Publications associées à Electrically Assisted Movement Therapy in Chronic Stroke Patients With Severe Upper Limb Paresis: A Pilot, Single-Blind, Randomized Crossover Study

Efficacy and safety of transcranial direct current stimulation to the ipsilesional motor cortex in subacute stroke (NETS): a multicenter, randomized, double-blind, placebo-controlled trial

Background Each year, five million people are left disabled after stroke. Upper -extremity (UE) dysfunction is a leading problem. Neuroplasticity can be enhanced by non-invasive brain stimulation (NIBS) but evidence from large, randomized multicenter trial ...

Elsevier2024

Using Negative Control Populations to Assess Unmeasured Confounding and Direct Effects

Mats Julius Stensrud

Sometimes treatment effects are absent in a subgroup of the population. For example, penicillin has no effect on severe symptoms in individuals infected by resistant Staphylococcus aureus, and codeine has no effect on pain in individuals with certain polym ...

Lippincott Williams & Wilkins2024

A First-in-Human Randomized Study to Assess the Safety, Tolerability, Pharmacokinetics, and Neutralization Profile of Two Investigational Long-Acting Anti-SARS-CoV-2 Monoclonal Antibodies

Didier Trono, Norman Lionel Moullan

Introduction: COVID-19 remains a significant risk for the immunocompromised given their lower responsiveness to vaccination or infection. Therefore, passive immunity through long-acting monoclonal antibodies (mAbs) offers a needed approach for pre-exposure ...

2024

Context-Aware Monitoring of Hand Motor Primitives in Daily Life Activities: A Pathway to Objectively Assess Rehabilitation of Patients with Upper-Limb Neurological Impairment

The hands, our silent performers in daily life, face overwhelming challenges when neurological impairments disrupt the simple tasks that compose our daily symphony. This thesis unveils a comprehensive framework for the objective monitoring of upper-limb re ...

EPFL2024

A comprehensive stroke risk assessment by combining atrial computational fluid dynamics simulations and functional patient data

Alfio Quarteroni

Stroke, a major global health concern often rooted in cardiac dynamics, demands precise risk evaluation for targeted intervention. Current risk models, like the CHA 2 DS 2 -VASc \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepa ...

Nature Portfolio2024

The role of computational methods in cardiovascular medicine: a narrative review

Alfio Quarteroni, Luca Dede', Christian Vergara, Stefano Pagani

Background and Objective: Computational models of the cardiovascular system allow for a detailed and quantitative investigation of both physiological and pathological conditions, thanks to their ability to combine clinical-possibly patient-specific-data wi ...

Ame Publishing Company2024

Reversible photo-electrochemical device for solar hydrogen and power generation

Sophia Haussener, Alexandre Dominique M. Cattry, Saurabh Yuvraj Tembhurne, Matthieu Jonin, Mahendra Patel

A reversible photo-electrochemical device operating under concentrated irradiation could offer a stand-alone solution for producing solar fuel (in photo-driven electrolysis mode) and power (in fuel cell mode). This strategy would present the advantage of h ...

2024

Combination of Neurotechnologies Towards Personalized Neurorehabilitation for Stroke Patients

Claudia Bigoni

"Ensure healthy lives and promote well-being for all at all ages" is the third sustainable development goal for the United Nations Agenda of 2030. This doctoral thesis fully embodied this objective by targeting stroke, a leading cause of death and disabili ...

EPFL2023

Neurophysiological underpinnings of an intensive protocol for upper limb motor recovery in subacute and chronic stroke patients

Silvestro Micera, Matteo Vissani, Michael Lassi

ABS T R A C T BACKGROUND: Upper limb (UL) motor impairment following stroke is a leading cause of functional limitations in activities of daily living. Robot-assisted therapy supports rehabilitation, but how its efficacy and the underlying neural mechanism ...

Edizioni Minerva Medica2023

Longitudinal evaluation of the mechanisms supporting post-stroke motor recovery using TMS-EEG coupling

Andéol Geoffroy Cadic-Melchior

Stroke is the main source of long-lasting disability, affecting dominantly motor functions. The extent and course of recovery are highly heterogeneous between patients, with a minority of patients fully recovering from their initial impairments, leaving 85 ...

