AIMC Topic: Sleep

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Interactive Sleep Stage Labelling Tool For Diagnosing Sleep Disorder Using Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Traditional manual scoring of the entire sleep for diagnosis of sleep disorders is highly time-consuming and dependent to experts experience. Thus, automatic methods based on electrooculography (EOG) analysis have been increasingly attracted attentio...

Multichannel Sleep Stage Classification and Transfer Learning using Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Current sleep medicine relies on the supervised analysis of polysomnographic measurements, comprising amongst others electroencephalogram (EEG), electromyogram (EMG), and electrooculogram (EOG) signals. Convolutional neural networks (CNN) provide an ...

Synaptic Mechanisms of Memory Consolidation during Sleep Slow Oscillations.

The Journal of neuroscience : the official journal of the Society for Neuroscience
UNLABELLED: Sleep is critical for regulation of synaptic efficacy, memories, and learning. However, the underlying mechanisms of how sleep rhythms contribute to consolidating memories acquired during wakefulness remain unclear. Here we studied the ro...

[The curative effect analysis of continuous positive airway pressure combined with modified oral appliance in the treatment of severe OSAHS].

Lin chuang er bi yan hou tou jing wai ke za zhi = Journal of clinical otorhinolaryngology head and neck surgery
OBJECTIVE: To evaluate the curative effect of continuous positive airway pressure(CPAP) combined with modified oral appliance (MOA) in the treatment of severe OSAHS.

[Validation of the advanced event detection in patients with sleep apnea hypopnea syndrome using auto-CPAP treatment].

Zhonghua jie he he hu xi za zhi = Zhonghua jiehe he huxi zazhi = Chinese journal of tuberculosis and respiratory diseases
OBJECTIVE: To validate the use of the event detection capabilities in an auto-CPAP system used by patients with sleep apnea hypopnea syndrome (SAHS).

Optimized echo state networks with leaky integrator neurons for EEG-based microsleep detection.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The performance of a microsleep detection system was calculated in terms of its ability to detect the behavioural microsleep state (1-s epochs) from spectral features derived from 16-channel EEG sampled at 256 Hz. Best performance from a single class...