• DocumentCode
    2589336
  • Title

    Implementing Feedback Error Learning for FES control

  • Author

    Koike, Yuka ; Gonzalez, Jose ; Gomez, Jose ; Yu, Wenwei

  • Author_Institution
    Med. Syst. Eng. Dept., Chiba Univ., Chiba, Japan
  • Volume
    3
  • fYear
    2011
  • fDate
    15-17 Oct. 2011
  • Firstpage
    1324
  • Lastpage
    1328
  • Abstract
    Walking assist using Functional Electrical Stimulation (FES) has been studied for a quite long time to help paraplegic persons overcome their walking impairment. One of the problems of these devices is how to cope with individual dependent, time-varying, and nonlinear user´s characteristics and external disturbances. In this study, Feedback Error Learning (FEL), a scheme that integrates feedback and feedforward control, was applied to FES control. As a first step, an inverted-pendulum model was used to examine the usefulness of this scheme. Next, the control of a swinging motion, using a leg model simulation, was performed. After the verification in the simulation models, an FES experiment was to investigate the applicability of this system. The data obtained from the FES experiments were used to construct a new simulation model for investigating the effect of FES in different condition. The results showed that, usability of the FEL scheme for different FES control strategies.
  • Keywords
    bioelectric phenomena; feedback; feedforward; gait analysis; learning (artificial intelligence); medical control systems; neuromuscular stimulation; FES control; feedback error learning; feedforward control; functional electrical stimulation; inverted pendulum model; leg model simulation; paraplegic persons; swinging motion control; walking impairment; Artificial neural networks; Feedback control; Humans; Mathematical model; Muscles; Trajectory; FES; Feedback Error Learning; neural network; rehabilitation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Engineering and Informatics (BMEI), 2011 4th International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-9351-7
  • Type

    conf

  • DOI
    10.1109/BMEI.2011.6098623
  • Filename
    6098623