Sleep Arousal Detection
4 papers with code • 2 benchmarks • 1 datasets
Sleep arousal is a kind of EEG events happened during octurnal sleep. Too many arousals will contribute to many health problem, like daytime sleepiness, memory loss, diabetes, etc. Some research take it as a kind of sleep deprivation.
Benchmarks
These leaderboards are used to track progress in Sleep Arousal Detection
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
|||||
|
MESA
Most implemented papers
DOSED: a deep learning approach to detect multiple sleep micro-events in EEG signal
The proposed approach, applied here on sleep related micro-architecture events, is inspired by object detectors developed for computer vision such as YOLO and SSD.
Deepsleep: Fast and Accurate Delineation of Sleep Arousals at Millisecond Resolution by Deep Learning
GuanLab/DeepSleep
•
•
Lancet 2019
Background: Sleep arousals are transient periods of wakefulness punctuated into sleep.
DeepSleep 2.0: Automated Sleep Arousal Segmentation via Deep Learning
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 PhysioNet Computing Challenge.
State-of-the-art sleep arousal detection evaluated on a comprehensive clinical dataset
sleep-is-all-you-need/arousaldetector
•
•
Scientific Reports 2024
Therefore, we conclude that state-of-the-art arousal detection on our clinical data is possible with our model architecture.
