Publications associées à Towards Whole Body Fatigue Assessment of Human Movement: A Fatigue-Tracking System Based on Combined sEMG and Accelerometer Signals

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

Axel Bisi, Alberto Silvio Chiappa, Alexander Mathis, Alessandro Marin Vargas

Here we provide the neural data, activation and predictions for the best models and result dataframes of our article "Task-driven neural network models predict neural dynamics of proprioception". It contains the behavioral and neural experimental data (cu ...

EPFL Infoscience2024

An Ultralow-Power Triaxial MEMS Accelerometer With High-Voltage Biasing and Electrostatic Mismatch Compensation

Yimai Peng, Li Xu, Kyojin Choo

This article presents a triaxial micro electromechani-cal system (MEMS) capacitive accelerometer using a high-voltage biasing technique to achieve high resolution with ultralow power. The accelerometer system generates a differential pair of high voltages ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Comparing transferability in neural network approaches and linear models for machine-learning interaction potentials

Kevin Rossi

Atomic simulations using machine learning interatomic potential (MLIP) have gained a lot of popularity owing to their accuracy in comparison to conventional empirical potentials. However, the transferability of MLIP to systems outside the training set pose ...

AMER PHYSICAL SOC2023

Harmonization of multi-scanner in vivo magnetic resonance spectroscopy: ENIGMA consortium task group considerations

Cristina Ramona Cudalbu

Magnetic resonance spectroscopy is a powerful, non-invasive, quantitative imaging technique that allows for the measurement of brain metabolites that has demonstrated utility in diagnosing and characterizing a broad range of neurological diseases. Its impa ...

FRONTIERS MEDIA SA2023

Evaluating contrast sensitivity in early and intermediate age-related Macular Degeneration with the Quick Contrast Sensitivity Function

Michael Herzog, Simona Adele Garobbio

Purpose: The purpose of this study was to describe, validate, and compare the contrast sensitivity functions (CSFs) acquired with the novel quick CSF (qCSF) method from patients with early and intermediate age-related macular degeneration (eAMD and iAMD) a ...

2023

The inductive bias of deep learning: Connecting weights and functions

Guillermo Ortiz Jimenez

Years of a fierce competition have naturally selected the fittest deep learning algorithms. Yet, although these models work well in practice, we still lack a proper characterization of why they do so. This poses serious questions about the robustness, trus ...

EPFL2023

Exploration of the parameter space for the excitation and saturation of Edge Harmonic Oscillations

Guillermo Bustos Ramirez

This thesis presents advancements in the understanding of the plasma conditions leading to the excitation and saturation of the Edge Harmonic Oscillations (EHOs) observed during QH-mode operation in tokamak plasmas. Such operations represent a safer altern ...

EPFL2023

Complex Daily Activities, Country-Level Diversity, and Smartphone Sensing: A Study in Denmark, Italy, Mongolia, Paraguay, and UK

Daniel Gatica-Perez, Karim Assi, Lakmal Buddika Meegahapola

Smartphones enable understanding human behavior with activity recognition to support peoples daily lives. Prior studies focused on using inertial sensors to detect simple activities (sitting, walking, running, etc.) and were mostly conducted in homogeneous ...

Assoc Computing Machinery2023

Fundamental Limits in Statistical Learning Problems: Block Models and Neural Networks

Elisabetta Cornacchia

This thesis focuses on two selected learning problems: 1) statistical inference on graphs models, and, 2) gradient descent on neural networks, with the common objective of defining and analysing the measures that characterize the fundamental limits. In th ...

EPFL2023

Inter-Individual Variability in Motor Output Is Driven by Recruitment Gain in the Corticospinal Tract Rather Than Motor Threshold

Traian Popa

Variability in the response of individuals to various non-invasive brain stimulation protocols is a major problem that limits their potential for clinical applications. Baseline motor-evoked potential (MEP) amplitude is the key predictor of an individual's ...

