Abstract
This paper presents a robust time-varying identification method, Ezponentially Weighted Least Squares (EWLS), and its application to the identification of human elbow joint dynamics under slow time varying conditions. The method requires only a single trial to extract all of the parameters in the model. In the experiments, a pseudorandom binary force perturbation (PRBS) was applied to the elbow. Both stiffness and viscous parameters increased with co-contraction in posture. During movement the stiffness was lower than that in posture.
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