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

Bibliographic Details
Title: Comparison of EEG Signal Spectral Characteristics Obtained with Consumer- and Research-Grade Devices.
Authors: Mikhaylov, Dmitry, Saeed, Muhammad, Husain Alhosani, Mohamed, F. Al Wahedi, Yasser
Source: Sensors (14248220); Dec2024, Vol. 24 Issue 24, p8108, 19p
Subject Terms: ELECTROENCEPHALOGRAPHY, BIOFEEDBACK training, HEADBANDS, MENTAL health, CONSUMERS
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. [ABSTRACT FROM AUTHOR]
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Database: Complementary Index
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ISSN:14248220
DOI:10.3390/s24248108
Published in:Sensors (14248220)
Language:English