Scale-free and oscillatory spectral measures of sleep stages in humans [PDF]
Frontiers in Neuroinformatics, 2022 Power spectra of sleep electroencephalograms (EEG) comprise two main components: a decaying power-law corresponding to the aperiodic neural background activity, and spectral peaks present due to neural oscillations.
Bence Schneider +10 more
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Sleep Stage Classification Using EEG Signal Analysis: A Comprehensive Survey and New Investigation
Entropy, 2016 Sleep specialists often conduct manual sleep stage scoring by visually inspecting the patient’s neurophysiological signals collected at sleep labs. This is, generally, a very difficult, tedious and time-consuming task.
Khald Ali I. Aboalayon +3 more
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Statistical Complexity Analysis of Sleep Stages [PDF]
EntropyStudying sleep stages is crucial for understanding sleep architecture, which can help identify various health conditions, including insomnia, sleep apnea, and neurodegenerative diseases, allowing for better diagnosis and treatment interventions.
Cristina D. Duarte +5 more
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Improved non-invasive detection of sleep stages when combining skin sympathetic nerve activity and heart rate variability analysis with AI [PDF]
Scientific ReportsSleep is a cyclic physiological process that goes into different stages, and every stage has its’ importance in the construction or recovery of physiological function. Sleep scoring is performed from polysomnography recordings which requires signals from
Md. Aktaruzzaman, Thomas H. Everett
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Validation Study of a Contactless Monitoring Device for Vital Signs During Sleep and Sleep Architecture in Adults With Sleep-Disordered Breathing [PDF]
Sleep Medicine Research, 2021 Background and Objective Few clinical studies have investigated the accuracy of non-contact monitoring devices for vital signs during sleep and sleep architecture in adults with sleep-disordered breathing (SDB).
Young Jeong Lee +6 more
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Estimating Sleep Stages Using a Head Acceleration Sensor
Sensors, 2021 Sleep disruption from causes, such as changes in lifestyle, stress from aging, family issues, or life pressures are a growing phenomenon that can lead to serious health problems. As such, sleep disorders need to be identified and addressed early on.
Motoki Yoshihi +4 more
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REM Sleep Stage Identification with Raw Single-Channel EEG
Bioengineering, 2023 This paper focused on creating an interpretable model for automatic rapid eye movement (REM) and non-REM sleep stage scoring for a single-channel electroencephalogram (EEG).
Gabriel Toban, Khem Poudel, Don Hong
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Mixed-Input Deep Learning Approach to Sleep/Wake State Classification by Using EEG Signals
Diagnostics, 2023 Sleep stage classification plays a pivotal role in predicting and diagnosing numerous health issues from human sleep data. Manual sleep staging requires human expertise, which is occasionally prone to error and variation. In recent times, availability of
Md. Nazmul Hasan, Insoo Koo
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Rules-Based and SVM-Q Methods With Multitapers and Convolution for Sleep EEG Stages Classification
IEEE Access, 2022 Sleep EEG signals analysis is an approach that helps researchers identify and understand the different phenomena concealed within sleep EEG data. This research introduces a time-frequency analysis approach to untangle the parameters of the sleep stages ...
Ignacio A. Zapata, Yan Li, Peng Wen
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Scoring sleep: the rules for looking inside [PDF]
Romanian Journal of Neurology, 2015 Polysomnography is the most comprehensive sleep study, a multi-parametric recording test (electroencephalography, electrooculogram, chin and limbs electromyogram, respiratory and cardiac functions and permanent videorecording), used as an important ...
Floriana Boghez, Ioana Mandruta
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