The scoring of sleep stages is one of the essential tasks in sleep analysis. Since a manual
procedure requires considerable human and financial resources, and incorporates some …

Automatic sleep stage classification plays an essential role in sleep quality measurement
and sleep disorder diagnosis. Although many approaches have been developed, most use …

Over the last few years, human activity recognition (HAR) has drawn increasing interest from
the scientific community. This attention is mainly attributable to the proliferation of wearable …

Sleep staging has a very important role in diagnosing patients with sleep disorders. In
general, this task is very time-consuming for physicians to perform. Deep learning shows …

The past few years have witnessed a remarkable advance in deep learning for EEG-based
sleep stage classification (SSC). However, the success of these models is attributed to …

The complexity of sleep disorder diagnosis continuously increases the clinical requirement
for simultaneous measurement of sleep arousal and sleep stage, which, however, has not …

Sleep staging is a standard diagnostic method for evaluating sleep quality, which would
enable early diagnosis of sleep disorders as well as mental diseases. Polysomnography …

Electroencephalography (EEG) is often used to evaluate several types of neurological brain
disorders because of its noninvasive and high temporal resolution. In contrast to …

This work attempts to design an effective sleep staging system, making the best use of the
available signals, strategies, and features in the literature. It must not only perform well on …

Clinical sleep diagnosis traditionally relies on polysomnography (PSG) and expert manual
classification of sleep stages. Recent advancements in deep learning have shown promise …