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... personalised management of obstructive sleep apnoea. Current Otorhinolaryngology Reports, ... Spectral Power Density of Sleep Electroencephalography and Psychiatric Symptoms ... in Patients with Breathing-related Sleep Disorder. Clinical Psychopharmacology and ...
Posted by szhivotovsky on May 16, 2023 in Guest Blogger
Overview AI for automated sleep staging is considered mature ... its way to commercial sleep evaluation systems. Systems underpinned by deep learning require large datasets ... a broad sample of sleep stages the machine seeks ...
Sleep Heart Health Study
6.6.2.6 Rules for assigning sleep stages EEG frequencies are ... and then disappears in sleep. The slowing may be ... waking record. Stage 1 sleep Stage 1 sleep occurs most often in ...
Sleep Heart Health Study
6.6.2.4 Rules for assigning sleep stages when arousal is ... maximize the amount of sleep identified and thus the ... require a change in sleep stage. The epoch is ...
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 ... applications and recording environments. Sleep staging can be performed ... neural network to infer sleep stage on the basis ...
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))
poxqual1 under Sleep Monitoring/Polysomnography/Evening and Morning Survey in MROS variables
Posted by szhivotovsky on September 1, 2023 in Guest Blogger
Overview Obstructive sleep apnea (OSA) affects more ... remaining undiagnosed. Although home sleep test solutions have existed ... of 39% for home sleep tests. Previous academic attempts ...
Reply by mrueschman on March 22, 2017 on Forum
... many variables that describe sleep architecture. TIMES34P is the "percent of sleep time in stage 3-4 sleep" (deep sleep). ...
stg2stg3pr5 under Sleep Monitoring/Polysomnography/Signal Quality in MESA variables
Reply by SoumyadeepThakur on April 22, 2021 on Forum
... trying to predict the sleep stage within a 30 ... I can't find the sleep stage annotations (W, 1, 2, Deep Sleep, REM) in the .edf ...
Sleep Heart Health Study
... be considered reliable, but sleep latency will be unreliable. ... being when onset of sleep occurs prior to the ... at the onset of sleep. Sleep latency will be considered ...
... NSRR Winter Webinar Series: Sleep Data Analysis Showcase PhysioZoo: ... of Physiological Biomarkers in Sleep Medicine Probing Complex Physiologic Signals During Sleep: Applications to Assessing Neuroautonomic ... Large Amount of NSRR Sleep Data via Deep Learning Algorithms Luna: A Toolset for Largescale Sleep Signal Analysis Analysis of ...
ltdp10 under Sleep Monitoring/Polysomnography/Evening and Morning Survey/SHHS1 in SHHS variables
Quality of sleep last night: light/deep (1=light to 5=deep)
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