Recursive Filter Design for Estimating Time Varying Multijoint Human Arm Viscoelasticity

The time varying human multijoint arm dynamics can be modeled by two factors, simplified musculoskeletal dynamics and the uncertainty factor consisting of measurement noises and modeling error of a rigid body dynamics. In some cases, the uncertainty factor may not be Gaussian; the Kalman filter is no longer the optimal filter. In this paper, for the non-Gaussian environment, a recursive filter design method for estimating time varying human multijoint arm viscoelasticity during the arm is moving is presented. The method is based on a score function approach associated with D U factorization algorithm and equivalent noise technique for multiple innovations process. The proposed method for an experimentbased human arm model provides greater accuracy and robustness in capturing texture information of the model under the case of non-Gaussian noises, while the performance of standard Kalman filter degrades significantly.