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MSDAC: A multi-source domain adversarial framework for motion prediction in intracortical brain-computer interfaces.

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    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
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    Summary

    New brain-computer interface decoding methods improve stability for paralyzed patients. The multi-source domain adversarial classification (MSDAC) framework enhances cross-day decoding accuracy without recalibration.

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    Area of Science:

    • Neuroscience
    • Biomedical Engineering
    • Machine Learning

    Background:

    • Intracortical brain-computer interfaces (iBCIs) enable motor function restoration in paralysis.
    • Current iBCI decoding methods require frequent recalibration due to neural data instability, hindering reliable online control.

    Purpose of the Study:

    • To develop a robust cross-day decoding framework for iBCIs that minimizes the need for frequent recalibration.
    • To enhance the stability and performance of iBCI systems by addressing neural data variability.

    Main Methods:

    • Proposed a multi-source domain adversarial classification (MSDAC) framework utilizing out-of-distribution generalization.
    • Implemented adversarial networks to minimize distribution discrepancies across historical data domains (by date).
    • Evaluated the MSDAC framework on five months of monkey center-out neural activity data.

    Main Results:

    • The MSDAC framework achieved an average decoding accuracy of 84.38% across 150 days without using test day data for calibration.
    • Demonstrated robust domain-invariant characteristics, leading to superior performance on unseen test data.
    • Significantly improved decoding stability and reduced the need for recalibration.

    Conclusions:

    • The MSDAC framework offers a stable and effective solution for cross-day decoding in iBCI systems.
    • This approach has the potential to significantly advance the clinical applicability of iBCIs for individuals with paralysis.
    • MSDAC represents a promising direction for developing reliable, long-term brain-computer interfaces.