Electroencephalography (EEG) is immediate and sensitive to neurological changes
resulting from sleep stages and is considered a computing tool for understanding the …

The recommendations for identifying sleep stages based on the interpretation of
electrophysiological signals (electroencephalography [EEG], electro-oculography [EOG] …

Abstract Study Objectives New electroencephalogram (EEG) features became available for
use in polysomnography and have shown promise in early studies. They include a …

Quantification of sleep is important for the diagnosis of sleep disorders and sleep research.
However, the only widely accepted method to obtain sleep staging is by visual analysis of …

Sleep specialists often conduct manual sleep stage scoring by visually inspecting the
patient's neurophysiological signals collected at sleep labs. This is, generally, a very difficult …

We present a novel method for automatic sleep scoring based on single-channel EEG. We
introduce the use of a deep convolutional neural network (CNN) on raw EEG samples for …

Objective Sleep stage scoring is essential for diagnosing sleep disorders. Visual scoring of
sleep stages is very time-consuming and prone to human errors. In this work, we introduce …

Recent years have witnessed a surge in human sleep electroencephalography (EEG)
studies, employing increasingly sophisticated analysis strategies to relate …

Abstract Study Objective: To assess the performance of automatic sleep scoring software
(ASEEGA) based on a single EEG channel comparatively with manual scoring (2 experts) of …

An accurate home sleep study to assess electroencephalography (EEG)‐based sleep
stages and EEG power would be advantageous for both clinical and research purposes …