Evidence map›Paper›PMID 39771843›Full record

ArticleSensors (Basel, Switzerland)2024

Comparison of EEG Signal Spectral Characteristics Obtained with Consumer- and Research-Grade Devices.

Dmitry Mikhaylov, Muhammad Saeed, Mohamed Husain Alhosani, Yasser F Al Wahedi

Abstract readComparative Study
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Dmitry MikhaylovAbu Dhabi Maritime Academy, Abu Dhabi P.O. Box 54477, United Arab Emirates.
Muhammad SaeedAbu Dhabi Maritime Academy, Abu Dhabi P.O. Box 54477, United Arab Emirates.ORCID 0000-0002-5079-0149
Mohamed Husain AlhosaniAbu Dhabi Maritime Academy, Abu Dhabi P.O. Box 54477, United Arab Emirates.
Yasser F Al WahediAbu Dhabi Maritime Academy, Abu Dhabi P.O. Box 54477, United Arab Emirates.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electroencephalography (EEG) has emerged as a pivotal tool in both research and clinical practice due to its non-invasive nature, cost-effectiveness, and ability to provide real-time monitoring of brain activity. Wearable EEG technology opens new avenues for consumer applications, such as mental health monitoring, neurofeedback training, and brain-computer interfaces. However, there is still much to verify and re-examine regarding the functionality of these devices and the quality of the signal they capture, particularly as the field evolves rapidly. In this study, we recorded the resting-state brain activity of healthy volunteers via three consumer-grade EEG devices, namely PSBD Headband Pro, PSBD Headphones Lite, and Muse S Gen 2, and compared the spectral characteristics of the signal obtained with that recorded via the research-grade Brain Product amplifier (BP) with the mirroring montages. The results showed that all devices exhibited higher mean power in the low-frequency bands, which are characteristic of dry-electrode technology. PSBD Headband proved to match BP most precisely among the other examined devices. PSBD Headphones displayed a moderate correspondence with BP and signal quality issues in the central group of electrodes. Muse demonstrated the poorest signal quality, with extremely low alignment with BP. Overall, this study underscores the importance of considering device-specific design constraints and emphasizes the need for further validation to ensure the reliability and accuracy of wearable EEG devices.

Indexed as

ElectroencephalographySignal Processing, Computer-AssistedAdultBrainBrain-Computer InterfacesElectrodesFemaleHumansMaleWearable Electronic DevicesYoung Adultconsumer-grade EEG devicesdry electrodesEEG device comparisonEEG signal qualityspectral analysiswearable EEG technology

Identifiers

PMID39771843
PMCPMC11679099

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Registered trials

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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.