Deep Learning for Pediatric Sleep Staging From Photoplethysmography: A Transfer Learning Approach From Adults to Children
This research establishes a new state-of-the-art performance for the task of sleep staging in children using raw PPG. The findings underscore the value of transfer learning from the adults to children domain. However, the reduced performance in children under 5 suggests the need for further research and additional datasets covering a broader pediatric age range to fully address generalization limitations.
Authors
- Riva Tauman (ORCID: https://orcid.org/0000-0002-6574-3601)
- Joachim A. Behar (ORCID: https://orcid.org/0000-0001-5956-7034)
- Alissa Tabakhov
- Sharon Haimov
Institutions
- Tel Aviv University (IL)
- Technion – Israel Institute of Technology (IL)
- Tel Aviv Sourasky Medical Center (IL)
Publication Details
- Journal
- IEEE Transactions on Biomedical Engineering
- Published
- 2024-09-27
- DOI
- https://doi.org/10.1109/tbme.2024.3470534
- Citations
- 3
- Primary Topic
- Obstructive Sleep Apnea Research
- Type
- article
- Field-Weighted Citation Impact
- 0.98