Sleep stage scoring is a challenging task. Most of existing sleep stage classification
approaches rely on analysing electroencephalography (EEG) signals in time or frequency …

Abstract Background and Objective Sleep scoring is important in sleep research because
any errors in the scoring of the patient's sleep electroencephalography (EEG) recordings …

The electroencephalogram (EEG) signals are commonly used in diagnosing and treating
sleep disorders. Many existing methods for sleep stages classification mainly depend on the …

Manual staging of sleep data from EEG signals is time consuming, error prone, and resource
intensive. These limitations lead to continuous interests of researchers and clinicians toward …

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 …

Effective sleep monitoring from electroencephalogram (EEG) signals is meaningful for the
diagnosis of sleep disorders, such as sleep Apnea, Insomnia, Snoring, Sleep …

Sleep scoring is one of the primary tasks for the classification of sleep stages in
Electroencephalogram (EEG) signals. Manual visual scoring of sleep stages is time …

Since speed of classification is important to real-time applications, this study proposed fast
classification of sleep and wake stages using a single electroencephalograph (EEG) …

Background and objective: Proper scoring of sleep stages can give clinical information on
diagnosing patients with sleep disorders. Since traditional visual scoring of the entire sleep …

Feature extraction from physiological signals of EEG (electroencephalogram) is an essential
part for sleep staging. In this study, multidomain feature extraction was investigated based …