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This paper presents a new method to characterize human ankle mechanical impedance during treadmill locomotion with a wearable ankle robot, Anklebot. An ensemble-based system identification method was used to investigate the time-varying behavior of ankle mechanical impedance in two degrees of freedom, both in the sagittal and frontal planes. We also provide solutions to overcome the limitations of original ensemble-based methods in practical applications. A pilot study of three human subjects demonstrated the efficacy of our approach. Analysis results showed clear time-varying behaviors of ankle impedance across the gait cycle except in the mid- and terminal-stance phases, and these behaviors were accurately approximated as a second-order model with stiffness, damping, and inertia components. Interestingly, all three subjects showed similar time-varying behaviors in both degrees of freedom: impedance increased around heel-strike and decreased significantly at the end of the stance phase.