• DocumentCode
    471389
  • Title

    Decomposition of a Parallel Cascade Model of Ankle Stiffness Using Subspace Methods

  • Author

    Zhao, Y. ; Kearney, R.E.

  • Author_Institution
    Dept. of Biomed. Eng., McGill Univ., Montreal, Que.
  • fYear
    2006
  • fDate
    Aug. 30 2006-Sept. 3 2006
  • Firstpage
    296
  • Lastpage
    299
  • Abstract
    Joint stiffness, defined as the relation between the angular position of a joint and the torque acting about it, can be used to describe the dynamical behavior of the human ankle during posture and movement. Joint stiffness can be separated into intrinsic stiffness and reflex stiffness, which are modeled as a linear system and a Hammerstein system, respectively. A two-pathway parallel cascade model, with the intrinsic stiffness on one pathway and the reflex stiffness on the other, can be used to describe the joint stiffness. In this paper, we present a new method to separate the torque from each pathway from the total torque measurement. A subspace based system identification method is used to estimate the dynamics of each pathway directly from measured data without iteration. Simulation studies demonstrate that the method produces accurate results without the need of iteration
  • Keywords
    biomechanics; digital simulation; elasticity; medical computing; parameter estimation; physiological models; Hammerstein system; ankle dynamics simulation; human ankle stiffness; intrinsic stiffness; joint stiffness; linear system; reflex stiffness; subspace-based system identification method; two-pathway parallel cascade model; Biomedical measurements; Instruments; Iterative algorithms; Linear systems; MIMO; Muscles; Position measurement; State estimation; State-space methods; Torque measurement; ankle dynamics; decomposition; parallel cascade systems; subspace method;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
  • Conference_Location
    New York, NY
  • ISSN
    1557-170X
  • Print_ISBN
    1-4244-0032-5
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2006.259714
  • Filename
    4461743