A deep learning-based algorithm for detection of cortical arousal during sleep

Abstract Study Objectives The frequency of cortical arousals is an indicator of sleep quality. Additionally, cortical arousals are used to identify hypopneic events. However, it is inconvenient to record electroencephalogram (EEG) data during home sleep testing. Fortunately, most cortical arousal ev...

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Veröffentlicht in:	Sleep (New York, N.Y.) N.Y.), 2020-12, Vol.43 (12), p.1
Hauptverfasser:	Li, Ao, Chen, Siteng, Quan, Stuart F, Powers, Linda S, Roveda, Janet M
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Analysis Arousal Atherosclerosis Big Data Approaches to Sleep and Circadian Rhythms Deep Learning Development and progression Electrocardiogram Electrocardiography Electroencephalography Machine learning Neural networks Physiology Polysomnography Sleep
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