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HD-sEMG-Based Control Using Neck Muscles and Shallow Neural Networks: Assessing Performance in

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    |February 19, 2026
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    Summary

    This study shows that the Recursive Rehabilitation Control Network (RRC-Net) and High-Density Electrode Array (HDE-Array) system effectively enhances rehabilitation independence for individuals with spinal cord injuries, with no performance difference between healthy and tetraplegic users.

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    Area of Science:

    • Neuroscience
    • Rehabilitation Engineering
    • Biomedical Engineering

    Background:

    • Functional Electrical Stimulation (FES) is crucial for restoring function in individuals with spinal cord injuries.
    • Developing intuitive and effective control systems is essential for maximizing independence through FES-assisted devices.
    • Existing control systems often require invasive methods or extensive training, limiting their widespread adoption.

    Purpose of the Study:

    • To evaluate the efficacy of the integrated Recursive Rehabilitation Control Network (RRC-Net) / High-Density Electrode Array (HDE-Array) system.
    • To assess the system's suitability for controlling multi-Degree of Freedom (DoF) tasks as proxies for FES control.
    • To determine if healthy and tetraplegic individuals exhibit comparable performance using the RRC-Net/HDE-Array system.

    Main Methods:

    • The study involved 10 tetraplegic and 8 healthy subjects performing two control tasks: a cursor task and a 3-DoF hand kinematic model task.
    • High-Density surface Electromyography (HD-sEMG) signals from the neck were used to train the RRC-Net neural network for movement estimation.
    • Performance metrics including Mean Global Distance (MGD), Mean Angular Distance (MAD), Task Completion Score (TCS), and Normalised Distance (ND) were analyzed.

    Main Results:

    • Both healthy and tetraplegic subjects achieved high performance levels in both cursor and hand control tasks.
    • No statistically significant differences in performance were observed between healthy and tetraplegic participants for either task.
    • Specific p-values indicated high similarity in performance: MGD (p=0.93), MAD (p=0.77), TCS (p=0.68), and ND (p=0.63).

    Conclusions:

    • The RRC-Net/HDE-Array system demonstrates significant potential for enhancing rehabilitation independence in individuals with spinal cord injuries.
    • The non-invasive nature, simplicity, and comfort of the system make it a promising tool for controlling assistive devices.
    • The system's effectiveness and comparable performance across user groups suggest a viable pathway for restoring functional control.