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personalised management of obstructive sleep apnoea. Current Otorhinolaryngology Reports,
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Spectral Power Density of Sleep Electroencephalography and Psychiatric Symptoms
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in Patients with Breathing-related Sleep Disorder. Clinical Psychopharmacology and
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Posted by
szhivotovsky
on
May 16, 2023
in
Guest Blogger
Overview AI for automated sleep staging is considered mature
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its way to commercial sleep evaluation systems. Systems underpinned by deep learning require large datasets
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a broad sample of sleep stages the machine seeks
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6.6.2.6 Rules for assigning sleep stages EEG frequencies are
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and then disappears in sleep. The slowing may be
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waking record. Stage 1 sleep Stage 1 sleep occurs most often in
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6.6.2.4 Rules for assigning sleep stages when arousal is
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maximize the amount of sleep identified and thus the
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require a change in sleep stage. The epoch is
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Posted by
szhivotovsky
on
October 17, 2023
in
Guest Blogger
Overview The Greifswald Sleep Stage Classifier (GSSC) is a highly accurate, deep learning-based automatic sleep stage classifier that priortises
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applications and recording environments. Sleep staging can be performed
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neural network to infer sleep stage on the basis
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stg2stg3pr
under
Sleep Monitoring/Polysomnography/Signal Quality
in
CHAT variables
1=sleep staging problem - scoring stage2/stage3-4 unreliable (when distinction between Stage 2 and Deep Sleep is unreliable because of EEG artifact (usually due to the respiratory or sweat artifact on the EEG, and High Pass filter =1Hz used))
Posted by
szhivotovsky
on
September 1, 2023
in
Guest Blogger
Overview Obstructive sleep apnea (OSA) affects more
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remaining undiagnosed. Although home sleep test solutions have existed
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of 39% for home sleep tests. Previous academic attempts
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be considered reliable, but sleep latency will be unreliable.
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being when onset of sleep occurs prior to the
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at the onset of sleep. Sleep latency will be considered
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NSRR Winter Webinar Series: Sleep Data Analysis Showcase PhysioZoo:
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of Physiological Biomarkers in Sleep Medicine Probing Complex Physiologic Signals During Sleep: Applications to Assessing Neuroautonomic
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Large Amount of NSRR Sleep Data via Deep Learning Algorithms Luna: A Toolset for Largescale Sleep Signal Analysis Analysis of
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avg_orp_wake
under
Sleep Monitoring/Polysomnography/Electroencephalogram
in
SHHS variables
Average Odds Ratio Product (ORP) in all 30-s epochs during manually scored sleep stages. ORP is a continuous index of sleep depth and wake propensity. A value of 0 indicates very deep sleep, a value of 2.5 indicates full wakefulness. Search for all EEG variables within this dataset
avg_orp_n1
under
Sleep Monitoring/Polysomnography/Electroencephalogram
in
SHHS variables
Average Odds Ratio Product (ORP) in all 30-s epochs during manually scored sleep stages. ORP is a continuous index of sleep depth and wake propensity. A value of 0 indicates very deep sleep, a value of 2.5 indicates full wakefulness. Search for all EEG variables within this dataset
avg_orp_n2
under
Sleep Monitoring/Polysomnography/Electroencephalogram
in
SHHS variables
Average Odds Ratio Product (ORP) in all 30-s epochs during manually scored sleep stages. ORP is a continuous index of sleep depth and wake propensity. A value of 0 indicates very deep sleep, a value of 2.5 indicates full wakefulness. Search for all EEG variables within this dataset
avg_orp_n3
under
Sleep Monitoring/Polysomnography/Electroencephalogram
in
SHHS variables
Average Odds Ratio Product (ORP) in all 30-s epochs during manually scored sleep stages. ORP is a continuous index of sleep depth and wake propensity. A value of 0 indicates very deep sleep, a value of 2.5 indicates full wakefulness. Search for all EEG variables within this dataset
avg_orp_rem
under
Sleep Monitoring/Polysomnography/Electroencephalogram
in
SHHS variables
Average Odds Ratio Product (ORP) in all 30-s epochs during manually scored sleep stages. ORP is a continuous index of sleep depth and wake propensity. A value of 0 indicates very deep sleep, a value of 2.5 indicates full wakefulness. Search for all EEG variables within this dataset
avg_orp_nonrem
under
Sleep Monitoring/Polysomnography/Electroencephalogram
in
SHHS variables
Average Odds Ratio Product (ORP) in all 30-s epochs during manually scored sleep stages. ORP is a continuous index of sleep depth and wake propensity. A value of 0 indicates very deep sleep, a value of 2.5 indicates full wakefulness. Search for all EEG variables within this dataset
avg_org_trt
under
Sleep Monitoring/Polysomnography/Electroencephalogram
in
SHHS variables
Average Odds Ratio Product (ORP) in all 30-s epochs during total recording time. ORP is a continuous index of sleep depth and wake propensity. A value of 0 indicates very deep sleep, a value of 2.5 indicates full wakefulness. Search for all EEG variables within this dataset
pct_epoch_1to1_25pct
under
Sleep Monitoring/Polysomnography/Electroencephalogram
in
SHHS variables
Distribution of 30-s epochs, as a percent of total recording time in different Odds Ratio Product (ORP) deciles. Younes et al. 2022 (PubMed ID: 35272350) ORP is a continuous index of sleep depth and wake propensity. A value of 0 indicates very deep sleep; a value of 2.5 indicates full wakefulness. These values are used to construct the ORP histogram and ORP phenotype (:orp_type:). Search for all EEG variables within this dataset
pct_epoch_2to2_25pct
under
Sleep Monitoring/Polysomnography/Electroencephalogram
in
SHHS variables
Distribution of 30-s epochs, as a percent of total recording time in different Odds Ratio Product (ORP) deciles. Younes et al. 2022 (PubMed ID: 35272350) ORP is a continuous index of sleep depth and wake propensity. A value of 0 indicates very deep sleep; a value of 2.5 indicates full wakefulness. These values are used to construct the ORP histogram and ORP phenotype (:orp_type:). Search for all EEG variables within this dataset
pct_epoch_0_75to1pct
under
Sleep Monitoring/Polysomnography/Electroencephalogram
in
SHHS variables
Distribution of 30-s epochs, as a percent of total recording time in different Odds Ratio Product (ORP) deciles. Younes et al. 2022 (PubMed ID: 35272350) ORP is a continuous index of sleep depth and wake propensity. A value of 0 indicates very deep sleep; a value of 2.5 indicates full wakefulness. These values are used to construct the ORP histogram and ORP phenotype (:orp_type:). Search for all EEG variables within this dataset
pct_epoch_1_75to2pct
under
Sleep Monitoring/Polysomnography/Electroencephalogram
in
SHHS variables
Distribution of 30-s epochs, as a percent of total recording time in different Odds Ratio Product (ORP) deciles. Younes et al. 2022 (PubMed ID: 35272350) ORP is a continuous index of sleep depth and wake propensity. A value of 0 indicates very deep sleep; a value of 2.5 indicates full wakefulness. These values are used to construct the ORP histogram and ORP phenotype (:orp_type:). Search for all EEG variables within this dataset