Subspace method decomposition and identification of the parallel-cascade model of ankle joint stiffness: Theory and simulation

摘要

This paper describes a state-space representation of the parallel-cascade model of ankle joint stiffness whose parameters are directly related to the underlying dynamics of the system. It then proposes a two step subspace method to identify this model. In the first step, the intrinsic stiffness is estimated using proper orthogonal projections. In the second step, the reflexive pathway is estimated by iterating between estimating its nonlinear and linear components. The identified models can be easily converted to continuous-time for physiological interpretation. Monte-Carlo studies using simulated data which replicate closely the experimental conditions, were used to compare the performance of the new method with the previous parallel-cascade, and subspace methods. The new method is more robust to noise and is guaranteed to converge.