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Energy-Optimal Human Walking With Feedback-Controlled Robotic Prostheses: A Computational Study.

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    IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society
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    Optimizing robotic prostheses can improve mobility for lower-limb amputees. Minimizing prosthesis work rate reduces metabolic energy, potentially below non-amputee levels, but requires asymmetric gaits.

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    Area of Science:

    • Biomechanics
    • Robotics
    • Human-Computer Interaction

    Background:

    • Lower-limb amputees often face reduced mobility and increased metabolic cost.
    • Robotic prostheses offer a potential solution for improving amputee walking energetics and kinematics.

    Purpose of the Study:

    • To computationally optimize robotic prosthesis controllers for minimizing metabolic energy expenditure during walking.
    • To investigate the relationship between prosthesis work rate and metabolic rate in simulated transtibial amputees.

    Main Methods:

    • Large-scale trajectory optimization was applied to a simulated transtibial amputee model with a robotic prosthesis.
    • Multiple prosthesis feedback controllers were evaluated to identify energy-minimizing gaits.

    Main Results:

    • Net metabolic rate showed a non-monotonic relationship with net prosthesis work rate; extremes increased metabolic cost.
    • Predicted metabolic rates could be reduced below non-amputee levels with optimized, asymmetric gaits.
    • Symmetric walking gaits and passive SACH foot prostheses were associated with higher metabolic rates.

    Conclusions:

    • Computational optimization frameworks can aid robotic prosthesis design by exploring energy-minimizing gait strategies.
    • Achieving below-non-amputee metabolic rates may require highly asymmetric, computationally derived gaits.
    • Further research is needed to bridge simulation predictions with experimental validation for prosthesis design.