Oscillator-Based Hybrid Gait Phase Estimation Method for Hip Assistive Exoskeleton

Abstract

To solve the problem of slow or lack of convergence of the gait phase estimation of the adaptive oscillator (AO) in the walking speed switching stage, this study designs an oscillator-based hybrid gait phase estimation method for hip assistive exoskeletons. First, the collected raw data of the hip angle are processed by performing Butterworth low-pass filtering. Then, by analyzing the characteristics of the hip angle curve and plantar pressure during each stage of walking, a divider that combines the hip angle, hip angular velocity, and plantar pressure is constructed to divide each gait cycle accurately. Finally, a phase estimator based on the angle model (AMPE) is proposed to replace the AO for phase estimation during the walking speed switching phase and to revert to AO for phase estimation when the walking speed is stable. By performing experiments of different walking speeds switching on the treadmill and outdoor walking scenarios, it is verified that the oscillator-based hybrid gait phase estimation method (AO+AMPE) has lower phase estimation errors and improves the gait feature estimation performance in the case of different walking speed switching, when compared with the AO-based phase estimation method and the hybrid phase oscillator-based (PO+AO) phase estimation method.