Cookies Policy

This site uses cookies. By continuing to browse the site you are agreeing to our use of cookies.

I accept this policy

Find out more here

Computer-aided generation of stimulation data and model identification for functional electrical stimulation (FES) control of lower extremities

No metrics data to plot.
The attempt to load metrics for this article has failed.
The attempt to plot a graph for these metrics has failed.
The full text of this article is not currently available.

Brill’s MyBook program is exclusively available on BrillOnline Books and Journals. Students and scholars affiliated with an institution that has purchased a Brill E-Book on the BrillOnline platform automatically have access to the MyBook option for the title(s) acquired by the Library. Brill MyBook is a print-on-demand paperback copy which is sold at a favorably uniform low price.

Access this article

+ Tax (if applicable)
Add to Favorites
You must be logged in to use this functionality

Standard stimulation data for unassisted standing up of paraplegic patients was generated by dynamic optimization linked with model simulation, to overcome the difficulties in the present electromyogram (EMG)-based method. The generated stimulation data were roughly in agreement with the normal subjects' EMG. From these, it is suggested that the 'model-based' method is useful as an alternative of the 'EMG-based method'. The same technique can be applied to generation of patient-specific stimulation data once the musculoskeletal system of a patient is properly identified. The musculoskeletal system must be identified from data taken from simple and non-invasive experiments for the identification method to be practically acceptable. We developed a musculoskeletal model and systematic identification protocols for this purpose. They were validated for the vastus lateralis muscle at the knee joint. The identification was successful and the predicted joint angle trajectories closely matched the experimental data. This implies that the model-based generation of patient-specific stimulation data is possible.


Full text loading...


Data & Media loading...

Article metrics loading...



Can't access your account?
  • Tools

  • Add to Favorites
  • Printable version
  • Email this page
  • Subscribe to ToC alert
  • Get permissions
  • Recommend to your library

    You must fill out fields marked with: *

    Librarian details
    Your details
    Why are you recommending this title?
    Select reason:
    Frontiers of Medical and Biological Engineering — Recommend this title to your library
  • Export citations
  • Key

  • Full access
  • Open Access
  • Partial/No accessInformation