The prototyped dry-contact ear-EEG platform represents an important technological advancement of the method in terms of user-friendliness because it eliminates the need for gel in the electrode-skin interface.

Sleep is a key phenomenon to both understanding, diagnosing and treatment of many illnesses, as well as for studying health and well being in general. Today, the only widely accepted method for clinically monitoring sleep is the polysomnography (PSG), which is, however, both expensive to perform and influences the sleep. This has led to investigations into light weight electroencephalography (EEG) alternatives. However, there has been a substantial performance gap between proposed alternatives and PSG. Here we show results from an extensive study of 80 full night recordings of healthy participants wearing both PSG equipment and ear-EEG. We obtain automatic sleep scoring with an accuracy close to that achieved by manual scoring of scalp EEG (the current gold standard), using only ear-EEG as input, attaining an average Cohen’s kappa of 0.73. In addition, this high performance is present for all 20 subjects. Finally, 19/20 subjects found that the ear-EEG had little to no negative effect on their sleep, and subjects were generally able to apply the equipment without supervision. This finding marks a turning point on the road to clinical long term sleep monitoring: the question should no longer be whether ear-EEG could ever be used for clinical home sleep monitoring, but rather when it will be.

Abbreviations: (AF594) Alexa Fluor™ 594, (AF594-MBL) conjugated human mannan-binding lectin, (CG-EGA) continuous glucose (Clarke) error grid analysis, (CGM) continuous glucose monitoring, (FDA) Food and Drug Administration, (HMCV1-Dex) hexamethoxy crystal violet-conjugated dextran, (ISF) interstitial fluid, (LED) light-emitting diode, (RAD) relative absolute difference

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