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Scalable Anatomically-Tunable Fully In-Ear Dry-Electrode Array for User-Generic Unobtrusive Electrophysiology.

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    This study introduces a simplified fabrication method for in-ear electroencephalography (EEG) sensors using printed circuit board (PCB) components. These novel dry-contact sensors offer improved wearability and successfully record brain activity and muscle artifacts.

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    Area of Science:

    • Biomedical Engineering
    • Neuroscience
    • Wearable Technology

    Background:

    • Traditional scalp electroencephalography (EEG) systems are cumbersome, require wet gels, and limit user mobility.
    • In-ear EEG offers a more wearable, user-friendly, and concealable alternative.
    • Current in-ear EEG fabrication is complex, requiring specialized equipment and custom designs.

    Purpose of the Study:

    • To simplify the fabrication of in-ear EEG sensors.
    • To develop user-generic in-ear EEG devices using readily available printed circuit board (PCB) components.
    • To assess the performance and reliability of these simplified in-ear EEG sensors.

    Main Methods:

    • Designed and fabricated in-ear EEG sensors using standard PCB components and user-generic earpiece designs.
    • Evaluated the sensors' ability to capture electrophysiological signals, including eye blinks, jaw clenches, auditory steady-state responses (ASSR), and alpha modulation.
    • Performed electrochemical impedance spectroscopy (EIS) to assess electrode-skin contact and impedance.

    Main Results:

    • The fabricated in-ear EEG sensors successfully recorded various physiological signals.
    • Electrode-skin contact was reliable, with impedance comparable to conventional dry electrodes.
    • The new design allows for substantially greater channel density compared to existing dry-electrode approaches.

    Conclusions:

    • A simplified, low-barrier fabrication method for in-ear EEG sensors has been demonstrated using PCB components.
    • These sensors provide a viable and potentially more accessible solution for wearable brain-computer interfaces.
    • The technology shows promise for long-term, comfortable, and discreet electroencephalography monitoring.