Title :
Identification of time-varying joint dynamics using wavelets
Author :
Wang, Guangzhi ; Zhang, Li-Qun
Author_Institution :
Northwestern Univ., Chicago, IL, USA
fDate :
29 Oct-1 Nov 1998
Abstract :
A wavelet-based method was investigated to identify time-varying properties of joint dynamics. Wavelet decomposition was used to expand each time-varying coefficient of an autoregressive with exogenous input (ARX) model into a finite set of basis sequences, and singular value decomposition was used to obtain more robust parameter estimates of the expansion. With a set of well-selected basis, the time-varying ARX coefficients could be well approximated by a combination of a small number of basis sequences, which simplified the identification of the time-varying parameters. The estimated time-varying ARX parameters were converted to a second-order continuous-time system characterizing joint dynamics with joint stiffness, viscosity and limb inertia. Simulation based on a time-varying joint dynamics model showed that the method tracked the time-varying system parameter closely
Keywords :
biomechanics; elasticity; physiological models; singular value decomposition; time-varying systems; viscosity; wavelet transforms; basis sequences; exogenous input model; joint mechanics; joint stiffness; joint viscosity; limb inertia; second-order continuous-time system; time-varying coefficient; time-varying joint dynamics identification; time-varying joint dynamics model; Humans; Muscles; Orthopedic surgery; Parameter estimation; Robustness; Singular value decomposition; System identification; Time varying systems; Torque; Viscosity;
Conference_Titel :
Engineering in Medicine and Biology Society, 1998. Proceedings of the 20th Annual International Conference of the IEEE
Conference_Location :
Hong Kong
Print_ISBN :
0-7803-5164-9
DOI :
10.1109/IEMBS.1998.746132