Sleep is a vital process of our daily life as we roughly spend one-third of our lives asleep. In
order to evaluate sleep quality and potential sleep disorders, sleep stage classification is a …

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 …

Background and objective In recent years, several automatic sleep stage classification
methods based on convolutional neural networks (CNN) by learning hierarchical feature …

We propose in this work a feature learning approach using deep bidirectional recurrent
neural networks (RNNs) with attention mechanism for single-channel automatic sleep stage …

Background and objective: This paper presents a new framework for automatic classification
of sleep stages using a deep learning algorithm from single-channel EEG signals. Each …

Sleep stage scoring is fundamental for the examination and analysis of sleep problems.
Sleep experts score sleep by analyzing brain activity, muscle activity, and eye activity …

Humans spend about one-third of their time in sleep. Sleep is closely related to human
physical and mental health and is a very important life activity. Automatic sleep stage …

Automatic sleep stage mymargin classification is of great importance to measure sleep
quality. In this paper, we propose a novel attention-based deep learning architecture called …

Objective. Computerized classification of sleep stages based on single-lead
electroencephalography (EEG) signals is important, but still challenging. In this paper, we …

Electroencephalogram (EEG) is a common base signal used to monitor brain activities and
diagnose sleep disorders. Manual sleep stage scoring is a time-consuming task for sleep …