Abstract

Sleep is an important part of the body's recuperation and energy accumulation, and the quality of sleep also has a significant impact on people's physical and mental state during the epidemic of Coronavirus Disease. It has attracted increasing attention on how to improve the quality of sleep and reduce the impact of sleep-related diseases on health during the Epidemic of Coronavirus Disease. The electroencephalogram (EEG) signals collected during sleep belong to spontaneous EEG signals. Spontaneous sleep EEG signals can reflect the body's changes, which is also an basis for diagnosis and treatment of related diseases. Therefore, the establishment of an effective model for classifying sleep EEG signals is an important auxiliary tool for evaluating sleep quality, diagnosing and treating sleep-related diseases.

How to Cite
E, JINMING CAO, BIN ZHAO, Mingzhe. Deep Learning for Classification of Sleep EEG Data during the Epidemic of Coronavirus Disease. Global Journal of Medical Research, [S.l.], nov. 2020. ISSN 2249-4618. Available at: <https://medicalresearchjournal.org/index.php/GJMR/article/view/2305>. Date accessed: 15 may 2021.


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