Real-time classification technique for early detection and prevention of myocardial infarction on wearable devices

Publications associées (28)

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Real-time Personalized Monitoring of Neurological Disorders on Wearable Systems

Renato Zanetti

The terminology of neurological disorders encompasses a range of serious illnesses (e.g., epilepsy, Alzheimer's disease) leading to morbidity, disability, and stigma. Epilepsy alone affects over 50 million people worldwide, and these figures are rising as ...

EPFL2023

An Error-Based Approximation Sensing Circuit for Event-Triggered Low-Power Wearable Sensors

David Atienza Alonso, Alexandre Sébastien Julien Levisse, Tomas Teijeiro Campo, Silvio Zanoli, Flavio Ponzina

Event-based sensors have the potential to optimize energy consumption at every stage in the signal processing pipeline, including data acquisition, transmission, processing, and storage. However, almost all state-of-the-art systems are still built upon th ...

2023

Performance evaluation and the implementation of the turbocharger, fuel cell, and battery in Unmanned Aerial Vehicles (UAVs)

Jan Van Herle, Hossein Pourrahmani

The current study evaluates integrating fuel cell technology into the batteries as an alternative for internal combustion engines (ICEs) for Unmanned Aerial Vehicles (UAV). To further improve the performance of the UAV, a turbocharger is also integrated to ...

Elsevier2023

Zinc carboxylate optimization strategy for extending Al-air battery system's lifetime

Andreas Züttel, Thi Ha My Pham, Liping Zhong, Manhui Wei

Although Al-air batteries are expected to be the candidates for energy conversion systems in renewable energy market due to the higher energy density, richer reserves, and lighter mass of Al metal, the anode self-discharge is seen as a notorious issue that ...

ELSEVIER SCI LTD2023

Towards Robust Monitoring of the Laser Powder Bed Fusion Process based on Acoustic Emission combined with Machine Learning Solutions

Rita Drissi Daoudi

Laser Powder Bed Fusion (LPBF) is an Additive Manufacturing (AM) process consolidating parts layer by layer, from a metallic powder bed. It allows no limitation in terms of geometry and is therefore of particular interest to various industries. Metallic LP ...

EPFL2023

On double-descent in uncertainty quantification in overparametrized models

Florent Gérard Krzakala, Lenka Zdeborová, Lucas Andry Clarte, Bruno Loureiro, Bruno Loureiro

Uncertainty quantification is a central challenge in reliable and trustworthy machine learning. Naive measures such as last-layer scores are well-known to yield overconfident estimates in the context of overparametrized neural networks. Several methods, ra ...

PMLR Proceedings of Machine Learning Research2023

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Florent Gérard Krzakala, Lenka Zdeborová, Hugo Chao Cui

We consider the problem of learning a target function corresponding to a deep, extensive-width, non-linear neural network with random Gaussian weights. We consider the asymptotic limit where the number of samples, the input dimension and the network width ...

2023

Ageing-aware battery discharge prediction with deep learning

Olga Fink, Luca Biggio

Electrochemical batteries are ubiquitous devices in our society. When employed in mission-critical applications, the ability to precisely predict their end-of-discharge under highly variable operating conditions is of paramount importance in order to suppo ...

ELSEVIER SCI LTD2023

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

Operando Electrochemical Liquid Cell Scanning Transmission Electron Microscopy Investigation of the Growth and Evolution of the Mosaic Solid Electrolyte Interphase for Lithium-Ion Batteries

Corsin Battaglia, Rolf Erni

The solid electrolyte interphase (SEI) is a key component of a lithium-ion battery forming during the first few dischage/charge cycles at the interface between the anode and the electrolyte. The SEI passivates the anode-electrolyte interface by inhibiting ...

Amer Chemical Soc2023

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