The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Concealed, Unobtrusive Ear-Centered EEG Acquisition: cEEGrids for Transparent EEG
Open accessAbstract
Electroencephalography (EEG) is an important clinical tool and frequently used to study the brain-behavior relationship in humans noninvasively. Traditionally, EEG signals are recorded by positioning electrodes on the scalp and keeping them in place with glue, rubber bands, or elastic caps. This setup provides good coverage of the head, but is impractical for EEG acquisition in natural daily-life situations. Here, we propose the transparent EEG concept. Transparent EEG aims for motion tolerant, highly portable, unobtrusive, and near invisible data acquisition with minimum disturbance of a user's daily activities. In recent years several ear-centered EEG solutions that are compatible with the transparent EEG concept have been presented. We discuss work showing that miniature electrodes placed in and around the human ear are a feasible solution, as they are sensitive enough to pick up electrical signals stemming from various brain and non-brain sources. We also describe the cEEGrid flex-printed sensor array, which enables unobtrusive multi-channel EEG acquisition from around the ear. In a number of validation studies we found that the cEEGrid enables the recording of meaningful continuous EEG, event-related potentials and neural oscillations. Here, we explain the rationale underlying the cEEGrid ear-EEG solution, present possible use cases and identify open issues that need to be solved on the way toward transparent EEG.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Source modeling sleep slow waves
Murphy, M., Riedner, B. A., Huber, R., Massimini, M., Ferrarelli, F., & Tononi, G. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0807933106 · Cited by 454
The role of EEG in epilepsy: A critical review
Noachtar, S., & Rémi, J. (2009) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2009.02.035 · Cited by 434 · cited 2×
“EEG is extensively used for clinical applications such as epilepsy diagnostics (Noachtar and Rémi, 2009), sleep staging (Campbell, 2009), diagnosis of hearing loss (Paulraj et al.”
Method
Cited by
Hearables: Automatic Overnight Sleep Monitoring With Standardized In-Ear EEG Sensor
Nakamura, T., Alqurashi, Y. D., Morrell, M. J., & Mandic, D. P. (2020) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2019.2911423 · Cited by 147
Computer-assisted EEG diagnostic review for idiopathic generalized epilepsy
Clarke, S., Karoly, P. J., Nurse, E., Seneviratne, U., Taylor, J., Knight-Sadler, R., Kerr, R., Moore, B., Hennessy, P., Mendis, D., et al. (2021) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2019.106556 · Cited by 55
Zhao, H., Yu, S., Prinable, J., McEwan, A., & Karlsson, P. (2020) · IFMBE Proceedings · doi:10.1007/978-3-030-31635-8_226 · Cited by 9
Getting More from the Sleep Recording
McNicholas, W. T. (2021) · Sleep Medicine Clinics · doi:10.1016/j.jsmc.2021.08.001 · Cited by 3
Metadata
- Authors
- Bleichner, M. G., & Debener, S.
- Venue
- Frontiers in Human Neuroscience
- Publisher
- Frontiers Media SA
- Published
- 2017-04-07
- Volume
- 11
- Pages
- 163-163
- ISSN
- 1662-5161 (ISSN-L)
- OpenAlex
- W2602633288
- Cited by
- 215
- References
- 2
- FWCI
- 9.16
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Concealed, Unobtrusive Ear-Centered EEG Acquisition: cEEGrids for Transparent EEG. https://app.cochat.ai/papers/10.3389/fnhum.2017.00163
- The paper
- Bleichner, M. G., & Debener, S. (2017). Concealed, Unobtrusive Ear-Centered EEG Acquisition: cEEGrids for Transparent EEG. Frontiers in Human Neuroscience. https://doi.org/10.3389/fnhum.2017.00163
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.