Results 31 to 40 of about 549,762 (295)
HARU Sleep: A Deep Learning-Based Sleep Scoring System With Wearable Sheet-Type Frontal EEG Sensors
IEEE Access, 2022 Analysis of sleep stages using electroencephalograms (EEGs), a critical procedure in health monitoring, has been researched extensively. Scoring of the sleep stages is highly dependent on experts’ knowledge or hand-crafted features created by ...
Shoya Matsumori +5 more
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A Review of Cerebral Hemodynamics During Sleep Using Near-Infrared Spectroscopy
Frontiers in Neurology, 2020 Investigating cerebral hemodynamic changes during regular sleep cycles and sleep disorders is fundamental to understanding the nature of physiological and pathological mechanisms in the regulation of cerebral oxygenation during sleep.
Haoran Ren +8 more
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Sleep stage detection using only heart rate
Health Informatics Journal, 2020 Getting enough quality sleep plays a vital role in protecting our mental health, physical health, and quality of life. Sleep deprivation can make it difficult to concentrate on daily activities, and lower sleep quality is associated with hypertension ...
Yasue Mitsukura +3 more
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Fast Convolutional Method for Automatic Sleep Stage Classification [PDF]
Healthcare Informatics Research, 2018 ObjectivesPolysomnography is essential to diagnose sleep disorders. It is used to identify a patient's sleep pattern during sleep. This pattern is obtained by a doctor or health practitioner by using a scoring process, which is time consuming.
Intan Nurma Yulita +2 more
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Deep residual networks for automatic sleep stage classification of raw polysomnographic waveforms [PDF]
, 2018 We have developed an automatic sleep stage classification algorithm based on deep residual neural networks and raw polysomnogram signals. Briefly, the raw data is passed through 50 convolutional layers before subsequent classification into one of five ...
Jennum, Poul +4 more
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Frontiers in Human Neuroscience, 2018 Electroencephalography (EEG) recordings represent a vital component of the assessment of sleep physiology, but the methodology presently used is costly, intrusive to participants, and laborious in application.
Annette Sterr +13 more
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Validation of non-REM sleep stage decoding from resting state fMRI using linear support vector machines [PDF]
, 2016 A growing body of literature suggests that changes in consciousness are reflected in specific connectivity patterns of the brain as obtained from resting state fMRI (rs-fMRI). As simultaneous electroencephalography (EEG) is often unavailable, decoding of
Altmann, A +9 more
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Destructive Bruxism: Sleep Stage Relationship [PDF]
Sleep, 1988 Despite apparent similar amounts of bruxism, two groups that had been evaluated polysomnographically differed dramatically in symptomatology. Patients with severe symptoms were referred to as the destructive bruxism group and were compared with (a) a group with sleep disturbance complaints who had bruxism and (b) a group of insomniac depressed patients
J C, Ware, J D, Rugh
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Does Rapid Eye Movement Sleep Aggravate Obstructive Sleep Apnea? [PDF]
Clinical and Experimental Otorhinolaryngology, 2019 Objectives. To investigate the apnea-hypopnea index (AHI) according to the sleep stage in more detail after control of posture. Methods. Patients who underwent nocturnal polysomnography between December 2007 and July 2018 were retrospectively evaluated ...
Sung Hee Kim +6 more
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Large-Scale Automated Sleep Staging [PDF]
Sleep, 2017 Automated sleep staging has been previously limited by a combination of clinical and physiological heterogeneity. Both factors are in principle addressable with large data sets that enable robust calibration. However, the impact of sample size remains uncertain.
Haoqi Sun +6 more
openaire +2 more sources