Extracting continuous sleep depth from EEG data without machine learning
The human sleep-cycle has been divided into discrete sleep stages that can be recognized in electroencephalographic (EEG) and other bio-signals by trained specialists or machine learning systems. It is however unclear whether these human-defined stages can be re-discovered with unsupervised methods...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-05-01
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| Series: | Neurobiology of Sleep and Circadian Rhythms |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2451994423000093 |