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Sleep staging from electrocardiography and respiration with deep learning.

Sleep(2020)

Cited 50|Views4
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Abstract
Our results validate that ECG and respiratory effort provide substantial information about sleep stages in a large heterogeneous population. This opens new possibilities in sleep research and applications where electroencephalography is not readily available or may be infeasible.
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Key words
deep learning,electrocardiography,respiration,sleep stages
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