Optimizing automated sleep stage scoring of 5-s mini-epochs: a transfer learning study
After optimization, U-Sleep performance in mini-epochs matched the high performance levels previously reported in both human and automated 30-second epoch scoring. This demonstrates the feasibility of precise, automated high resolution sleep staging. Future work should include external validation and application to full-night recordings.
Authors
- Louise Frøstrup Follin
- Berit Hjelde Hansen (ORCID: https://orcid.org/0000-0002-5988-6817)
- Hilde T Juvodden (ORCID: https://orcid.org/0000-0001-6796-7177)
- Stine Knudsen (ORCID: https://orcid.org/0000-0003-1946-1125)
- Mathias Perslev (ORCID: https://orcid.org/0000-0002-0358-4692)
- Julie Anja Engelhard Christensen (ORCID: https://orcid.org/0000-0003-4225-3359)
- Janita Vevelstad
- Rannveig Viste (ORCID: https://orcid.org/0000-0002-7475-2999)
- Tobias Kaufmann (ORCID: https://orcid.org/0000-0002-4003-1018)
- Alexander Neergaard Zahid (ORCID: https://orcid.org/0000-0001-6881-9766)
Institutions
- Oslo University Hospital (NO)
- Lynn University (US)
- University of Oslo (NO)
- Rigshospitalet (DK)
- German Center for Infection Research (DE)
- Precision for Medicine (United States) (US)
- Lyngsø Marine (Denmark) (DK)
- University of Tübingen (DE)
- Technical University of Denmark (DK)
Publication Details
- Journal
- SLEEP
- Published
- 2025-12-11
- DOI
- https://doi.org/10.1093/sleep/zsaf393
- Citations
- 1
- Primary Topic
- Sleep and Wakefulness Research
- Type
- article
- Field-Weighted Citation Impact
- 1.43
Funders
- Helse- og Omsorgsdepartementet
- Lundbeckfonden
- H. Lundbeck A/S
- Helse Sør-Øst RHF