AIMC Topic: Polysomnography

Clear Filters Showing 191 to 200 of 270 articles

Bayesian Nonnegative CP Decomposition-Based Feature Extraction Algorithm for Drowsiness Detection.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Daytime short nap involves physiological processes, such as alertness, drowsiness and sleep. The study of the relationship between drowsiness and nap based on physiological signals is a great way to have a better understanding of the periodical rhyme...

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...

Automatic detection of rapid eye movements (REMs): A machine learning approach.

Journal of neuroscience methods
BACKGROUND: Rapid eye movements (REMs) are a defining feature of REM sleep. The number of discrete REMs over time, or REM density, has been investigated as a marker of clinical psychopathology and memory consolidation. However, human detection of REM...

Clinical course of H1N1-vaccine-related narcolepsy.

Sleep medicine
OBJECTIVE: To follow and analyze the clinical course and quality of life of Pandemrix H1N1-vaccine-related narcolepsy (pNT1).

Relationship between obstructive sleep apnea cardiac complications and sleepiness in children with Down syndrome.

Sleep medicine
OBJECTIVE/BACKGROUND: Children with Down syndrome (DS) have a high rate of pulmonary hypertension and sleepiness. They also have a high prevalence of obstructive sleep apnea syndrome (OSAS). We hypothesized that OSAS was associated with cardiovascula...

Multi-channel EEG-based sleep stage classification with joint collaborative representation and multiple kernel learning.

Journal of neuroscience methods
BACKGROUND: Electroencephalography (EEG) based sleep staging is commonly used in clinical routine. Feature extraction and representation plays a crucial role in EEG-based automatic classification of sleep stages. Sparse representation (SR) is a state...

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...

Volumetric MRI analysis pre- and post-Transoral robotic surgery for obstructive sleep apnea.

The Laryngoscope
OBJECTIVES/HYPOTHESIS: To quantitatively measure volumetric changes in upper airway soft tissue structures using magnetic resonance imaging (MRI) pre- and post transoral robotic surgery for obstructive sleep apnea (OSA-TORS).

Automatic detection of sleep apnea based on EEG detrended fluctuation analysis and support vector machine.

Journal of clinical monitoring and computing
Sleep apnea syndrome (SAS) is prevalent in individuals and recently, there are many studies focus on using simple and efficient methods for SAS detection instead of polysomnography. However, not much work has been done on using nonlinear behavior of ...