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    Summary
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    We developed a new method to remove strong electrical stimulation artifacts from brain recordings. This technique significantly improves the quality of neural signals for brain-computer interfaces, aiding movement and sensation restoration.

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    Area of Science:

    • Neuroscience
    • Biomedical Engineering
    • Signal Processing

    Background:

    • Bi-directional brain-computer interfaces (BCIs) are crucial for restoring motor function and sensation.
    • Simultaneous neural recording and cortical stimulation in BCIs face challenges due to strong stimulation artifacts obscuring neural signals.

    Purpose of the Study:

    • To propose and validate a novel subspace-based method for effective removal of cortical electrical stimulation artifacts.
    • To demonstrate the practical applicability and superior performance of the proposed artifact removal technique.

    Main Methods:

    • A novel subspace-based algorithm was developed for artifact removal.
    • The method was applied to experimentally recorded electroencephalogram (EEG) data containing stimulation artifacts.

    Main Results:

    • The proposed method successfully suppressed cortical electrical stimulation artifacts by 30-40 dB.
    • Demonstrated superior performance compared to existing state-of-the-art artifact removal techniques.
    • The method is computationally efficient.

    Conclusions:

    • The novel subspace-based method offers an effective solution for removing stimulation artifacts in bi-directional BCIs.
    • This advancement can enhance the reliability and performance of BCIs for neural signal recording and stimulation.