7 citations · 12 across the 5 of their papers we have counts for
5 papers
Why ML-based cough models do not generalize: a systematic cross-dataset evaluation for tuberculosis screening
Wensi Zhang, Tomas Teijeiro, Jérôme Thevenot +1
Cough acoustics are promising for non-invasive tuberculosis (TB) screening, yet whether machine learning (ML) models capture disease-related acoustics or artifacts of data collecti…
VersaPants: A Loose-Fitting Textile Capacitive Sensing System for Lower-Body Motion Capture
Deniz Kasap, Taraneh Aminosharieh Najafi, Jérôme Paul Rémy Thevenot +3
We present VersaPants, the first loose-fitting, textile-based capacitive sensing system for lower-body motion capture, built on the open-hardware VersaSens platform. By integrating…
Cough-E: A multimodal, privacy-preserving cough detection algorithm for the edge
Stefano Albini, Lara Orlandic, Jonathan Dan +4
Continuous cough monitors can greatly aid doctors in home monitoring and treatment of respiratory diseases. Although many algorithms have been proposed, they still face limitations…
How to Count Coughs: An Event-Based Framework for Evaluating Automatic Cough Detection Algorithm Performance
Lara Orlandic, Jonathan Dan, Jerome Thevenot +3
Chronic cough disorders are widespread and challenging to assess because they rely on subjective patient questionnaires about cough frequency. Wearable devices running Machine Lear…
Acoustical Features as Knee Health Biomarkers: A Critical Analysis
Christodoulos Kechris, Jerome Thevenot, Tomas Teijeiro +3
Acoustical knee health assessment has long promised an alternative to clinically available medical imaging tools, but this modality has yet to be adopted in medical practice. The f…