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BEATS: An Open-Source, High-Precision, Multi-Channel EEG Acquisition Tool System.

Bing Zou, Yubo Zheng, Mu Shen

    IEEE Transactions on Biomedical Circuits and Systems
    |April 4, 2023
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces BEATS, an open-source electroencephalogram (EEG) acquisition system for brain-computer interface (BCI) research. It offers high-fidelity, 32-channel signal collection with a superior sampling rate and microsecond-level precision.

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    Area of Science:

    • Neuroscience
    • Biomedical Engineering
    • Computer Science

    Background:

    • Stable electroencephalogram (EEG) signal acquisition is critical for non-invasive brain-computer interface (BCI) technology.
    • Existing EEG systems often have closed-source hardware and software, limiting flexible expansion and secondary development for real-time BCI research.

    Purpose of the Study:

    • To present the Beijing University of Posts and Telecommunications EEG Acquisition Tool System (BEATS).
    • To provide an open-source, comprehensive EEG acquisition system addressing limitations in current technologies for BCI research.

    Main Methods:

    • Developed a comprehensive system including analog front end, microprocessor, and software platform.
    • Implemented techniques such as direct memory access, first-in-first-out, and timers for precise data acquisition.
    • Ensured wireless transmission of 32-channel EEG signals at a 4 kHz sampling rate.

    Main Results:

    • BEATS achieves a sampling rate superior to state-of-the-art systems.
    • Acquisition precision and stability are guaranteed at the microsecond level.
    • Demonstrated 24-hour continuous acquisition with no packet loss and an average maximum delay of 0.07 s/h.

    Conclusions:

    • BEATS is a high-performance, open-source EEG acquisition system suitable for real-time BCI research.
    • Its open design, plug-in structure, and accessible materials facilitate rapid reproduction and further development.
    • The system enhances flexibility and accessibility in EEG signal acquisition for advanced BCI applications.