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Nonlinear Mapping From EMG to Prosthesis Closing Velocity Improves Force Control With EMG Biofeedback.

Filip Gasparic, Nikola Jorgovanovic, Christian Hofer

    IEEE Transactions on Haptics
    |July 12, 2023
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces nonlinear mapping for electromyography (EMG) biofeedback to improve myoelectric prosthesis control. Nonlinear mapping enhances grasping force accuracy, especially for stronger muscle contractions, benefiting amputee users.

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    Area of Science:

    • Biomedical Engineering
    • Rehabilitation Technology
    • Human-Machine Interface

    Background:

    • Controlling myoelectric prosthesis grasping force using EMG biofeedback is challenging due to increased signal variability with higher muscle contractions.
    • Existing linear mapping methods struggle to maintain performance as desired force increases.

    Purpose of the Study:

    • To implement and validate a novel EMG biofeedback system using nonlinear mapping to enhance myoelectric prosthesis force control.
    • To investigate the effectiveness of nonlinear mapping compared to linear mapping and no feedback.

    Main Methods:

    • Developed an EMG biofeedback system employing nonlinear mapping, where EMG signal intervals are mapped to prosthesis velocity intervals.
    • Evaluated the system with 20 non-disabled subjects performing force-matching tasks and four transradial amputees performing a functional task.
    • Compared performance across conditions: no feedback, linear mapping biofeedback, and nonlinear mapping biofeedback.

    Main Results:

    • EMG biofeedback significantly improved the success rate of producing desired force compared to no feedback (65.4% vs. 46.2%).
    • Nonlinear mapping yielded a higher success rate than linear mapping (62.4% vs. 49.2%).
    • The highest success rate (72%) was achieved with EMG biofeedback combined with nonlinear mapping in non-disabled subjects, a trend also observed in amputee subjects.

    Conclusions:

    • EMG biofeedback is effective in improving myoelectric prosthesis force control.
    • Nonlinear mapping is a superior approach to linear mapping, effectively mitigating the challenges posed by increased myoelectric signal variability during strong muscle contractions.
    • The proposed nonlinear mapping strategy offers a promising advancement for intuitive and accurate prosthetic control.