The visual scoring of sleep in adults.

By M. Silber, S. Ancoli-Israel, M. Bonnet, S. Chokroverty, M. Grigg-Damberger, M. Hirshkowitz, S. Kapen, S. Keenan, M. Kryger, T. Penzel and 2 more. Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine, 2007

1,066 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/daf27e2ddb41caa215b8b7fddc7cb1259a30add1

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Citations in the corpus

Learning machines and sleeping brains: Automatic sleep stage classification using decision-tree multi-class support vector machines. (2015, methodology): “Since expert visual scoring will be used to benchmark the results f the automatic classification method, sleep stages were first visully scored offline according to standard criteria (Silber et al., 2007) y two experts to derive hypnograms based on 30-s epochs to etermine the vigilance state (wake, ”
A revised glossary of terms most commonly used by clinical electroencephalographers and updated proposal for the report format of the EEG findings. Revision 2017 (2017, background): “Comment: classified by various systems (see Iber et al., 2007 and Silber et al., 2007, based on the frameworks of Dement and Kleitman, 1957, Rechtschaffen and Kales, 1968).”
An open-source, high-performance tool for automated sleep staging (2021, methodology): “All PSG recordings were scored by trained technicians using standard AASM guidelines ( Iber et al., 2007 ; Silber et al., 2007 ).”
Automatic Sleep Stage Scoring Using Time-Frequency Analysis and Stacked Sparse Autoencoders (2015, methodology): “In Table 1 we reproduce the Rechtschaﬀen and Kales sleep staging criteria [22], merging the criteria for N3 and N4 into a single stage (N3).”
Automatic Sleep Stage Scoring with Single-Channel EEG Using Convolutional Neural Networks (2016, methodology): “For our study, we removed the very small number of Movement and Not Scored epochs (Not Scored epochs were at the start or end of each recording), and also merged the N3 and N4 stages into a single N3 stage, as is currently the recommended by the American Academy of Sleep Medicine (AASM) [12, 25].”
ISRUC-Sleep: A comprehensive public dataset for sleep researchers (2016, methodology): “The 2007 AASM visual scoring rules recommend a frontal electrode for best detecting Kcomplexes, a central electrode for spindles, and an occipital electrode for alpha waves [10].”
Cellular and neurochemical basis of sleep stages in the thalamocortical network (2016, background): “These features form the basis for classification of sleep into different stages: rapid eye movement sleep (REM), and stages N1 (Stage 1), N2 (Stage 2) and N3 (Stage 3) of non-REM sleep (Rechtschaffen and Kales, 1968; Iber and Medicine, 2007; Silber et al., 2007).”
Rotating waves during human sleep spindles organize global patterns of activity that repeat precisely through the night (2016, methodology): “ECoG recordings that did not have a seizure in the preceding or following 12 hr were scored visually by an expert rater following the standard sleep stage classification (Silber et al., 2007).”