Activity counts measure attention, not model quality. Missing counts are unknown. Publication status follows the linked source; a listed venue alone does not confirm peer review.
- License
- MIT
- Signals
- ECG, EEG
- Type
- Task model
- Form factor
- Not reported
- Parameters
- Not reported
- Architecture
- Not reported
- Venue
- Not reported
- Year
- Not reported
- arXiv
- Not reported
- DOI
- Not reported
- Weights
- Not released
- Licence
- MIT (opens in a new tab)
- Caveats
- Not reported
- Datasets
- Not reported
- Added
- Oct 19, 2026
- Updated
- Oct 19, 2026
Original description
This repository contains the source code for the paper "MetaWearS: A Shortcut in Wearable Systems Lifecycle with Only a Few Shots".
Wearable systems provide continuous health monitoring and can lead to early detection of potential health issues. However, the lifecycle of wearable systems faces several challenges. First, effective model training for new wearable devices requires substantial labeled data from various subjects collected directly by the wearable. Second, subsequent model updates require further extensive labeled data for retraining. Finally, frequent model updating on the wearable device can decrease the battery life in long-term data monitoring.
Verbatim fromGitHub· Description from the repository README; licence: MIT
How it works
- Inputs
- ECG, EEG
- Approach
- code release · no weights
Datasets
Papers· 1
Cite
APA
MetaWearS. (n.d.).
BibTeX
@misc{metawearsmetawears,
title = {{MetaWearS}}
}Built from the hub record. Check it against the publisher before submitting.
History
Added to the ChatPPG research hub