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

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

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

Andreas Pautz, Oskari Ville Pakari, Vincent Pierre Lamirand

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

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

WINC: A Wireless IoT Network for Multi-Noise Source Cancellation

Haitham Al Hassanieh, Junfeng Guan, Jiaming Wang

This paper introduces Wireless IoT-based Noise Cancellation (WINC) which defines a framework for leveraging a wireless network of IoT microphones to enhance active noise cancellation in noise-canceling headphones. The IoT microphones forward ambient noise ...

Assoc Computing Machinery2023

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

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

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

Hervé Lissek, Romain Christophe Rémy Fleury, 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, Jean-Luc Starck, Utsav Akhaury, Kevin Michalewicz

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

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

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

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

Learning Disentangled Behaviour Patterns for Wearable-based Human Activity Recognition

Tao Lin

In wearable-based human activity recognition (HAR) research, one of the major challenges is the large intra-class variability problem. The collected activity signal is often, if not always, coupled with noises or bias caused by personal, environmental, or ...

ASSOC COMPUTING MACHINERY2022

Optical fibre based quench detection in HTS applications using machine learning classifiers

Bertrand Dutoit, Bertrand Dutoit, Arooj Akbar, Nicolo' Riva

A Mach-Zehnder Interferometer (MZI) based optical fibre sensing technique, developed and patented by EPFL, is an efficient and economical way to detect hotspots in High Temperature Superconductor (HTS) applications. Due to the MZI sensitivity being a compo ...

Elsevier2022