the inherently large parameter space and noisy, often hard-to-define performance metrics, especially when sequential tasks need to be accomplished. Distal contr ...

2022

Plasma-based Electroacoustic Actuator for Broadband Sound Absorption

Stanislav Sergeev

Environmental noise, mostly related to human activities, has an immense impact on public health. The development of noise reduction technologies is paramount in addressing this problem. Because of practical and economic reasons, a compact, broadband, light ...

EPFL2022

Compound Admittance Matrix Estimation of Three-phase Untransposed Power Distribution Grids using Synchrophasor Measurements

Mario Paolone, Jean-Yves Le Boudec, Fabrizio Sossan, Rahul Kumar Gupta

The paper considers the problem of estimating the parameters of the compound admittance matrix of three-phase untransposed low-and medium-voltage electrical distribution networks using synchrophasor measurements from phasor measurement units (PMUs). The wo ...

2021

An Efficient Signal-to-noise Approximation for Eccentric Inspiraling Binaries

Alexandra Shelest

Eccentricity has emerged as a potentially useful tool for helping to identify the origin of black hole mergers. However, eccentric templates can be computationally very expensive owing to the large number of harmonics, making statistical analyses to distin ...

IOP Publishing Ltd2022

Bayesian Methods for the Identification of Distribution Networks

Giancarlo Ferrari Trecate, Pulkit Nahata, Jean-Sébastien Hubert Brouillon

The increasing integration of intermittent renewable generation, especially at the distribution level, necessitates advanced planning and optimisation methodologies contingent on the knowledge of the admittance matrix, capturing the topology and line param ...

IEEE2021

High accuracy measurement of the prompt neutron decay constant in CROCUS using Gamma Noise and bootstrapped uncertainties

Andreas Pautz, Vincent Pierre Lamirand, Oskari Ville Pakari, Pavel Frajtag, Tom Mager

We experimentally demonstrate the advantages of gamma detection for noise measurements to deter-mine the prompt neutron decay constant a of a nuclear reactor using the power spectral density (PSD) method, coupled to a new uncertainty estimation scheme base ...

PERGAMON-ELSEVIER SCIENCE LTD2022