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 …

Multiple types of sleep arousal account for a large proportion of the causes of sleep
disorders. The detection of sleep arousals is very important for diagnosing sleep disorders …

Poor-quality sleep substantially diminishes the overall quality of life. It has been shown that
sleep arousal serves as a good indicator for scoring sleep quality. However, patients are …

DeepSleep 2.0 is a compact version of DeepSleep, a state-of-the-art, U-Net-inspired, fully
convolutional deep neural network, which achieved the highest unofficial score in the 2018 …

Objective. Sleep is a critical physiological process that plays a vital role in maintaining
physical and mental health. Accurate detection of arousals and sleep stages is essential for …

Introduction Detecting arousal events during sleep is a challenging, time‐consuming, and
costly process that requires neurology knowledge. Even though similar automated systems …

Purpose Sleep arousal detection is an important factor to monitor the sleep disorder.
Design/methodology/approach Thus, a unique n th layer one-dimensional (1D) …

Sleep is a natural state of reduced consciousness and physical activity that is crucial for the
body's circadian rhythm and various physiological processes. Sleep disordered breathing …

Sleep is crucial for overall health and well-being. Analyzing sleep stages and the frequency
of arousal can enhance our understanding of sleep quality and help protect individuals' …

Sleep arousal, a type of sleep disorder, occurs when one wakes up and then goes back to
sleep. It is crucial to assess the frequency and duration of sleep arousals to determine sleep …