Adaptive user-specified control of movements with Functional Neuromuscular Stimulation

Pankaj Kataria, James J. Abbas

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Functional Neuromuscular Stimulation (FNS) systems can provide a person with thoracic level spinal cord injury the ability to stand, with limited maneuverability. We aim to develop a system that enhances maneuvering ability by providing the user with control of stimulation to adjust limb position, but nonlinear system properties make it difficult for the user to control limb position. In this work, we have implemented an adaptive neural network controller to linearize the system input/output properties as seen by the user. We have tested our controller on a model of a swinging lower leg that is controlled via stimulation. The results of a series of simulations indicate that the adaptive controller can successfully linearize input/output properties for a wide range of model parameters and also that the controller performs well over a wide range of values of learning rate and network size.

Original languageEnglish (US)
Title of host publicationAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
PublisherIEEE
Pages604
Number of pages1
ISBN (Print)0780356756
StatePublished - 1999
Externally publishedYes
EventProceedings of the 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Fall Meeting of the Biomedical Engineering Society (1st Joint BMES / EMBS) - Atlanta, GA, USA
Duration: Oct 13 1999Oct 16 1999

Publication series

NameAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume1
ISSN (Print)0589-1019

Other

OtherProceedings of the 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Fall Meeting of the Biomedical Engineering Society (1st Joint BMES / EMBS)
CityAtlanta, GA, USA
Period10/13/9910/16/99

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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