  Gait phase-based control is a trending research topic for walking-aid robots,
especially robotic lower-limb prostheses. Gait phase estimation is a challenge
for gait phase-based control. Previous researches used the integration or the
differential of the human's thigh angle to estimate the gait phase, but
accumulative measurement errors and noises can affect the estimation results.
In this paper, a more robust gait phase estimation method is proposed using a
unified form of piecewise monotonic gait phase-thigh angle models for various
locomotion modes. The gait phase is estimated from only the thigh angle, which
is a stable variable and avoids phase drifting. A Kalman filter-based smoother
is designed to further suppress the mutations of the estimated gait phase.
Based on the proposed gait phase estimation method, a gait phase-based joint
angle tracking controller is designed for a transfemoral prosthesis. The
proposed gait estimation method, the gait phase smoother, and the controller
are evaluated through offline analysis on walking data in various locomotion
modes. And the real-time performance of the gait phase-based controller is
validated in an experiment on the transfemoral prosthesis.
