IDEAS home Printed from https://ideas.repec.org/a/taf/gcmbxx/v13y2010i2p171-183.html
   My bibliography  Save this article

A computationally efficient optimisation-based method for parameter identification of kinematically determinate and over-determinate biomechanical systems

Author

Listed:
  • M.S. Andersen
  • M. Damsgaard
  • B. MacWilliams
  • J. Rasmussen

Abstract

This paper introduces a general optimisation-based method for identification of biomechanically relevant parameters in kinematically determinate and over-determinate systems from a given motion. The method is designed to find a set of parameters that is constant over the time frame of interest as well as the time-varying system coordinates, and it is particularly relevant for biomechanical motion analysis where the system parameters can be difficult to accurately determine by direct measurements. Although the parameter identification problem results in a large-scale optimisation problem, we show that, due to a special structure in the linearised Karush–Kuhn–Tucker optimality conditions, the solution can be found very efficiently. The method is applied to a set of test problems relevant for gait analysis. These involve determining the local coordinates of markers placed on the model, segment lengths and joint axes of rotation from both gait and range of motion experiments.

Suggested Citation

  • M.S. Andersen & M. Damsgaard & B. MacWilliams & J. Rasmussen, 2010. "A computationally efficient optimisation-based method for parameter identification of kinematically determinate and over-determinate biomechanical systems," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 13(2), pages 171-183.
    • Handle: RePEc:taf:gcmbxx:v:13:y:2010:i:2:p:171-183
    DOI: 10.1080/10255840903067080
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/10255840903067080
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/10255840903067080?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mark Tröster & Sarah Budde & Christophe Maufroy & Michael Skipper Andersen & John Rasmussen & Urs Schneider & Thomas Bauernhansl, 2022. "Biomechanical Analysis of Stoop and Free-Style Squat Lifting and Lowering with a Generic Back-Support Exoskeleton Model," IJERPH, MDPI, vol. 19(15), pages 1-16, July.
    2. Kevin Ball & Thomas Greiner, 2012. "A procedure to refine joint kinematic assessments: Functional Alignment," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 15(5), pages 487-500.
    3. Nicholas Ali & Michael Skipper Andersen & John Rasmussen & D. Gordon E. Robertson & Gholamreza Rouhi, 2014. "The application of musculoskeletal modeling to investigate gender bias in non-contact ACL injury rate during single-leg landings," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 17(14), pages 1602-1616, October.
    4. Vincent Richard & Giuliano Lamberto & Tung-Wu Lu & Aurelio Cappozzo & Raphaël Dumas, 2016. "Knee Kinematics Estimation Using Multi-Body Optimisation Embedding a Knee Joint Stiffness Matrix: A Feasibility Study," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-18, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:gcmbxx:v:13:y:2010:i:2:p:171-183. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/gcmb .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.