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A Multimodal Dataset for Automatic Edge-AI Cough Detection

Publications associées (24)

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

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 ...

EPFL2024

A Multimodal Dataset for Automatic Edge-AI Cough Detection

David Atienza Alonso, Tomas Teijeiro Campo, Lara Orlandic, Jérôme Paul Rémy Thevenot

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 ...

New York2023

A semi-supervised algorithm for improving the consistency of crowdsourced datasets: The COVID-19 case study on respiratory disorder classification

David Atienza Alonso, Tomas Teijeiro Campo, Lara Orlandic

Background and Objective: Cough audio signal classification is a potentially useful tool in screening for respiratory disorders, such as COVID-19. Since it is dangerous to collect data from patients with contagious diseases, many research teams have turned ...

2023

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

Kamiar Aminian, Anisoara Ionescu, Abolfazl Soltani, Francesca Salis

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 ...

BioMed Central2023

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

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

Kamiar Aminian, David Atienza Alonso, Jérôme Paul Rémy Thevenot

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 ...

2023

Hardware-Software co-design Methodologies for Edge AI Optimization

Flavio Ponzina

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 ...

EPFL2023

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

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

Kamiar Aminian, Anisoara Ionescu, Sara Pagnamenta

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 ...

MDPI2022

Towards real-world biomechanical analysis of performance and functional capacity using wearable sensors

Salil Apte

Today, wearable heart rate monitors are an integral part of runners' training sessions, with heart rate data routinely used to assess effort intensity and stress on the body. As athletes translate their physical capacity into performance on the field throu ...

EPFL2022