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Optimal Depth of Discharge for Electric Batteries with Robust Capacity-Shrinkage Estimator

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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

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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

Self-Aware Machine Learning for Chronic Pathology Monitoring on Wearable Devices

Farnaz Forooghifar

Remote health monitoring has attracted a lot of attention over the past decades to provide the opportunity for early detection of pathological health conditions. This early detection improves the quality of life for the patients and significantly reduces t ...

EPFL2022

Photocured Nanocellulose Composites: Recent Advances

Yves Leterrier, Aigoul Schreier, Mohammed Arif Poothanari, Julien Bras

This perspective gives an overview of recent progress in thefield of photocured polymer composites based on variousforms of nanocelluloses, with a focus on cellulose nanofibrils. The manufacturing processes and performances of these nanocellulosecomposites ...

AMER CHEMICAL SOC2022

MBioTracker: Multimodal Self-Aware Bio-Monitoring Wearable System for Online Workload Detection

David Atienza Alonso, Adriana Arza Valdes, Fabio Isidoro Tiberio Dell'Agnola, Una Pale, Rodrigo Mariño Andrés

Cognitive workload affects operators' performance principally in high-risk or time-demanding situations and when multitasking is required. An online cognitive workload monitoring system can provide valuable inputs to decision-making instances, such as the ...

2021

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Objective: Cognitive workload monitoring (CWM)can enhance human-machine interaction by supporting task execution assistance considering the operator’s cognitive state. Therefore, we propose a machine learning design methodology and a data processing strate ...

2021

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Epilepsy affects more than 50 million people and ranks among the most common neurological diseases worldwide. Despite advances in treatment, one-third of patients still suffer from refractory epilepsy. Wearable devices for real-time patient monitoring can ...

2020

The paper assesses the influence of equivalent circuit battery models on the optimal design of the propulsion system of an energy-autonomous Hyperloop capsule. By knowing a pre-determined payload to be transported along pre-determined trajectories, the pro ...

IEEE2020

Whether it is for personal use or for medical application, wearable sensors are becoming more and more widespread. This is the industry answer to two parallel trends. First, the public show a wish to collect data about their own lifestyle. This rather new ...

EPFL2019

Event-Triggered Sensing for High-Quality and Low-Power Cardiovascular Monitoring Systems

David Atienza Alonso, Amir Aminifar, Tomas Teijeiro Campo, Grégoire Casimir Joseph Surrel

In the context of wearable medical systems, resources are scarce while performance requirements are high. Traditional sampling strategies create large amounts of data, which hinders the device's battery lifetime. However, energy savings are possible when r ...

2019