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Simulating human-prosthesis interaction and informing robotic prosthesis design using metabolic optimization

Handford, Matthew Lawrence
http://orcid.org/0000-0003-0713-248X
http://rave.ohiolink.edu/etdc/view?acc_num=osu1539707296618987

Abstract Details

2018, Doctor of Philosophy, Ohio State University, Mechanical Engineering.
Robotic lower limb prostheses can improve the quality of life for amputees. Development of such devices, currently dominated by long prototyping periods, could be sped up by predictive simulations. In contrast to some amputee simulations, which track experimentally determined non-amputee walking kinematics, we can instead explicitly model the human-prosthesis interaction to produce a prediction of the user's walking kinematics. To accomplish this, we use large-scale trajectory optimization on a muscle-driven multi-body model of an amputee with a robotic prosthesis to obtain metabolic energy-minimizing walking gaits. While this computational framework can be applied to a wide range of passive or biomechatronic prosthetic, exoskeletal, and assistive devices, here, we focus on unilateral ankle-foot prostheses. We use this optimization to determine optimized prosthesis controllers by minimizing a weighted sum of human metabolic and prosthesis costs and develop Pareto optimal curves between human metabolic and prosthesis cost with various prostheses masses and at various speeds. We also use this optimization to obtain trends in the energetics and kinematics for various net prosthesis work rates produced by given prosthesis feedback controllers. We find that the net metabolic rate has a roughly quadratic relationship with the net prosthesis work rate. This simulation predicts that metabolic rate could be reduced below that of a non-amputee, although such gaits are highly asymmetric and not seen in experiments with amputees. Walking simulations with bilateral symmetry in kinematics or ground reaction forces have higher metabolic rates than asymmetric gaits, suggesting a potential reason for asymmetries in amputee walking. Our findings suggest that a computational framework such as one presented here could augment the experimental approaches to prosthesis design iterations, although quantitatively accurate predictions of experiments from simulation remains an open problem. We run a series of optimizations to examine additional objective functions, which may improve the prediction. These objective functions include mechanical muscle costs and socket interaction costs. Finally, we consider a simple point-mass model of a unilateral amputee, finding that the point-mass models make broad qualitative predictions similar to those of the complex model: as the prosthesis produces more net work, the metabolic cost to the person is reduced and the bilateral asymmetry of the gait increases; favoring the affected side.
Manoj Srinivasan (Advisor)
Steve Collins (Committee Member)
Kiran D'Souza (Committee Member)
Rob Siston (Committee Member)
154 p.
Mechanical Engineering
prosthetics; rehabilitation robotics; legged locomotion; human-robot interaction; trajectory optimization; biomechanics; predictive models; biological system modeling; optimal control; design optimization; cost function; c; energy optimality

Recommended Citations

Citations

  • Handford, M. L. (2018). Simulating human-prosthesis interaction and informing robotic prosthesis design using metabolic optimization [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1539707296618987

    APA Style (7th edition)

  • Handford, Matthew. Simulating human-prosthesis interaction and informing robotic prosthesis design using metabolic optimization. 2018. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1539707296618987.

    MLA Style (8th edition)

  • Handford, Matthew. "Simulating human-prosthesis interaction and informing robotic prosthesis design using metabolic optimization." Doctoral dissertation, Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1539707296618987

    Chicago Manual of Style (17th edition)

osu1539707296618987
327
© 2018, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.