Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium

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The Internet of Things (IoT) consists of physical objects and devices embedded with network connectivity, software, and sensors to collect and transmit data. The development of the Internet of Things (IoT) has led to various security and privacy issues, in ...

Idiopathic normal pressure hydrocephalus (iNPH), the leading cause of reversible dementia in older adults, is characterized by urinary incontinence, gait impairment, cognitive decline, and ventriculomegaly. Neuroradiological features rely on visual assessm ...

Purpose: This study aimed to evaluate the efficacy of the Chat Generative Pre-trained Transformer (ChatGPT) in guiding the need for invasive coronary angiography (ICA) in high-risk non-ST-elevation (NSTE) acute coronary syndrome (ACS) patients based on bot ...

A range of behavioral and contextual factors, including eating and drinking behavior, mood, social context, and other daily activities, can significantly impact an individual's quality of life and overall well-being. Therefore, inferring everyday life aspe ...

Integrating low-power wearable systems into routine health monitoring is an ongoing challenge. Recent advances in the computation capabilities of wearables make it possible to target complex scenarios by exploiting multiple biosignals and using high-perfor ...

This data set contains the data collected during the FNS project Green Piezo (Grant no. 179064) in association with the recent publication entitled “3D printing of customizable transient bioelectronics and sensors”. This work aims to study and demonstrate ...

Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions. Central to effective decision-making is the discipline of optimization, which seeks th ...

This paper offers a new algorithm to efficiently optimize scheduling decisions for dial-a-ride problems (DARPs), including problem variants considering electric and autonomous vehicles (e-ADARPs). The scheduling heuristic, based on linear programming theor ...

This thesis introduces spectroscopy-free Raman biosensing, which may find increasing use in the next generation of wearable devices for preventive healthcare. While wearables have made substantial advancements in detecting physical biomarkers, they have ye ...

We introduce an algorithm to reconstruct a mesh from discrete samples of a shape's Signed Distance Function (SDF). A simple geometric reinterpretation of the SDF lets us formulate the problem through a point cloud, from which a surface can be extracted wit ...

Integrating smart algorithms on neural devices presents significant opportunities for various brain disorders. In this paper, we review the latest advancements in the development of three categories of intelligent neural prostheses featuring embedded signa ...

The rapid development of wearable biomedical systems now enables real-time monitoring of electroencephalography (EEG) signals. Acquisition of these signals relies on electrodes. These systems must meet the design challenge of selecting an optimal set of el ...

Federated learning (FL) has recently emerged as a compelling machine learning paradigm, prioritizing the protection of privacy for training data. The increasing demand to address issues such as "the right to be forgotten" and combat data poisoning attacks ...

Polymer optical fibre (POFs) based wearable sensors have attracted a lot of attention in the field of healthcare and biomedical applications. They are in particular envision as the next generation of sensors for the continuous, real-time n ...

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 ...

The goal of this work is to use anisotropic adaptive finite elements for the numerical simulation of aluminium electrolysis. The anisotropic adaptive criteria are based on a posteriori error estimates derived for simplified problems. First, we consider an ...

Systems and apparatus are provided for using a non-invasively monitored uncalibrated pressure signal from a patient to compute cardiac output and other cardio-vascular parameters, thereby providing safe, effective, reliable and low cost monitoring of patie ...

Sweat secreted by the human eccrine sweat glands can provide valuable biomarker information during exercise. Real-time non-invasive biomarker recordings are therefore useful for evaluating the physiological conditions of an athlete such as their hydration ...

A smart wearable (SW) for collecting data on an integrity of a joint of a wearer, the wearable including a first frame (1) configured to be attached in proximity of the joint of the wearer, the frame (1) including an elastic sensor frame (3) having an open ...

We perform an error analysis of a fully discretised Streamline Upwind Petrov Galerkin Dynamical Low Rank (SUPG-DLR) method for random time-dependent advection-dominated problems. The time integration scheme has a splitting-like nature, allowing for potenti ...

Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium

Chattez avec Graph Search

GraphFedAI framework for DDoS attack detection in IoT systems using federated learning and graph based artificial intelligence

Idiopathic normal pressure hydrocephalus: A sulcal morphometry approach to brain phenotype and clinical response

Assessing the need for coronary angiography in high-risk non-ST-elevation acute coronary syndrome patients using artificial intelligence and computed tomography

Generalization and Personalization of Machine Learning for Multimodal Mobile Sensing in Everyday Life

M2SKD: Multi-to-Single Knowledge Distillation of Real-Time Epileptic Seizure Detection for Low-Power Wearable Systems

Dataset for '3D printing of customizable transient bioelectronics and sensors'

Reliable data-driven decision-making through optimal transport

A ride time-oriented scheduling algorithm for dial-a-ride problems

Toward Wearable Biosensing by Spectroscopy-free Raman Shift Detection and Soft Optofluidics

Reach For the Arcs: Reconstructing Surfaces from SDFs via Tangent Points

Intelligent Neural Interfaces: An Emerging Era in Neurotechnology

FETCH: A Fast and Efficient Technique for Channel Selection in EEG Wearable Systems

Fast-FedUL: A Training-Free Federated Unlearning with Provable Skew Resilience

Moulding and Microfluidic Wet Spinning of the Soft Polymer Optical Fibers for Sensory Applications

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

Adaptive Finite Elements with Large Aspect Ratio. Application to Aluminium Electrolysis

Apparatus for non-invasively computing cardio-vasculature parameters using morphology of uncalibrated pressure wave signal

Multisensing wearables for real-time monitoring of sweat electrolyte biomarkers during exercise and analysis on their correlation with core body temperature

A wearable to assess knee joint integrity using non-contact acoustic sensors

Error estimates for SUPG-stabilised Dynamical Low Rank Approximations