Study of Conduction Mechanisms in Antistatic Felts at the Mesoscopic Scale

peer reviewedThis work is part of a project that deals with the optimization of the quantity and the nature of conductive fibers in antistatic felts used for filtering and sieving powders. Our research concerns the electrical properties at the mesoscopic scale. It aims at determining the conduction mechanisms and the distribution of the electric potential at the scale of the distance between the conductive fibers. In this paper, current-voltage (I-V) measurement results are presented and discussed. X-ray microtomography is used to obtain the geometry of the conductive fibers inside the felts before and after these I-V tests. The studied textile material is based on polyester fibers and stainless steel conductive fibers.Nouvelle conception de filtres textiles antistatique

Analysis of temporal gait features extracted from accelerometer-based signals during ambulatory walking in Parkinson’s disease

Objective: To perform a proof-of-concept study showing the utility of versatile algorithms aimed at objectively quantifying the duration of refined gait features during ambulatory walking in a patient with Parkinson’s disease (PD) in ON and OFF medication states as compared with an age-matched control subject

A Perturbation Finite Element Technique for Modeling Electrostatic MEMS

Projet ARC (Convention 03/08-298, “Modélisation, Simulation Multiphysique et Optimisation de Problèmes Couplés - Application aux Micro-Systèmes Électromécaniques (MEMS)”

Human Activity Recognition for the Assessment of Daily-life Activities Using Machine Learning

editorial reviewedThis study is part of a larger project that focuses on the recording and analysis of movement and physiological data for clinical applications. One aim of the project is to extract gait parameters that can help in identifying abnormal human movements. Human activity recognition (HAR) is an important field of study that has the potential to recognize daily-life activities from gait parameters and has applications in the areas of medical diagnosis and fitness tracking [1]. The goal of this study is to extract small- and large-scale characteristics from IMU and physiological data that can assist in identifying a variety of daily activities to design a HAR system. In this study, we designed a human activity detection algorithm by fusing cutting-edge signal processing and machine learning methods. Existing IMU-based hardware has been used to record movement signals [2]. On 10 healthy volunteers, the proposed algorithm was evaluated to recognize 10 different static, dynamic, and transitional activities. To identify the different human movements, the recorded data estimated the number of time, frequency, and time-frequency characteristics. The classifier was created using the ensemble machine learning method known as random subspace (RS). Each participant received individualized hold-on validation for RS (70% of the data were utilized for training and the remaining 30% for testing). By reaching an overall accuracy of 97.11%, the findings show that the developed algorithm is capable of differentiating among various activities. The proposed algorithm as conceived works well for static, dynamic, and transitional tasks (figure 1). The suggested technique may be used to automatically identify typical everyday tasks for the effective management of movement disorders

A perturbation method for the 3D Finite Element Modeling

Projet ARC (Convention 03/08-298, “Modélisation, Simulation Multiphysique et Optimisation de Problèmes Couplés - Application aux Micro-Systèmes Électromécaniques (MEMS)”

Méthode de Perturbation pour la Modélisation par Éléments Finis des Systèmes Électrostatiques en Mouvement - Application aux MEMS Électrostatiques

audience: researcher, professional, studentLa modélisation par éléments finis des conducteurs en mouvement nécessite généralement des calculs successifs et le remalliage de certaines régions. Une modélisation 3D de géométries complexes par les techniques classiques nécessite dès lors de gros efforts en terme de temps de calcul. Dans cette thèse, une méthode originale basée sur une approche par sous-problèmes, appelée méthode de perturbation, a été développée. Utilisant la méthode des éléments finis, cette technique consiste à subdiviser un problème entier en sous-problèmes. La complexité du problème initial est par conséquent diminuée en ne se concentrant que sur les zones les plus pertinentes. Appliquée aux systèmes en mouvement, la méthode de perturbation permet d'exploiter les résolutions antérieures au lieu d'effectuer un nouveau calcul pour chaque position. L'analyse par la méthode de perturbation des microsystèmes électromécaniques (MEMS) électrostatiques comprenant des parties en déplacement ou en déformation est en outre considérée dans ce travail. Il est notamment question de démontrer l'implication naturelle de cette approche pour des simulations plus efficaces et plus précises des MEMS électrostatiques.projet ARC (Convention 03/08-298, “Modélisation, Simulation Multiphysique et Optimisation de Problèmes Couplés - Application aux Micro-Systèmes Electromécaniques (MEMS)”

An iterative finite element perturbation method for computing electrostatic field distortions

A finite element perturbation method is developed for computing electrostatic field distortions and the ensuing charges and forces on moving conductive regions subjected to fixed potentials. It is based on the subsequent solution of an unperturbed problem in a complete domain, where conductive regions have been extracted, and of perturbation problems in subdomains restricted to the surroundings of the added conductive regions. The solution of the unperturbed problem serves as source (with a very reduced support) for the perturbation subproblems. For every new position of the conductors, the solution of the unperturbed problem does not vary and is thus reused; only the perturbation subproblems have to be solved. Further, this approach allows for the use of independent and well-adapted meshes. An iterative procedure is required if the conductive regions are close to the sources

Electrostatic Analysis of Moving Conductors Using a Perturbation Finite Element Method

This paper deals with the analysis of electrostatic problems involving moving devices by means of a perturbation finite element method. A reference problem without any moving parts is first solved and gives the source for a sequence of perturbation problems in subdomains restricted to the neighborhood of these parts. The source accounts for all the previous calculations for preceding positions what increases the efficiency of the simulations. This proposed approach also improves the computation accuracy and decreases the complexity of the analysis of moving conductors thanks to the use of independent and adaptively refined meshes

A Perturbation Finite Element Method for Modeling Electrostatic MEMS without Remeshing

peer reviewedThis paper deals with the coupled electrostatic- mechanical analysis of electrostatically actuated MEMS. An iterative perturbation procedure in conjunction with the finite element method is used to solve the coupled problem without the need of remeshing the whole electric domain. The method offers the advantage of overcoming degenerated finite elements in the mesh of some electric regions where the deflection of the MEMS moving parts is critical. The actuation of such systems is achieved by applying either an electric voltage or a global charge