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    A new Artificial Neural Network (ANN) control system for a 3 degrees-of-freedom (DoF) prosthetic wrist significantly improves function for transradial amputees in virtual reality (VR). This advanced prosthetic control reduces compensatory movements and enhances task performance compared to current myoelectric options.

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    Area of Science:

    • Biomedical Engineering
    • Neuroscience
    • Rehabilitation Technology

    Background:

    • Current prosthetic devices often have limited wrist functionality.
    • Existing control systems struggle to achieve efficient control for multi-DoF wrists.
    • Artificial Neural Network (ANN) based controls show promise for predicting distal joint movements.

    Purpose of the Study:

    • To adapt and evaluate an ANN-based 3 degrees-of-freedom (DoF) wrist control system for transradial amputations.
    • To compare the performance of the novel control system against current myoelectric control in virtual reality (VR).
    • To assess the system's impact on functional tasks and compensatory movements.

    Main Methods:

    • Trained an ANN on natural arm movements to predict distal joint control.
    • Adapted the control system for transradial amputation and real-life application considerations.
    • Compared the 3-DoF wrist control with myoelectric control on pick-and-place and clothespin relocation tasks in VR.
    • Simulated prosthesis mechanical constraints using a wrist brace in able-bodied participants (Exp1) and tested on transradial amputees (Exp2).

    Main Results:

    • The novel 3-DoF wrist control maintained good performance and significantly reduced compensatory movements compared to simulated prosthesis constraints.
    • Participants with transradial amputation showed markedly improved performance and reduced compensatory movements using the new control compared to their prosthesis alone.
    • The ANN-based 3-DoF wrist control outperformed current myoelectric prostheses in VR task completion.

    Conclusions:

    • The proposed movement-based 3-DoF wrist control represents a significant advancement over current myoelectric prostheses for virtual reality applications.
    • This control strategy effectively enhances prosthetic wrist functionality, improving performance and reducing compensatory movements in amputees.
    • Further development is warranted for the translation of this promising control system to real-world prosthetic devices.