Automated sleep disorder detection is challenging because physiological symptoms can
vary widely. These variations make it difficult to create effective sleep disorder detection …

We present a new approach to classifying the sleep stage that incorporates a
computationally inexpensive method based on permutations for channel selection and takes …

Sleep apnea syndrome (SAS) is a disorder in which respiratory airflow frequently stops
during sleep. Alterations in electroencephalogram (EEG) signal are one of the physiological …

Early illness diagnosis and prediction are important goals in healthcare in order to offer
timely preventive measures. The best, least invasive, and most reliable way for identifying …

Sleep Apnea is a sleep disorder which causes stop in breathing for a short duration of time
that happens to human beings and animals during sleep. Electroencephalogram (EEG) …

Sleep apnea, a severe sleep disorder, is a clinically complicated disease that requires timely
diagnosis for proper treatment. In this paper, an automated deep learning-based approach …

Sleep apnea, a serious sleep disorder affecting a large population, causes disruptions in
breathing during sleep. In this paper, an automatic apnea detection scheme is proposed …

Purpose This study evaluated a novel approach for diagnosis and classification of
obstructive sleep apnea (OSA), called Obstructive Sleep Apnea Smart System (OSASS) …

Sleep apnea is a sleep disorder that can cause serious health problems. An Artificial Neural
Network classifier to detect sleep apnea has been presented in this paper by utilizing the …

Sleep apnea is a slee** disorder, which adversely affects the health of humans. The
diagnosis of sleep apnea is possible by the detection of apnea events using …