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Related Experiment Video

Updated: Jan 25, 2026

Engineering Platform and Experimental Protocol for Design and Evaluation of a Neurally-controlled Powered Transfemoral Prosthesis
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Co-Adaptive Velocity and Position Control of 3-DoFs Prosthesis via Incremental Learning.

Dario Di Domenico, Fabio Egle, Andrea Marinelli

    IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society
    |January 23, 2026
    PubMed
    Summary
    This summary is machine-generated.

    Velocity-based prosthetic control enhances upper-limb prosthesis performance and user satisfaction compared to position control. This myocontrol strategy offers lower errors and workload, improving prosthetic movement for users.

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    Area of Science:

    • Biomedical Engineering
    • Rehabilitation Robotics
    • Neuroprosthetics

    Background:

    • Upper-limb prosthesis control is complex, requiring high cognitive load for natural movements.
    • Electromyographic (EMG) signal instability limits machine learning-based myocontrol.
    • Existing methods struggle with intuitive control of multi-degree-of-freedom (DoF) prosthetic devices.

    Purpose of the Study:

    • To investigate and compare simultaneous, proportional myocontrol strategies (position vs. velocity) for a 3-DoF upper-limb prosthesis.
    • To evaluate the co-adaptation between users and the prosthetic system using incremental learning.
    • To assess performance, usability, workload, simultaneity, and proportionality of each control strategy.

    Main Methods:

    • Two myocontrol strategies (position-based and velocity-based) were implemented with incremental learning for a 3-DoF prosthesis.
    • Six able-bodied and five limb-difference participants completed Target Achievement Control tests over four sessions.
    • Performance metrics included error rates, success rates, path efficiency, usability, workload, simultaneity, and proportionality.

    Main Results:

    • Velocity control demonstrated superior performance over position control across both participant groups, showing lower errors and workload.
    • Both control strategies improved over time in able-bodied participants; position control showed significant improvement in limb-difference participants.
    • No significant difference in usability was found between position and velocity control strategies.
    • Position control facilitated greater simultaneous actuation of multiple DoFs.

    Conclusions:

    • Velocity-based myocontrol is recommended for enhancing prosthetic performance and user satisfaction.
    • This strategy offers a more intuitive and less demanding control method for upper-limb prostheses.
    • Further research may explore hybrid control approaches to leverage the benefits of both strategies.