Abstract
Researchers are currently making progress in unifying the entire gait cycle of powered prostheses by using a human-inspired phase variable, but constructing a robust phase variable to more accurately estimate the gait phase and desired joint trajectories of prostheses during varying walking speeds remains an open problem. Firstly, this study proposed a piecewise monotonic and smooth phase variable to predict the gait phase from only the measured thigh angle. Compared to the two most widely used methods, thigh angle integral vs. thigh angle and thigh angular rate vs. thigh angle, the proposed method addressed the drift problem of the integral-based method and the noise problem of the angular rate-based. Then a predictive tuning-free model that represents gait kinematics as a continuous function of proposed phase variable and walking speed was constructed to generate desired joint virtual constraints for speed-adaptation control of powered knee-ankle prosthesis during continuously varying walking speeds. Experiments were conducted with six able-bodied participants wearing inertial measurement units and performing periodic and non-periodic (quick start and stop) tasks, and one transfemoral amputee wearing a powered knee-ankle prosthesis walking on a treadmill. Experimental results illustrated that the root mean squared error of the gait phase estimated by the proposed approach was 75% lower than the integral-based and angular rate-based methods, and the proposed approach performed well in the continuous phase control of a powered knee-ankle prosthesis during varying walking speeds.
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