Subspace identification method for ankle mechanics

Author

Kukreja, S.L. ; Haverkamp, B.R.J. ; Westwick, D.T. ; Kearney, R.E. ; Galiana, H.L. ; Verhaegen, M.H.

Author_Institution

Dept. of Biomed. Eng., McGill Univ., Montreal, Que., Canada

Volume

2

fYear

1995

fDate

20-23 Sep 1995

Firstpage

1413

Abstract

Presents results a new algorithm for modeling biological systems using a state space approach. One of the MIMO Output-Error State Space identification (MOESP) family of algorithms (see M. Verhaegen and P. Dewilde, Int. J. Control, vol. 55, no. 5, p. 1187-1210, 1992) has been adapted to model the linear part of human ankle mechanics. A mixed causal/anti-causal state space model was calculated to examine the relationship between torque and position of the ankle. Simulated and real data are used to show that the method yields parametric models for ankle mechanics that describe behavior as well as nonparametric models. However, the parametric models obtained using the MOESP identification method have many fewer parameters

Keywords

biomechanics; identification; physiological models; MIMO output-error state space identification algorithms family; biological systems modeling algorithm; human ankle mechanics; mixed causal/anti-causal state space model; nonparametric models; parametric models; subspace identification method; torque-position relationship; Biological system modeling; Biological systems; Humans; Inverse problems; Laboratories; Parametric statistics; Robustness; Space technology; State-space methods; Torque;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 1995., IEEE 17th Annual Conference

Conference_Location

Montreal, Que.

Print_ISBN

0-7803-2475-7

Type

conf

DOI

10.1109/IEMBS.1995.579753

Filename

579753