Micro SleepNet: efficient deep learning model for mobile terminal real-time sleep staging

The real-time sleep staging algorithm that can perform inference on mobile devices without burden is a prerequisite for closed-loop sleep modulation. However, current deep learning sleep staging models have poor real-time efficiency and redundant parameters. We propose a lightweight and high-perform...

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Detalles Bibliográficos
Autores principales: Liu, Guisong, Wei, Guoliang, Sun, Shuqing, Mao, Dandan, Zhang, Jiansong, Zhao, Dechun, Tian, Xuelong, Wang, Xing, Chen, Nanxi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10416229/
https://www.ncbi.nlm.nih.gov/pubmed/37575302
http://dx.doi.org/10.3389/fnins.2023.1218072

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10416229/
https://www.ncbi.nlm.nih.gov/pubmed/37575302
http://dx.doi.org/10.3389/fnins.2023.1218072

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