Changes in the cortical network during sleep stage transitions
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DOI: 10.1002/jnr.25125
Abstract: Sleep state transitions are closely related to insomnia, drowsiness, and sleep maintenance. However, how the cortical network varies during such a transition process remains unclear. Changes in the cortical interaction during the shortâterm process of… read more here.
Keywords: stage transitions; sleep stage; stage; cortical network ... See more keywords
Convolutional neural networks for sleep stage scoring on a two-channel EEG signal
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DOI: 10.1007/s00500-019-04174-1
Abstract: Sleeping problems have become one of the major diseases all over the world. To tackle this issue, the basic tool used by specialists is the polysomnogram, which is a collection of different signals recorded during… read more here.
Keywords: sleep stage; neural networks; scoring two; convolutional neural ... See more keywords
Investigating the use of uni-directional and bi-directional long short-term memory models for automatic sleep stage scoring
Sign Up to like & getrecommendations! Published in 2020 at "Informatics in Medicine Unlocked"
DOI: 10.1016/j.imu.2020.100370
Abstract: Abstract In this paper, a study is conducted to investigate the use of a Long Short-Term Memory (LSTM) learning system in automatic sleep stage scoring. The developed algorithm will automatically learn to classify sleep stages… read more here.
Keywords: medicine; sleep stage; performance; automatic sleep ... See more keywords
Dynamic sleep stage transition process analysis in patients with Parkinson's disease having sleep apnea syndrome
Sign Up to like & getrecommendations! Published in 2021 at "Informatics in Medicine Unlocked"
DOI: 10.1016/j.imu.2021.100656
Abstract: Abstract Early detection of non-motor symptoms, such as sleep disorder, is recommended for those with Parkinson's disease (PD). It is important to understand the sleep patterns of patients with PD having concomitant sleep apnea syndrome… read more here.
Keywords: sleep stage; transition; patients sas; patients concomitant ... See more keywords
Association of neurocognitive functioning with sleep stage dissociation and REM sleep instability in medicated patients with schizophrenia.
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DOI: 10.1016/j.jpsychires.2021.02.004
Abstract: Many patients with schizophrenia present with impaired cognitive functioning and sleep disturbances. Dissociated stages of sleep represent instability within distinct sleep regulatory cerebral networks. Previous studies found increased rates of rapid eye movement (REM) sleep… read more here.
Keywords: functioning; stage dissociation; rem sleep; sleep stage ... See more keywords
Automatic sleep-stage scoring based on photoplethysmographic signals.
Sign Up to like & getrecommendations! Published in 2020 at "Physiological measurement"
DOI: 10.1088/1361-6579/ab921d
Abstract: OBJECTIVE Sleep-stage scoring is important for sleep-quality evaluation and the diagnosis of related diseases. In this study, an automatic sleep-stage scoring method using photoplethysmographic (PPG) signals was proposed. APPROACH To construct the classification model, we… read more here.
Keywords: sleep stage; sleep quality; automatic sleep; stage ... See more keywords
Automatic sleep stage classification based on a two-channel electrooculogram and one-channel electromyogram
Sign Up to like & getrecommendations! Published in 2022 at "Physiological Measurement"
DOI: 10.1088/1361-6579/ac6bdb
Abstract: Objective. Sleep monitoring by polysomnography (PSG) severely degrades sleep quality. In order to reduce the load of sleep monitoring, an approach to automatic sleep stage classification without an electroencephalogram (EEG) was proposed. Approach. A total… read more here.
Keywords: stage classification; sleep stage; automatic sleep; sleep ... See more keywords
MRASleepNet: a multi-resolution attention network for sleep stage classification using single-channel EEG
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Neural Engineering"
DOI: 10.1088/1741-2552/aca2de
Abstract: Objective. Computerized classification of sleep stages based on single-lead electroencephalography (EEG) signals is important, but still challenging. In this paper, we proposed a deep neural network called MRASleepNet for automatic sleep stage classification using single-channel… read more here.
Keywords: classification; sleep stage; model; stage classification ... See more keywords
1075 Sleep-stage Independent Electroencephalography Features For Classification Of Veterans With Post-traumatic Stress Disorder
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DOI: 10.1093/sleep/zsaa056.1071
Abstract: Prior sleep studies have suggested that electroencephalography (EEG) spectral power and synchrony features in certain sleep stages differ significantly at the group-average level between subjects with and without post-traumatic stress disorder (PTSD). Here, we investigated… read more here.
Keywords: post traumatic; sleep stage; stage independent; model ... See more keywords
0440 Validation Study of Neural Network Algorithm for Automated Sleep Stage Scoring: StageNet
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DOI: 10.1093/sleep/zsaa056.437
Abstract: Polysomnography (level 1) is an important test for evaluating sleep status or disorder. In general, measured raw data of polysomnography is manually scored by sleep expert. However, manual scoring is a time-consuming and labor-intensive work.… read more here.
Keywords: sleep stage; network algorithm; neural network; stage ... See more keywords
Beyond K-complex binary scoring during sleep: Probabilistic classification using deep learning.
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DOI: 10.1093/sleep/zsaa077
Abstract: BACKGROUND K-complexes (KCs) are a recognized EEG 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… read more here.
Keywords: classification; sleep stage; complex binary; binary scoring ... See more keywords