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

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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 ...

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 ...

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 ...

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 ...

Systems and methods for monitoring penile tumescence are provided that overcome the drawbacks of previously known systems by providing a wearable formed of a flexible and elastic tube having a plurality of sensors disposed on or embedded within it, the wea ...

The dataset supporting 'Fiber pumps for wearable fluidic systems', published in Science in March 2023. In this work, we present a fluidic pump in the form of a flexible and stretchable tube. These tubes - or 'fiber pumps' - can generate significant fluidic ...

Background: Although digital mobility outcomes (DMOs) can be readily calculated from real-world data collected with wearable devices and ad-hoc algorithms, technical validation is still required. The aim of this paper is to comparatively assess and validat ...

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 ...

Counting the number of times a patient coughs per day is an essential biomarker in determining treatment efficacy for novel antitussive therapies and personalizing patient care. Automatic cough counting tools must provide accurate information, while runnin ...

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 ...

Head tracking combined with head movements have been shown to improve auditory externalization of a virtual sound source and contribute to the performance in localization. With certain technically constrained head-tracking algorithms, as can be found in we ...

ML-based edge devices may face memory and computational errors that affect applications' reliability and performance. These errors can be the result of particular working conditions (e.g., radiation areas in physical experiments or avionics) or could be th ...

Counting the number of times a patient coughs per day is an essential biomarker in determining treatment efficacy for novel antitussive therapies and personalizing patient care. There is a need for wearable devices that employ multimodal sensors to perform ...

The transition towards a human-centered indoor climate is beneficial from occupants’ thermal comfort and from an energy reduction perspective. However, achieving this goal requires the knowledge of the thermal state of individuals at the level of body part ...

Hyperdimensional (HD) computing is a novel approach to machine learning inspired by neuroscience, which uses vectors in a hyper-dimensional space to represent data and models. This approach has gained significant interest in recent years with applications ...

Long-term monitoring of real-life physical activity (PA) using wearable devices is increasingly used in clinical and epidemiological studies. The quality of the recorded data is an important issue, as unreliable data may negatively affect the outcome measu ...

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 ...

Wearable and unobtrusive monitoring and prediction of epileptic seizures has the potential to significantly increase the life quality of patients, but is still an unreached goal due to challenges of real-time detection and wearable devices design. Hyperdim ...

The growing needs for human healthcare have driven the development of wearable devices for monitoring the health status of an individual. Polymers represent a promising platform for such devices due to their ability to form an intimate contact between soft ...

While the task of automatically detecting eating events has been examined in prior work using various wearable devices, the use of smartphones as standalone devices to infer eating events remains an open issue. This paper proposes a framework that infers e ...

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

Chat with Graph Search

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

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

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

Intelligent Neural Interfaces: An Emerging Era in Neurotechnology

Tumescense monitoring system for diagnosing erectile dysfunction and methods of use

Research data supporting 'Fiber pumps for wearable fluidic systems'

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

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

A Multimodal Dataset for Automatic Edge-AI Cough Detection

Real-time Personalized Monitoring of Neurological Disorders on Wearable Systems

Effects of Head-Tracking Artefacts on Externalization and Localization in Azimuth With Binaural Wearable Devices

Hardware-Software co-design Methodologies for Edge AI Optimization

A Multimodal Dataset for Automatic Edge-AI Cough Detection

Toward contactless human thermal monitoring: A framework for Machine Learning-based human thermo-physiology modeling augmented with computer vision

Hyperdimensional computing for biosignal monitoring: Applications for epilepsy detection

Putting Temperature into the Equation: Development and Validation of Algorithms to Distinguish Non-Wearing from Inactivity and Sleep in Wearable Sensors

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

Exploration of Hyperdimensional Computing Strategies for Enhanced Learning on Epileptic Seizure Detection

Development of stencil lithography for stretchable interconnects

Sensing Eating Events in Context: A Smartphone-Only Approach