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      Sleep EEG Derived From Behind-the-Ear Electrodes (cEEGrid) Compared to Standard Polysomnography: A Proof of Concept Study

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          Abstract

          Electroencephalography (EEG) recordings represent a vital component of the assessment of sleep physiology, but the methodology presently used is costly, intrusive to participants, and laborious in application. There is a recognized need to develop more easily applicable yet reliable EEG systems that allow unobtrusive long-term recording of sleep-wake EEG ideally away from the laboratory setting. cEEGrid is a recently developed flex-printed around-the-ear electrode array, which holds great potential for sleep-wake monitoring research. It is comfortable to wear, simple to apply, and minimally intrusive during sleep. Moreover, it can be combined with a smartphone-controlled miniaturized amplifier and is fully portable. Evaluation of cEEGrid as a motion-tolerant device is ongoing, but initial findings clearly indicate that it is very well suited for cognitive research. The present study aimed to explore the suitability of cEEGrid for sleep research, by testing whether cEEGrid data affords the signal quality and characteristics necessary for sleep stage scoring. In an accredited sleep laboratory, sleep data from cEEGrid and a standard PSG system were acquired simultaneously. Twenty participants were recorded for one extended nocturnal sleep opportunity. Fifteen data sets were scored manually. Sleep parameters relating to sleep maintenance and sleep architecture were then extracted and statistically assessed for signal quality and concordance. The findings suggest that the cEEGrid system is a viable and robust recording tool to capture sleep and wake EEG. Further research is needed to fully determine the suitability of cEEGrid for basic and applied research as well as sleep medicine.

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          Most cited references16

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          Statistical methods for assessing agreement between two methods of clinical measurement.

          In clinical measurement comparison of a new measurement technique with an established one is often needed to see whether they agree sufficiently for the new to replace the old. Such investigations are often analysed inappropriately, notably by using correlation coefficients. The use of correlation is misleading. An alternative approach, based on graphical techniques and simple calculations, is described, together with the relation between this analysis and the assessment of repeatability.
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            Unobtrusive ambulatory EEG using a smartphone and flexible printed electrodes around the ear

            This study presents first evidence that reliable EEG data can be recorded with a new cEEGrid electrode array, which consists of ten electrodes printed on flexible sheet and arranged in a c-shape to fit around the ear. Ten participants wore two cEEGrid systems for at least seven hours. Using a smartphone for stimulus delivery and signal acquisition, resting EEG and auditory oddball data were collected in the morning and in the afternoon six to seven hours apart. Analysis of resting EEG data confirmed well-known spectral differences between eyes open and eyes closed conditions. The ERP results confirmed the predicted condition effects with significantly larger P300 amplitudes for target compared to standard tones, and a high test-retest reliability of the P300 amplitude (r > = .74). Moreover, a linear classifier trained on data from the morning session revealed similar performance in classification accuracy for the morning and the afternoon sessions (both > 70%). These findings demonstrate the feasibility of concealed and comfortable brain activity acquisition over many hours.
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              Cerebral states during sleep, as studied by human brain potentials.

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                Author and article information

                Contributors
                Journal
                Front Hum Neurosci
                Front Hum Neurosci
                Front. Hum. Neurosci.
                Frontiers in Human Neuroscience
                Frontiers Media S.A.
                1662-5161
                26 November 2018
                2018
                : 12
                : 452
                Affiliations
                [1] 1School of Psychology, Faculty of Health and Medical Sciences, University of Surrey , Guilford, United Kingdom
                [2] 2Institute of Biomedical Engineering, University of Oxford , Oxford, United Kingdom
                [3] 3Surrey Sleep Research Centre, University of Surrey , Guildford, United Kingdom
                [4] 4Surrey Clinical Research Centre, Department of Psychology, University of Surrey , Guildford, Germany
                [5] 5Neuropsychology Lab, Department of Psychology, University of Oldenburg , Oldenburg, Germany
                [6] 6Cluster of Excellence Hearing, University of Oldenburg , Oldenburg, Germany
                Author notes

                Edited by: Matthew Tucker, University of South Carolina, United States

                Reviewed by: Vasil Kolev, Institute of Neurobiology (BAS), Bulgaria; Bjoern Rasch, Université de Fribourg, Switzerland; Rolf Verleger, Universität zu Lübeck, Germany

                *Correspondence: Annette Sterr, a.sterr@ 123456surrey.ac.uk
                Article
                10.3389/fnhum.2018.00452
                6276915
                30534063
                328f6ff7-c28b-4246-bd60-90f5e45e0d36
                Copyright © 2018 Sterr, Ebajemito, Mikkelsen, Bonmati-Carrion, Santhi, della Monica, Grainger, Atzori, Revell, Debener, Dijk and DeVos.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 13 March 2018
                : 24 October 2018
                Page count
                Figures: 4, Tables: 5, Equations: 0, References: 23, Pages: 9, Words: 0
                Funding
                Funded by: Engineering and Physical Sciences Research Council 10.13039/501100000266
                Award ID: EP/K503939/1
                Funded by: Wellcome Trust 10.13039/100004440
                Award ID: 098461/Z/12/Z
                Categories
                Neuroscience
                Original Research

                Neurosciences
                electroencephalography,monitoring,sleep recording,home polysomnography,sleep stages,wake
                Neurosciences
                electroencephalography, monitoring, sleep recording, home polysomnography, sleep stages, wake

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