Frontiers in Neurorobotics (Jan 2022)

Control Framework for Sloped Walking With a Powered Transfemoral Prosthesis

  • Namita Anil Kumar,
  • Shawanee Patrick,
  • Woolim Hong,
  • Pilwon Hur

DOI
https://doi.org/10.3389/fnbot.2021.790060
Journal volume & issue
Vol. 15

Abstract

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User customization of a lower-limb powered Prosthesis controller remains a challenge to this date. Controllers adopting impedance control strategies mandate tedious tuning for every joint, terrain condition, and user. Moreover, no relationship is known to exist between the joint control parameters and the slope condition. We present a control framework composed of impedance control and trajectory tracking, with the transitioning between the two strategies facilitated by Bezier curves. The impedance (stiffness and damping) functions vary as polynomials during the stance phase for both the knee and ankle. These functions were derived through least squares optimization with healthy human sloped walking data. The functions derived for each slope condition were simplified using principal component analysis. The weights of the resulting basis functions were found to obey monotonic trends within upslope and downslope walking, proving the existence of a relationship between the joint parameter functions and the slope angle. Using these trends, one can now design a controller for any given slope angle. Amputee and able-bodied walking trials with a powered transfemoral prosthesis revealed the controller to generate a healthy human gait. The observed kinematic and kinetic trends with the slope angle were similar to those found in healthy walking.

Keywords