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 …

With the increase in biosensors and data collection devices in the healthcare industry,
artificial intelligence and machine learning have attracted much attention in recent years. In …

Obstructive sleep apnea (OSA) is a sleep breathing disorder that can seriously affect the
health of patients. The manual diagnostic of OSA through the Polysomnography (PSG) …

Sleep relaxes and rests the body by slowing down the metabolism, making us physically
stronger and fitter when we wake up. However, in a sleep disorder that may occur in …

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

For real-world automatic sleep-stage classification tasks, various existing deep learning-
based models are biased toward the majority with a high proportion. Because of the unique …

Sleep stage classification plays a pivotal role in predicting and diagnosing numerous health
issues from human sleep data. Manual sleep staging requires human expertise, which is …

Deep learning has achieved unprecedented success in sleep stage classification tasks,
which starts to pave the way for potential real-world applications. However, due to its …

Sleep staging via electroencephalogram is essential for determining the quality of sleep.
Manual sleep staging is expensive and time-consuming. Recently, many deep learning …

Sleep is crucial for human health. Automatic sleep stage classification based on
polysomnography (PSG) is meaningful for the diagnosis of sleep diseases, which has …