RobustSleepNet: Transfer Learning for Automated Sleep Staging at Scale

• Published in: IEEE transactions on neural systems and rehabilitation engineering Vol. 29; pp. 1441 - 1451
• Main Authors: Guillot, Antoine, Thorey, Valentin
• Format: Journal Article
• Language: English
• Published: New York IEEE 2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Automated sleep stage classification; Brain modeling; Classification; Datasets; Deep learning; Demographics; Demography; EEG; Electroencephalography; Electromyography; Electrooculography; Human performance; Inspection; Machine learning; PSG; Sleep; Sleep disorders; Training; Transfer learning; Visual signals

Sleep disorder diagnosis relies on the analysis of polysomnography (PSG) records. As a preliminary step of this examination, sleep stages are systematically determined. In practice, sleep stage classification relies on the visual inspection of 30-second epochs of polysomnography signals. Numerous au...