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Automated sleep scoring: A review of the latest approaches
L Fiorillo, A Puiatti, M Papandrea, PL Ratti… - Sleep medicine …, 2019 - Elsevier
Clinical sleep scoring involves a tedious visual review of overnight polysomnograms by a
human expert, according to official standards. It could appear then a suitable task for modern …
human expert, according to official standards. It could appear then a suitable task for modern …
Sleep scoring using artificial neural networks
M Ronzhina, O Janoušek, J Kolářová, M Nováková… - Sleep medicine …, 2012 - Elsevier
Rapid development of computer technologies leads to the intensive automation of many
different processes traditionally performed by human experts. One of the spheres …
different processes traditionally performed by human experts. One of the spheres …
U-Sleep: resilient high-frequency sleep staging
Sleep disorders affect a large portion of the global population and are strong predictors of
morbidity and all-cause mortality. Sleep staging segments a period of sleep into a sequence …
morbidity and all-cause mortality. Sleep staging segments a period of sleep into a sequence …
Interrater reliability of sleep stage scoring: a meta-analysis
YJ Lee, JY Lee, JH Cho, JH Choi - Journal of Clinical Sleep …, 2022 - jcsm.aasm.org
Study Objectives: We evaluated the interrater reliabilities of manual polysomnography sleep
stage scoring. We included all studies that employed Rechtschaffen and Kales rules or …
stage scoring. We included all studies that employed Rechtschaffen and Kales rules or …
Expert-level sleep scoring with deep neural networks
S Biswal, H Sun, B Goparaju… - Journal of the …, 2018 - academic.oup.com
Objectives Scoring laboratory polysomnography (PSG) data remains a manual task of
visually annotating 3 primary categories: sleep stages, sleep disordered breathing, and limb …
visually annotating 3 primary categories: sleep stages, sleep disordered breathing, and limb …
[HTML][HTML] Validity and reliability of the Oura Ring Generation 3 (Gen3) with Oura sleep staging algorithm 2.0 (OSSA 2.0) when compared to multi-night ambulatory …
T Svensson, K Madhawa, NT Hoang, U Chung… - Sleep Medicine, 2024 - Elsevier
Purpose To evaluate the validity and the reliability of the Oura Ring Generation 3 (Gen3)
with Oura Sleep Staging Algorithm 2.0 (OSSA 2.0) through multi-night polysomnography …
with Oura Sleep Staging Algorithm 2.0 (OSSA 2.0) through multi-night polysomnography …
An end-to-end framework for real-time automatic sleep stage classification
A Patanaik, JL Ong, JJ Gooley, S Ancoli-Israel… - Sleep, 2018 - academic.oup.com
Sleep staging is a fundamental but time consuming process in any sleep laboratory. To
greatly speed up sleep staging without compromising accuracy, we developed a novel …
greatly speed up sleep staging without compromising accuracy, we developed a novel …
SLEEPNET: automated sleep staging system via deep learning
S Biswal, J Kulas, H Sun, B Goparaju… - arxiv preprint arxiv …, 2017 - arxiv.org
Sleep disorders, such as sleep apnea, parasomnias, and hypersomnia, affect 50-70 million
adults in the United States (Hillman et al., 2006). Overnight polysomnography (PSG) …
adults in the United States (Hillman et al., 2006). Overnight polysomnography (PSG) …
Scoring sleep with artificial intelligence enables quantification of sleep stage ambiguity: hypnodensity based on multiple expert scorers and auto-scoring
Abstract Study Objectives To quantify the amount of sleep stage ambiguity across expert
scorers and to validate a new auto-scoring platform against sleep staging performed by …
scorers and to validate a new auto-scoring platform against sleep staging performed by …
Ensemble computational intelligent for insomnia sleep stage detection via the sleep ECG signal
P Tripathi, MA Ansari, TK Gandhi, R Mehrotra… - IEEE …, 2022 - ieeexplore.ieee.org
Insomnia is a common sleep disorder in which patients cannot sleep properly. Accurate
detection of insomnia disorder is a crucial step for mental disease analysis in the early …
detection of insomnia disorder is a crucial step for mental disease analysis in the early …