A hybrid deep learning framework for sleep stage classification using single channel EEG signals
Abstract Background For the diagnosis of sleep disorders and analysis of sleep habits, the precise identification of sleep stages is crucial. Although manual scoring methods are common, the work process can be laborious, and it inherently involves variability. To get over these limitations, this res...
Gorde:
| Egile Nagusiak: | , , , , , |
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| Formatua: | Artigo |
| Hizkuntza: | Inglês |
| Argitaratua: |
Springer
2026-03-01
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| Saila: | Discover Artificial Intelligence |
| Gaiak: | |
| Sarrera elektronikoa: | https://doi.org/10.1007/s44163-026-01092-8 |
| Etiketak: |
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