Sleep stage classification is crucial in diagnosing sleep disorders and monitoring treatment
effectiveness, yet it is inconvenient, requiring many electrodes and labor-intensive …

Sleep is vital to our daily activity. Lack of proper sleep can impair functionality and overall
health. While stress is known for its detrimental impact on sleep quality, the precise effect of …

Background: Sleep stage classification is a crucial process for the diagnosis of sleep or
sleep-related diseases. Currently, this process is based on manual electroencephalogram …

In this work, an efficient automated new approach for sleep stage identification based on the
new standard of the American academy of sleep medicine (AASM) is presented. The …

This paper proposes a deep learning model, named DeepSleepNet, for automatic sleep
stage scoring based on raw single-channelEEG. Most of the existing methods rely on hand …

An automatic sleep monitoring system is a prime requirement in order to minimize analysts'
workload of visually inspecting large-scale data for sleep scoring and to improve the …

This paper introduced an end-to-end mixed deep learning model for automatic sleep
analysis based on the EEG signal. Unlike some existing machine learning models for EEG …

Elimination of intra-artifacts in EEG has been overlooked in most of the existing sleep
staging systems, especially in deep learning-based approaches. Whether intra-artifacts …

Quality sleep is one of the integral parts of the human body, which gives proper rest to the
body. It directly promotes and supports maintaining good health, both physically and …

Sleep disorder is a serious public health problem. Unobtrusive home sleep quality
monitoring system can better open the way of sleep disorder‐related diseases screening …