ArticleBrain topography2020
The Sensitivity of Ear-EEG: Evaluating the Source-Sensor Relationship Using Forward Modeling.
Article in Brain topography, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 32 citations in OpenAlex.
- Recent Progress in In-Ear EEG Technology and Its Emerging Real-World Applications: A Review.Micromachines · 2026Review
- In-ear EEG wearables for brain activity assessment and cognitive rehabilitation: the emerging role of multimodal embedded intelligence.Frontiers in human neuroscience · 2026Review
- Wireless ear EEG to monitor drowsiness.Nature communications · 2024Article
- The evaluation of cEEGrids for fatigue detection in aviation.Sleep advances : a journal of the Sleep Research Society · 2024Article
- Signal quality evaluation of an in-ear EEG device in comparison to a conventional cap system.Frontiers in neuroscience · 2024Article
- A Systematic Comparison of High-End and Low-Cost EEG Amplifiers for Concealed, Around-the-Ear EEG Recordings.Sensors (Basel, Switzerland) · 2023Article
- Validation of Continuous Monitoring System for Epileptic Users in Outpatient Settings.Sensors (Basel, Switzerland) · 2022Article
- Long-Term Polygraphic Monitoring through MEMS and Charge Transfer for Low-Power Wearable Applications.Sensors (Basel, Switzerland) · 2022Article
- Ear-EEG sensitivity modeling for neural sources and ocular artifacts.Frontiers in neuroscience · 2022Article
- Ear-EEG Measures of Auditory Attention to Continuous Speech.Frontiers in neuroscience · 2022Article
- Transcranial Auricular Vagus Nerve Stimulation (taVNS) and Ear-EEG: Potential for Closed-Loop Portable Non-invasive Brain Stimulation.Frontiers in human neuroscience · 2021Article
- Flex-Printed Ear-EEG Sensors for Adequate Sleep Staging at Home.Frontiers in digital health · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
Abstract
Ear-EEG allows to record brain activity in every-day life, for example to study natural behaviour or unhindered social interactions. Compared to conventional scalp-EEG, ear-EEG uses fewer electrodes and covers only a small part of the head. Consequently, ear-EEG will be less sensitive to some cortical sources. Here, we perform realistic electromagnetic simulations to compare cEEGrid ear-EEG with 128-channel cap-EEG. We compute the sensitivity of ear-EEG for different cortical sources, and quantify the expected signal loss of ear-EEG relative to cap-EEG. Our results show that ear-EEG is most sensitive to sources in the temporal cortex. Furthermore, we show how ear-EEG benefits from a multi-channel configuration (i.e. cEEGrid). The pipelines presented here can be adapted to any arrangement of electrodes and can therefore provide an estimate of sensitivity to cortical regions, thereby increasing the chance of successful experiments using ear-EEG.
Indexed as
Identifiers
What OpenQuestion holds
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.