ArticleBiomedical engineering letters2024
Evaluation of consumer-grade wireless EEG systems for brain-computer interface applications.
Article in Biomedical engineering letters, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- A comprehensive evaluation framework for consumer-grade EEG devices: signal quality, robustness, and usability.Scientific reports · 2026Article
- Wearable EEG devices in the detection of mild cognitive impairment: a systematic review.NPJ digital medicine · 2026Article
- Hybrid BCI for Meal-Assist Robot Using Dry-Type EEG and Pupillary Light Reflex.Biomimetics (Basel, Switzerland) · 2025Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the growing popularity of consumer-grade electroencephalogram (EEG) devices for health, entertainment, and cognitive research, assessing their signal quality is essential. In this study, we evaluated four consumer-grade wireless and dry-electrode EEG systems widely used for brain-computer interface (BCI) research and applications, comparing them with a research-grade system. We designed an EEG phantom method that reproduced µV-level amplitude EEG signals and evaluated the five devices based on their spectral responses, temporal patterns of event-related potential (ERP), and spectral patterns of resting-state EEG. We discovered that the consumer-grade devices had limited bandwidth compared with the research-grade device. A late component (e.g., P300) was detectable in the consumer-grade devices, but the overall ERP temporal pattern was distorted. Only one device showed an ERP temporal pattern comparable to that of the research-grade device. On the other hand, we confirmed that the activation of the alpha rhythm was observable in all devices. The results provide valuable insights for researchers and developers when it comes to selecting suitable EEG devices for BCI research and applications.
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