The steady-state passive joint moment was considered as a nonlinear elasticity in the past. However, we found that it was path dependent and the estimation error could be large if the commonly used path-independent functions were adopted. The aim of this study was to develop a model to describe the movement history-dependent passive moment in the steady state. The steadystate passive ankle moments of the rabbit were measured by a series of ramp-and-hold angle changes (stairway angle trajectory). A customized discrete Preisach model was constructed and a commonly adopted double-exponential function was also implemented. Two sets of data with different angle paths (major loop and inward loop trajectories) were acquired for model validation. The performance of the two models was compared. The results showed that the proposed model could accurately estimate the steady-state passive moment for both sets of validation data. The estimated error of the proposed model was approximately 50% smaller than that of the double-exponential function approach. It is expected that this new approach, by reducing the error of estimating passive joint moment, may contribute to the active control of joint moments.
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