Machine‐learning‐derived sleep–wake staging from around‐the‐ear electroencephalogram outperforms manual scoring and actigraphy
Quantification of sleep is important for the diagnosis of sleep disorders and sleep research. However, the only widely accepted method to obtain sleep staging is by visual analysis of polysomnography (PSG), which is expensive and time consuming. Here, we investigate automated sleep scoring based on...
| Main Authors: | , , , , , , , , , , |
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| Format: | Journal article |
| Published: |
Wiley
2018
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