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A Deep Learning Method Approach for Sleep Stage Classification with EEG Spectrogram
The classification of sleep stages is an important process. However, this process is time-consuming, subjective, and error-prone. Many automated classification methods use electroencephalogram (EEG) signals for classification. These methods do not classify well enough and perform poorly in the N1 du...
Autores principales: | Li, Chengfan, Qi, Yueyu, Ding, Xuehai, Zhao, Junjuan, Sang, Tian, Lee, Matthew |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9141573/ https://www.ncbi.nlm.nih.gov/pubmed/35627856 http://dx.doi.org/10.3390/ijerph19106322 |
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