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

7 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

eess.SP2025★ 1 cited

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…

eess.SP2024

Enabling Efficient Wearables: An Analysis of Low-Power Microcontrollers for Biomedical Applications

Dimitrios Samakovlis, Stefano Albini, Rubén Rodríguez Álvarez +4

Breakthroughs in ultra-low-power chip technology are transforming biomedical wearables, making it possible to monitor patients in real time with devices operating on mere μW. Altho…

eess.AS2024★ 7 cited

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…

cs.LG2024★ 1 cited

MetaWearS: A Shortcut in Wearable Systems Lifecycle with Only a Few Shots

Alireza Amirshahi, Maedeh H. Toosi, Siamak Mohammadi +5

Wearable systems provide continuous health monitoring and can lead to early detection of potential health issues. However, the lifecycle of wearable systems faces several challenge…

cs.LG2024

BiomedBench: A benchmark suite of TinyML biomedical applications for low-power wearables

Dimitrios Samakovlis, Stefano Albini, Rubén Rodríguez Álvarez +4

The design of low-power wearables for the biomedical domain has received a lot of attention in recent decades, as technological advances in chip manufacturing have allowed real-tim…