EPFL2023

Classification of patients with cardiac amyloidosis using machine learning models on Italian electronic clinical health records

Silvestro Micera, Sara Mazzucato

Amyloidosis refers to a range of medical conditions in which misshapen proteins accumulate in various organs and tissues, forming insoluble fibrils. Cardiac amyloidosis is frequently linked to the buildup of misfolded transthyretin (TTR) or immunoglobulin ...

IEEE2023

Immediate effect of ankle exoskeleton on spatiotemporal parameters and center of pressure trajectory after stroke

Mohamed Bouri, Solaiman Shokur, Silvestro Micera, Mouhamed Zorkot

Gait impairments is a common condition in post-stroke subjects. We recently presented a wearable ankle exoskeleton called G-Exos, which showed that the device assisted in the ankle's dorsiflexion and inversion/reversion movements. The aim of the current pi ...

IEEE2023

Rapid low-cost hyperspectral imaging system for quantitative assessment of infantile hemangioma

Viktor Vorobev

Hemangioma, the predominant benign tumor occurring in infancy, exhibits a wide range of prognoses and associated outcomes. The accurate determination of prognosis through noninvasive imaging modalities holds essential importance in enabling effective perso ...

Wiley-V C H Verlag Gmbh2023

Prompting Large Language Models to Power Educational Chatbots

Denis Gillet, Sandy Ingram, Juan Carlos Farah, Fanny Kim-Lan Lasne

The recent rise in both popularity and performance of large language models has garnered considerable interest regarding their applicability to education. Technologies like ChatGPT, which can engage in human-like dialog, have already disrupted educational ...

Springer2023

Prediction of post-stroke motor recovery benefits from measures of sub-acute widespread network damages

Dimitri Nestor Alice Van De Ville, Elvira Pirondini, Maria Giulia Preti, Cyprien Alban Félicien Rivier

Rivier et al. report that global measures of brain connectivity estimated by introducing virtual lesions in healthy structural connectomes significantly increase the accuracy of motor recovery prediction in stroke patients when added to focal and clinical ...

OXFORD UNIV PRESS2023

Survey experiments on economic expectations

Andreas Fuster

In this chapter, we discuss field experiments in surveys that are conducted with the purpose of learning about expectation formation and the link between expectations and behavior. We begin by reviewing the rationale for conducting experiments within surve ...

Academic Press2023

Modeling tumor size dynamics based on real-world electronic health records and image data in advanced melanoma patients receiving immunotherapy

Olivier Michielin, Monia Guidi, Alexandre Wicky, Nadia Terranova, Daniel Abler, Federico Amato

The development of immune checkpoint inhibitors (ICIs) has revolutionized cancer therapy but only a fraction of patients benefits from this therapy. Model-informed drug development can be used to assess prognostic and predictive clinical factors or biomark ...

2023

Harnessing Rule-Based Chatbots to Support Teaching Python Programming Best Practices

Denis Gillet, Sandy Ingram, Adrian Christian Holzer, Juan Carlos Farah

In recent years, the use of chatbots in education has been driven by advances in natural language processing and the increasing availability of digital education platforms. Although the added value of educational chatbots appears promising, researchers hav ...

Springer2023

Arbitrary Decisions are a Hidden Cost of Differentially Private Training

Bogdan Kulynych, Carmela González Troncoso

Mechanisms used in privacy-preserving machine learning often aim to guarantee differential privacy (DP) during model training. Practical DP-ensuring training methods use randomization when fitting model parameters to privacy-sensitive data (e.g., adding Ga ...

Assoc Computing Machinery2023

Interventionist estimands in event history analysis

Matias Janvin

The presence of competing events, such as death, makes it challenging to define causal effects on recurrent outcomes. In this thesis, I formalize causal inference for recurrent events, with and without competing events. I define several causal estimands an ...

EPFL2023