ArticleScientific reports2019
Accurate whole-night sleep monitoring with dry-contact ear-EEG.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.
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Who cites it
36 citing papers in PubMed, 1 synthesis or guideline pooled it, 127 citations in OpenAlex.
- A Systematic Review of Closed-Loop Feedback Techniques in Sleep Studies-Related Issues and Future Directions.Sensors (Basel, Switzerland) · 2020Pooled it
- Smart Wearable EEG Devices: A Review of Lightweight, Multi-Sensor Systems for Sleep and Everyday Neurophysiology.Biosensors · 2026Review
- Recent Progress in In-Ear EEG Technology and Its Emerging Real-World Applications: A Review.Micromachines · 2026Review
- A novel, wearable, in-ear EEG technology to assess sleep and daytime sleepiness.Bioelectronic medicine · 2026Article
- A direct comparison of simultaneously recorded scalp, around-ear and in-ear EEG for neural selective auditory attention decoding to speech.Scientific reports · 2025Article
- Evaluating the performance of wearable EEG sleep monitoring devices: a meta-analysis approach.npj biomedical innovations · 2025Article
- The Next Frontier in Brain Monitoring: A Comprehensive Look at In-Ear EEG Electrodes and Their Applications.Sensors (Basel, Switzerland) · 2025Review
- An Effective and Interpretable Sleep Stage Classification Approach Using Multi-Domain Electroencephalogram and Electrooculogram Features.Bioengineering (Basel, Switzerland) · 2025Article
- Ear-EEG sleep monitoring data sets.Scientific data · 2025Article
- Optimizing electrode configurations for EEG mild cognitive impairment detection.Scientific reports · 2025Article
- Home-Based sensing of the nervous system with clinical neurophysiology technologies: IFCN handbook chapter.Clinical neurophysiology practice · 2025Review
- DeepAttNet: deep neural network incorporating cross-attention mechanism for subject-independent mental stress detection in passive brain-computer interfaces using bilateral ear-EEG.Frontiers in human neuroscience · 2025Article
- Enhancing Deep Sleep Induction Through a Wireless In-Ear EEG Device Delivering Binaural Beats and ASMR: A Proof-of-Concept Study.Sensors (Basel, Switzerland) · 2024Article
- A ballistocardiogram dataset with reference sensor signals in long-term natural sleep environments.Scientific data · 2024Article
- An ensemble method for improving robustness against the electrode contact problems in automated sleep stage scoring.Scientific reports · 2024Article
- Wireless ear EEG to monitor drowsiness.Nature communications · 2024Article
- Evaluating the Electroencephalographic Signal Quality of an In-Ear Wearable Device.Sensors (Basel, Switzerland) · 2024Article
- Using a standalone ear-EEG device for focal-onset seizure detection.Bioelectronic medicine · 2024Article
- Signal quality evaluation of an in-ear EEG device in comparison to a conventional cap system.Frontiers in neuroscience · 2024Article
- Comparison analysis between standard polysomnographic data and in-ear-electroencephalography signals: a preliminary study.Sleep advances : a journal of the Sleep Research Society · 2024Article
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.