AI Medical Compendium Journal:
Sleep & breathing = Schlaf & Atmung

Showing 21 to 24 of 24 articles

Sleep staging from single-channel EEG with multi-scale feature and contextual information.

Sleep & breathing = Schlaf & Atmung
PURPOSE: Portable sleep monitoring devices with less-attached sensors and high-accuracy sleep staging methods can expedite sleep disorder diagnosis. The aim of this study was to propose a single-channel EEG sleep staging model, SleepStageNet, which e...

Support vector machines for automated snoring detection: proof-of-concept.

Sleep & breathing = Schlaf & Atmung
BACKGROUND: Snoring has been shown to be associated with adverse physical and mental health, independent of the effects of sleep disordered breathing. Despite increasing evidence for the risks of snoring, few studies on sleep and health include objec...

A prediction model based on artificial neural networks for the diagnosis of obstructive sleep apnea.

Sleep & breathing = Schlaf & Atmung
BACKGROUND: Recently, artificial neural networks (ANNs) have been widely applied in science, engineering, and medicine. In the present study, we evaluated the ability of artificial neural networks to be used as a computer program and assistant tool i...

Real-time prediction of disordered breathing events in people with obstructive sleep apnea.

Sleep & breathing = Schlaf & Atmung
PURPOSE: Conventional therapies for obstructive sleep apnea (OSA) are effective but suffer from poor patient adherence and may not fully alleviate major OSA-associated cardiovascular risk factors or improve certain aspects of quality of life. Predict...