Classification of sleep stages is one of the most important diagnostic approaches for a
variety of sleep-related disorders. Electroencephalography (EEG) is regarded as a powerful …

To evaluate sleep quality, it is necessary to monitor overnight sleep duration. However,
sleep monitoring typically requires more than 7 hours, which can be inefficient in termxs of …

Sleep disorder is a symptom of many neurological diseases that may significantly affect the
quality of daily life. Traditional methods are time-consuming and involve the manual scoring …

Sleep stage classification plays a crucial role in diagnosing sleep disorders and
understanding sleep physiology. In recent years, automated models based on machine …

Quality sleep plays a vital role in living beings as it contributes extensively to the healing
process and the removal of waste products from the body. Poor sleep may lead to …

METHODS: 8 normal healthy male volunteers aged 18–36 years (mean= 26.5) performed a
visuomotor tracking task while EEG, facial video, and tracking behavior were recorded. EEG …

As sleep disorders are becoming more prevalent there is an urgent need to classify sleep
stages in a less disturbing way. In particular, sleep-stage classification using simple sensors …

Sleep stage classification is important to accurately predict and diagnose patients with sleep
disorders. Though various deep learning approaches have been implemented to classify …

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 …

Classification of sleep stages is important for diagnosis and treatment of sleep disorder.
Manual classification performed by sleep experts is burdensome and time-consuming. This …