AIMC Topic: Polysomnography

Clear Filters Showing 241 to 250 of 270 articles

Conventional Machine Learning Methods Applied to the Automatic Diagnosis of Sleep Apnea.

Advances in experimental medicine and biology Jan 1, 2022
The overnight polysomnography shows a range of drawbacks to diagnose obstructive sleep apnea (OSA) that have led to the search for artificial intelligence-based alternatives. Many classic machine learning methods have been already evaluated for this ...
Machine Learning Sleep Apnea, Obstructive Polysomnography Humans Artificial Intelligence
View on PubMed DOI

[Advances in the development of deep learning assisted diagnosis for obstructive sleep apnea].

Zhonghua er bi yan hou tou jing wai ke za zhi = Chinese journal of otorhinolaryngology head and neck surgery Dec 7, 2021
Sleep Apnea, Obstructive Polysomnography Humans Deep Learning
View on PubMed DOI

Machine Learning-based Sleep Staging in Patients with Sleep Apnea Using a Single Mandibular Movement Signal.

American journal of respiratory and critical care medicine Nov 15, 2021
Algorithms Prospective Studies Female Humans Machine Learning Mandible Sleep Apnea Syndromes Polysomnography Sleep Stages Pattern Recognition, Automated Male Middle Aged Adult Sensitivity and Specificity
View on PubMed DOI

Assessment of obstructive sleep apnea-related sleep fragmentation utilizing deep learning-based sleep staging from photoplethysmography.

Sleep Oct 11, 2021
STUDY OBJECTIVES: To assess the relationship between obstructive sleep apnea (OSA) severity and sleep fragmentation, accurate differentiation between sleep and wakefulness is needed. Sleep staging is usually performed manually using electroencephalog...
Polysomnography Sleep Deprivation Sleep Apnea, Obstructive Sleep Deep Learning Photoplethysmography Humans
View on PubMed DOI

A deep learning-based algorithm for detection of cortical arousal during sleep.

Sleep Dec 14, 2020
STUDY OBJECTIVES: The frequency of cortical arousals is an indicator of sleep quality. Additionally, cortical arousals are used to identify hypopneic events. However, it is inconvenient to record electroencephalogram (EEG) data during home sleep test...
Polysomnography Arousal Electroencephalography Algorithms Sleep Deep Learning
View on PubMed DOI

Deep learning applied to polysomnography to predict blood pressure in obstructive sleep apnea and obesity hypoventilation: a proof-of-concept study.

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine Oct 15, 2020
STUDY OBJECTIVES: Nocturnal blood pressure (BP) profile shows characteristic abnormalities in OSA, namely acute postapnea BP surges and nondipping BP. These abnormal BP profiles provide prognostic clues indicating increased cardiovascular disease ris...
Humans Deep Learning Obesity Hypoventilation Sleep Apnea, Obstructive Blood Pressure Hypertension Polysomnography
View on PubMed DOI

Beyond K-complex binary scoring during sleep: probabilistic classification using deep learning.

Sleep Oct 13, 2020
STUDY OBJECTIVES: K-complexes (KCs) are a recognized electroencephalography marker of sensory processing and a defining feature of sleep stage 2. KC frequency and morphology may also be reflective of sleep quality, aging, and a range of sleep and sen...
Deep Learning Electroencephalography Humans Polysomnography Sleep Stages Sleep
View on PubMed DOI

Automatic sleep staging using heart rate variability, body movements, and recurrent neural networks in a sleep disordered population.

Sleep Sep 14, 2020
STUDY OBJECTIVES: To validate a previously developed sleep staging algorithm using heart rate variability (HRV) and body movements in an independent broad cohort of unselected sleep disordered patients.
Polysomnography Sleep Stages Heart Rate Humans Sleep Neural Networks, Computer Algorithms
View on PubMed DOI

Support vector machine prediction of obstructive sleep apnea in a large-scale Chinese clinical sample.

Sleep Jul 13, 2020
STUDY OBJECTIVES: Polysomnography is the gold standard for diagnosis of obstructive sleep apnea (OSA) but it is costly and access is often limited. The aim of this study is to develop a clinically useful support vector machine (SVM)-based prediction ...
Surveys and Questionnaires Humans Aged Support Vector Machine Male Sleep Apnea, Obstructive Sensitivity and Specificity China Polysomnography Female
View on PubMed DOI

Temporal dependency in automatic sleep scoring via deep learning based architectures: An empirical study.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
The present study evaluates how effectively a deep learning based sleep scoring system does encode the temporal dependency from raw polysomnography signals. An exhaustive range of neural networks, including state of the art architecture, have been us...
Sleep Stages Sleep Deep Learning Polysomnography Electroencephalography
View on PubMed DOI
Popular Topics
Recent Journals