MDPI2022

Data-Driven Predictive Models: Calculational Bias in Characterization of Spent Nuclear Fuel

Characteristics of the spent nuclear fuel (SNF) are typically calculated, requiring validation a priori. The validation process relies on the difference between calculations and measurements, namely the bias. Usually, predicting the bias based on benchmark ...

EPFL2022

On Preconditioning of Decentralized Gradient-Descent When Solving a System of Linear Equations

Nirupam Gupta

This article considers solving an overdetermined system of linear equations in peer-to-peer multiagent networks. The network is assumed to be synchronous and strongly connected. Each agent has a set of local data points, and their goal is to compute a line ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Concurrent Evolution of Biomechanical and Physiological Parameters With Running-Induced Acute Fatigue

Kamiar Aminian, Anisoara Ionescu, Gaëlle Prigent, Salil Apte, Vincent Gremeaux

Understanding the influence of running-induced acute fatigue on the homeostasis of the body is essential to mitigate the adverse effects and optimize positive adaptations to training. Fatigue is a multifactorial phenomenon, which influences biomechanical, ...

FRONTIERS MEDIA SA2022

Iterative pre-conditioning for expediting the distributed gradient-descent method: The case of linear least-squares problem

Nirupam Gupta

This paper considers the multi-agent linear least-squares problem in a server-agent network architecture. The system comprises multiple agents, each with a set of local data points. The agents are connected to a server, and there is no inter-agent communic ...

PERGAMON-ELSEVIER SCIENCE LTD2022

An Inertial Uni-Axial Interferometer-Based Accelerometer for Harsh Environments

Mark Edward John Butcher, Gerard Aliana Cervera

For high-impact devices, subsequent vibrations have as much influence on the deterioration of the mechanical structure as the impact itself. To mitigate the consequences of both impacts and resulting vibrations, it is crucial to accurately understand the p ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Human Head Yaw Estimation based on Two 3-axis Accelerometers

Hervé Lissek, Gilles André Courtois, Vincent Pierre Olivier Grimaldi

The estimation of the orientation of an object, and a human head in particular, can be defined by the Euler angles: the yaw, pitch and roll. The robust and drift-free estimation of those angles is usually achieved with the data from several sensors such as ...

2022

Multivariate time series forecasting for freeway networks

Semin Kwak

This dissertation introduces traffic forecasting methods for different network configurations and data availability. Chapter 2 focuses on single freeway cases. Although its topology is simple, the non-linearity of traffic features makes this prediction sti ...

EPFL2022

Local Kernel Regression and Neural Network Approaches to the Conformational Landscapes of Oligopeptides

Anne-Clémence Corminboeuf, Alberto Fabrizio, Michele Ceriotti, Benjamin André René Meyer, Raimon Fabregat I De Aguilar-Amat, Veronika Juraskova, Edgar Albert Engel

The application of machine learning to theoretical chemistry has made it possible to combine the accuracy of quantum chemical energetics with the thorough sampling of finite-temperature fluctuations. To reach this goal, a diverse set of methods has been pr ...

2022

Genomic Diversity of Torque Teno Virus in Blood Samples from Febrile Paediatric Outpatients in Tanzania: A Descriptive Cohort Study

Mary-Anne Hartley

Torque teno virus (TTV) is considered to be an ubiquitous member of the commensal human blood virome commonly reported in mixed genotype co-infections. This study investigates the genomic diversity of TTV in blood samples from 816 febrile Tanzanian childre ...

MDPI2022

On the benefit of concurrent adjustment of active and passive optical sensors with GNSS & raw inertial data

Jan Skaloud, Davide Antonio Cucci, Kyriaki Mouzakidou

In airborne laser scanning a high-frequency trajectory solution is typically determined from inertial sensors and employed to directly geo-reference the acquired laser points. When low-cost MEMS inertial sensors are used, such as in lightweight unmanned ae ...

2022