Deep Learning Enables Accurate Automatic Sleep Staging Based on Ambulatory Forehead EEG

Deep Learning Enables Accurate Automatic Sleep Staging Based on Ambulatory Forehead EEG

We have previously developed an ambulatory electrode set (AES) for the measurement of electroencephalography (EEG), electrooculography (EOG), and electromyography (EMG). The AES has been proven to be suitable for manual sleep staging and self-application in in- home polysomnography (PSG). To further...

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Bibliographic Details
Main Authors: Akseli Leino, Henri Korkalainen, Laura Kalevo, Sami Nikkonen, Samu Kainulainen, Alexander Ryan, Brett Duce, Kirsi Sipila, Jari Ahlberg, Johanna Sahlman, Tomi Miettinen, Susanna Westeren-Punnonen, Esa Mervaala, Juha Toyras, Sami Myllymaa, Timo Leppanen, Katja Myllymaa
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Ambulatory EEG
automatic scoring
deep learning
electroencephalography
sleep staging
Online Access:https://ieeexplore.ieee.org/document/9721838/

Internet

https://ieeexplore.ieee.org/document/9721838/

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