![]() ![]() It is estimated that around one-third of the general population in the United States are affected by insufficient sleep 8. Inadequate sleep is often associated with negative outcomes, including obesity 2, irritability 2, 3, cardiovascular dysfunction 4, hypotension 5, impaired memory 6 and depression 7. ![]() ![]() Sleep is important for our health and quality of life 1. This computational tool would greatly empower the scoring process in clinical settings and accelerate studies on the impact of arousals. Our algorithm enables fast and accurate delineation of sleep arousal events at the speed of 10 seconds per sleep recording. We created an augmentation strategy by randomly swapping similar physiological channels, which notably improved the prediction accuracy. Leveraging a specific architecture that ‘translates’ input polysomnographic signals to sleep arousal labels, this algorithm ranked first in the “You Snooze, You Win” PhysioNet Challenge. Here we present a deep learning approach for automatically segmenting sleep arousal regions based on polysomnographic recordings. Currently, sleep arousals are mainly annotated by human experts through looking at 30-second epochs (recorded pages) manually, which requires considerable time and effort. Excessive sleep arousals are associated with symptoms such as sympathetic activation, non-restorative sleep, and daytime sleepiness. Sleep arousals are transient periods of wakefulness punctuated into sleep. ![]()
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