AIMC Topic: Sleep Apnea Syndromes

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[Sleep apnea automatic detection method based on convolutional neural network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Aug 25, 2021
Sleep apnea (SA) detection method based on traditional machine learning needs a lot of efforts in feature engineering and classifier design. We constructed a one-dimensional convolutional neural network (CNN) model, which consists in four convolution...
Sensitivity and Specificity Electrocardiography Sleep Apnea Syndromes Humans Neural Networks, Computer Machine Learning
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Deep learning enables sleep staging from photoplethysmogram for patients with suspected sleep apnea.

Sleep Nov 12, 2020
STUDY OBJECTIVES: Accurate identification of sleep stages is essential in the diagnosis of sleep disorders (e.g. obstructive sleep apnea [OSA]) but relies on labor-intensive electroencephalogram (EEG)-based manual scoring. Furthermore, long-term asse...
Humans Sleep Apnea Syndromes Reproducibility of Results Deep Learning Sleep Photoplethysmography Sleep Stages
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[VOTE versus ACLTE: comparison of two snoring noise classifications using machine learning methods].

HNO Sep 1, 2019
BACKGROUND: Acoustic snoring sound analysis is a noninvasive method for diagnosis of the mechanical mechanisms causing snoring that can be performed during natural sleep. The objective of this work is development and evaluation of classification sche...
Machine Learning Noise Sleep Apnea Syndromes Sound Spectrography Snoring Humans
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Tracheal Sound Analysis Using a Deep Neural Network to Detect Sleep Apnea.

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine Aug 15, 2019
STUDY OBJECTIVES: Portable devices for home sleep apnea testing are often limited by their inability to discriminate sleep/wake status, possibly resulting in underestimations. Tracheal sound (TS), which can be visualized as a spectrogram, carries inf...
Humans Neural Networks, Computer Male Middle Aged Deep Learning Female Reproducibility of Results Sensitivity and Specificity Trachea Sleep Apnea Syndromes Respiratory Sounds Polysomnography
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Convolutional Neural Networks to Detect Pediatric Apnea-Hypopnea Events from Oximetry.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Pediatric sleep apnea-hypopnea syndrome (SAHS) is a highly prevalent breathing disorder that is related to many negative consequences for the children's health and quality of life when it remains untreated. The gold standard for pediatric SAHS diagno...
Oximetry Sleep Apnea Syndromes Polysomnography Humans Neural Networks, Computer Quality of Life Child
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Sleep Apnea Severity Estimation from Respiratory Related Movements 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 Jul 1, 2019
Sleep apnea is a common chronic respiratory disorder which occurs due to the repetitive complete or partial cessations of breathing during sleep. The gold standard assessment of sleep apnea requires full night polysomnography in a sleep laboratory wh...
Polysomnography Sleep Respiration Aged Adult Male Middle Aged Deep Learning Humans Sleep Apnea Syndromes Female
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Expert-level sleep scoring with deep neural networks.

Journal of the American Medical Informatics Association : JAMIA Dec 1, 2018
OBJECTIVES: Scoring laboratory polysomnography (PSG) data remains a manual task of visually annotating 3 primary categories: sleep stages, sleep disordered breathing, and limb movements. Attempts to automate this process have been hampered by the com...
Humans Neural Networks, Computer Machine Learning Polysomnography Sleep Stages Sleep Datasets as Topic Electroencephalography Classification Sleep Apnea Syndromes Models, Biological
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Robotics in oral and maxillofacial surgery.

Annals of the Royal College of Surgeons of England May 1, 2018
How trans-oral robotic surgery can treat cancer in the oropharyngyal space
Surgery, Oral Oropharyngeal Neoplasms Oropharynx Robotic Surgical Procedures Sleep Apnea Syndromes Organ Sparing Treatments Blood Loss, Surgical Robotics Length of Stay Humans Incidence Postoperative Complications Time Factors
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Towards a Wireless Smart Polysomnograph Using Symbolic Fusion.

Studies in health technology and informatics Jan 1, 2016
Polysomnography is the gold standard test for sleep disorders among which the Sleep Apnea Syndrome (SAS) is considered a public health issue because of the increase of the cardio-and cerebro-vascular risk it is associated with. However, the reliabili...
Pattern Recognition, Automated Equipment Failure Analysis Polysomnography Humans Equipment Design Wireless Technology Artificial Intelligence Sleep Apnea Syndromes Reproducibility of Results Sensitivity and Specificity Diagnosis, Computer-Assisted Decision Support Systems, Clinical
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[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 Nov 1, 2015
OBJECTIVE: To validate the use of the event detection capabilities in an auto-CPAP system used by patients with sleep apnea hypopnea syndrome (SAHS).
Humans Sleep Polysomnography Continuous Positive Airway Pressure Sleep Apnea Syndromes
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