Stochastic Estimation of Multi-variable Human Ankle Mechanical Impedance

Abstract

This article presents preliminary stochastic estimates of the multi-variable human ankle mechanical impedance. We employed Anklebot, a rehabilitation robot for the ankle, to provide torque perturbations. Time histories of the torques in Dorsi-Plantar flexion (DP) and Inversion-Eversion (IE) directions and the associated angles of the ankle were recorded. Linear time-invariant transfer functions between the measured torques and angles were estimated for the Anklebot and when the Anklebot was worn by a human subject. The difference between these impedance functions provided an estimate of the mechanical impedance of the ankle. High coherence was observed over a frequency range up to 30 Hz, indicating that this procedure yielded an accurate measure of ankle mechanical impedance in DP and IE directions. INTRODUCTION The mechanical impedance of the human ankle plays a major role in lower extremity function during locomotion such as maintaining the upright posture, shock absorption, lower-limb joint coordination during walking, steering, and propulsion on level ground and slopes – all functions which involve mechanical interaction of the foot with the contacting surface. One method for measuring ankle impedance is stochastic perturbation. The advantage of stochastic methods over steady-state procedures is that they provide a quantitative estimate without requiring any a-priori assumption about the order or dynamic structure of mechanical impedance. In particular, they do not require the common assumption that impedance is composed of inertia, damping and stiffness, but are applicable to more complex, higher-order dynamics. In prior work, Kirsch et. al. [1] estimated the ankle impedance in dorsiflexion direction by superimposing small stochastic motion perturbations during a large dorsiflexion motion

Extracted Key Phrases

5 Figures and Tables

Showing 1-10 of 14 extracted citations