Jérôme Paul Rémy Thevenot

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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 ...

Continuous cough monitors can greatly benefit doctors in home monitoring and treatment of respiratory diseases. Although many works propose algorithms to automate this task, they suffer of poor data privacy and short-term monitoring. Edge-AI is a promising ...

Chronic cough disorders are widespread and challenging to assess because they rely on subjective patient questionnaires about cough frequency. Wearable devices running Machine Learning (ML) algorithms are promising for quantifying daily coughs, providing c ...

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 ...

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 ...

Jérôme Paul Rémy Thevenot

Chat with Graph Search

A Multimodal Dataset for Automatic Edge-AI Cough Detection

Cough-E: A multimodal, privacy-preserving cough detection algorithm for the edge

How to Count Coughs: An Event-Based Framework for Evaluating Automatic Cough Detection Algorithm Performance

A Multimodal Dataset for Automatic Edge-AI Cough Detection

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