A deep transfer learning approach for wearable sleep stage classification with photoplethysmography
Abstract Unobtrusive home sleep monitoring using wrist-worn wearable photoplethysmography (PPG) could open the way for better sleep disorder screening and health monitoring. However, PPG is rarely included in large sleep studies with gold-standard sleep annotation from polysomnography. Therefore, tr...
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Autores principales: | , , , , , , , |
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Formato: | article |
Lenguaje: | EN |
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Nature Portfolio
2021
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Acceso en línea: | https://doaj.org/article/fec60914d8ef48c2a357f505610bfa45 |
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