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

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.

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Publication Details

Journal
Sensors
Published
2024-12-19
DOI
https://doi.org/10.3390/s24248108
Citations
8
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
2.74
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article

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

Muhammad Saeed, Dmitry Mikhaylov, Yasser F. Al Wahedi, Mohamed Husain Alhosani
8 citations
Sensors
EEG and Brain-Computer Interfaces
2.74
article

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

Muhammad Saeed, Dmitry Mikhaylov, Yasser F. Al Wahedi, Mohamed Husain Alhosani
article en
8 citations

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.

SensorsVol. 24(24)
No poverty
Openalex Percentile: Top 9%
EEG and Brain-Computer Interfaces
2.74
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