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A scoping review on the use of consumer-grade EEG devices for research
Open accessAbstract
Background: Commercial electroencephalography (EEG) devices have become increasingly available over the last decade. These devices have been used in a wide variety of fields ranging from engineering to cognitive neuroscience. Purpose: The aim of this study was to chart peer-review articles that used consumer-grade EEG devices to collect neural data. We provide an overview of the research conducted with these relatively more affordable and user-friendly devices. We also inform future research by exploring the current and potential scope of consumer-grade EEG. Methods: We followed a five-stage methodological framework for a scoping review that included a systematic search using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines. We searched the following online databases: PsycINFO, MEDLINE, Embase, Web of Science, and IEEE Xplore. We charted study data according to application (BCI, experimental research, validation, signal processing, and clinical) and location of use as indexed by the first author’s country. Results: We identified 916 studies that used data recorded with consumer-grade EEG: 531 were reported in journal articles and 385 in conference papers. Emotiv devices were used most, followed by the NeuroSky MindWave, OpenBCI, interaXon Muse, and MyndPlay Mindband. The most common usage was for brain-computer interfaces, followed by experimental research, signal processing, validation, and clinical purposes. Conclusions: Consumer-grade EEG is a useful tool for neuroscientific research and will likely continue to be used well into the future. Our study provides a comprehensive review of their application, as well as future directions for researchers who plan to use these devices.
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“Practical deployment often limits channel count, as many commercial and mobile devices lack research-grade electrode coverage [3].”
From ERP-XTTN: interpretable prototype-guided cross-attention for cross-subject ERP classification (2026) · cites this paper as [3]
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Metadata
- Authors
- Sabio, J., Williams, N. S., McArthur, G. M., & Badcock, N. A.
- Affiliations
- The University of Queensland (AU)
- Macquarie University (AU)
- The University of Western Australia (AU)
- Corresponding author
- Sabio, Joshua
- Venue
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2024-03-06
- Volume
- 19
- Issue
- 3
- Pages
- e0291186
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC10917334
- OpenAlex
- W4392536393
- Cited by
- 98
- References
- 158
- Citations by year
- 2026: 41 · 2025: 47 · 2024: 9
- FWCI
- 6.27
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- UWA Profiles and Research Repository (UWA) (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- Macquarie University Co-Funded Research Fellowship Scheme (83673928)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
- Physical Sciences › Computer Science › Human-Computer Interaction › Gaze Tracking and Assistive Technology
- Keywords
- consumer-grade EEG, brain-computer interface, NeuroSky MindWave, OpenBCI, EEG signal processing, clinical EEG
- MeSH terms
- Electroencephalography, Engineering, Peer Review, MEDLINE, Brain-Computer Interfaces
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