Abstract
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, here, we explicitly model the human-prosthesis interaction to produce a prediction of the user’s walking kinematics. We obtain simulations of an amputee using an ankle-foot prosthesis by simultaneously optimizing human movements and prosthesis actuation, minimizing a weighted sum of human metabolic and prosthesis costs. The resulting Pareto optimal solutions predict that increasing prosthesis energy cost, decreasing prosthesis mass, and allowing asymmetric gaits all decrease human metabolic rate for a given speed and alter human kinematics. The metabolic rates increase monotonically with speed. Remarkably, by performing an analogous optimization for a non-amputee human, we predict that an amputee walking with an appropriately optimized robotic prosthesis can have a lower metabolic cost – even lower than assuming that the non-amputee’s ankle torques are cost-free.
Highlights
Robotic lower limb prostheses can improve the quality of life for amputees
While all the results in the main manuscript are based on the above cost functions for the human and the prosthesis, we considered two other simple cost functions that have previously been used in biomechanics to model “effort” or metabolic cost: (1) cost rate for each muscle proportional to muscle-force squared[16,22], and (2) energy cost for each muscle proportional to a weighted sum of positive and negative work, scaled by the efficiencies of positive and negative work[11,23]
If ideal motor torques replaced all muscles crossing one ankle while maintaining identical kinematics, the human cost could be reduced by 41% by this “muscle replacement strategy”
Summary
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. The resulting Pareto optimal solutions predict that increasing prosthesis energy cost, decreasing prosthesis mass, and allowing asymmetric gaits all decrease human metabolic rate for a given speed and alter human kinematics. By performing an analogous optimization for a non-amputee human, we predict that an amputee walking with an appropriately optimized robotic prosthesis can have a lower metabolic cost – even lower than assuming that the non-amputee’s ankle torques are cost-free. Passive prosthesis users experience reduced mobility[2,3] and increased metabolic cost[4,5] compared to non-amputees. This reduced performance is partially due to reduced foot control and an inability to produce net positive work with the prosthesis. We predict that optimal prosthesis actuation can reduce the amputee metabolic cost much below normal human metabolic cost
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