Literature DB >> 7607094

Recording the sleep EEG with periorbital skin electrodes.

E Werth1, A A Borbély.   

Abstract

The aim of the study was to examine whether the typical changes of the EEG in the course of a sleep episode can be recorded by skin electrodes placed at the outer canthi of the eyes. In sleep recording from young, healthy subjects, the signals from the electro-oculogram (EOG, E1-A2) derivation and a central scalp EEG derivation (C3-A2) were compared. Sleep stage scores obtained separately from each of the two signals yielded highly corresponding values with the exception of stages 2 and 4, for which there were discrepancies. Both signals were subjected to spectral analysis to compare the spectra and their evolution during sleep. An automated detection routine served to identify and eliminate epochs contaminated by eye movement potentials. The typical time course of EEG slow-wave activity (SWA; power density in the 0.75-4.5 Hz range) could be derived from both signals with only minor differences between the data sets. However, compared to the EEG spectra, power density of the EOG spectra was attenuated in frequencies higher than 2 Hz and the typical changes in the spindle frequency range were not evident. The results show that the major sleep parameters as well as the dynamics of SWA can be reliably determined from signals recorded from periorbital skin electrodes.

Entities:  

Mesh:

Year:  1995        PMID: 7607094     DOI: 10.1016/0013-4694(94)00337-k

Source DB:  PubMed          Journal:  Electroencephalogr Clin Neurophysiol        ISSN: 0013-4694


  4 in total

1.  Electro-oculography-based detection of sleep-wake in sleep apnea patients.

Authors:  Jussi Virkkala; Jussi Toppila; Paula Maasilta; Adel Bachour
Journal:  Sleep Breath       Date:  2014-10-01       Impact factor: 2.816

2.  Comparison of a single-channel EEG sleep study to polysomnography.

Authors:  Brendan P Lucey; Jennifer S Mcleland; Cristina D Toedebusch; Jill Boyd; John C Morris; Eric C Landsness; Kelvin Yamada; David M Holtzman
Journal:  J Sleep Res       Date:  2016-06-02       Impact factor: 3.981

3.  Machine-learning-derived sleep-wake staging from around-the-ear electroencephalogram outperforms manual scoring and actigraphy.

Authors:  Kaare B Mikkelsen; James K Ebajemito; Maria A Bonmati-Carrion; Nayantara Santhi; Victoria L Revell; Giuseppe Atzori; Ciro Della Monica; Stefan Debener; Derk-Jan Dijk; Annette Sterr; Maarten de Vos
Journal:  J Sleep Res       Date:  2018-11-13       Impact factor: 3.981

4.  Cortical region-specific sleep homeostasis in mice: effects of time of day and waking experience.

Authors:  Mathilde C C Guillaumin; Laura E McKillop; Nanyi Cui; Simon P Fisher; Russell G Foster; Maarten de Vos; Stuart N Peirson; Peter Achermann; Vladyslav V Vyazovskiy
Journal:  Sleep       Date:  2018-07-01       Impact factor: 5.849

  4 in total

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