Virtual constraint control of Knee-Ankle prosthesis using an improved estimate of the thigh phase-variable

In the human gait cycle, virtual constraints enforce a robust relationship between the thigh phase-variable and the knee/ankle angle. These constraints enable an accurate estimation and control of angular trajectory when the input phase-variable profile is low in gait aperiodicity and sensor noise. In this work, we present discrete Fourier transform (DFT) based virtual constraint schemes for estimating the knee/ankle trajectories using an improved monotonic and linear trajectory of the thigh phase-variable. To minimize the likely aberrations in the desired trajectory of the phase-variable, the contour of the thigh angle and its integral is amplitude scaled, time shifted, and interpolated over the complete stride. The processed contour is then refitted to an ideal circle using polynomial optimization via two different schemes. For both proposed schemes, estimated knee/ankle trajectories are compared with the benchmark gait kinematics of healthy persons and an amputee wearing three commercial prostheses. Simulation results, based on realistic prosthesis actuator parameters, show a 2.18 ± 0.83 times reduction in the mean trajectory tracking error for three contrasting walking speeds, validating the efficacy of proposed schemes.