MetaWearS
Meta-learning framework for few-shot adaptation in wearable health monitoring.
Meta-learning framework for few-shot adaptation in wearable health monitoring. Pre-trains on large datasets with prototypical network structure; fine-tunes on few shots per user. Lightweight update mechanism conserves battery. Provides code, Jupyter notebooks, and hardware implementation details.
Deep Neural NetworksInternet of ThingsMedicalTime SeriesWearable
- Technical
- Source code: Lab Github
- Last commit: 2026-01-10
The Embedded Systems Laboratory (ESL) is part of the Institute of Electrical Engineering at EPFL, and focuses on the definition of system-level multi-objective design methods, optimization methodologies and tools for high-performance embedded systems and nano-scale Multi-Processor System-on-Chip (MPSoC) architectures targeting the Internet-of-Things (IoT) Era.
This page was last edited on 2026-03-03.
This page was last edited on 2026-03-03.