• DocumentCode
    3540594
  • Title

    Selection of optimization methods for estimating muscle parameters during walking

  • Author

    Wang, Weijie

  • Author_Institution
    Dept. of Orthopedic & Trauma Surg., Univ. of Dundee, Dundee, UK
  • fYear
    2009
  • fDate
    16-19 Aug. 2009
  • Abstract
    In the computer simulation of musculoskeletal human model during walking, mathematical optimization is used to estimate muscle parameters, e.g. the muscle force, work and power. Though there are many mathematical optimization methods available, some of them are suitable for the estimate of muscle parameters in simulations and some not. This study aimed to compare several main optimization methods in terms of the feasibility and possibilities in calculating muscle parameters in musculoskeletal modeling. The results showed that different optimization methods can produce different muscle force patterns. Using electromyography obtained from experiment as the criteria, it was found that the min-max minimization or its combination with other methods are better than the genetic algorithm and pattern search methods in terms of the similarity between the simulated muscle forces and the experimental electromyography patterns.
  • Keywords
    electromyography; gait analysis; minimax techniques; parameter estimation; electromyography; genetic algorithm; mathematical optimization; min-max minimization; muscle force pattern; muscle parameters estimation; musculoskeletal human model; optimization method selection; pattern search; walking; Computational modeling; Computer simulation; Electromyography; Humans; Legged locomotion; Mathematical model; Muscles; Musculoskeletal system; Optimization methods; Parameter estimation; Electromyography; Muscle Force; Optimization; Simulation; Walking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronic Measurement & Instruments, 2009. ICEMI '09. 9th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-3863-1
  • Electronic_ISBN
    978-1-4244-3864-8
  • Type

    conf

  • DOI
    10.1109/ICEMI.2009.5274024
  • Filename
    5274024