A Deep Learning Strategy for Automatic Sleep Staging Based on Two-Channel EEG Headband Data

A Deep Learning Strategy for Automatic Sleep Staging Based on Two-Channel EEG Headband Data

Sleep disturbances are common in Alzheimer’s disease and other neurodegenerative disorders, and together represent a potential therapeutic target for disease modification. A major barrier for studying sleep in patients with dementia is the requirement for overnight polysomnography (PSG) to achieve f...

Deskribapen osoa

Xehetasun bibliografikoak
Egile Nagusiak: Amelia A. Casciola, Sebastiano K. Carlucci, Brianne A. Kent, Amanda M. Punch, Michael A. Muszynski, Daniel Zhou, Alireza Kazemi, Maryam S. Mirian, Jason Valerio, Martin J. McKeown, Haakon B. Nygaard
Formatua: Artikulua
Hizkuntza:English
Argitaratua: MDPI AG 2021-05-01
Saila:Sensors
Gaiak:
deep learning
EEG headband
sleep staging
machine learning
neurodegenerative disease
sleep
Sarrera elektronikoa:https://www.mdpi.com/1424-8220/21/10/3316

Internet

https://www.mdpi.com/1424-8220/21/10/3316

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