Advanced User Interfaces for Upper Limb Functional Electrical Stimulation

Elaine A. Corbett*, Christian Ethier, Emily R. Oby, Konrad Paul Kording, Eric Perreault, Lee E Miller

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Spinal cord injury (SCI) paralyzes approximately 12,000 people each year in the United States. Individuals with an injury at and above the sixth cervical vertebra (C6) lose function in the upper and lower limbs. To provide greater independence to this population, the restoration of reaching and grasping movements is critically important. Functional electrical stimulation (FES) is currently the only clinical approach for reanimating paralyzed muscles. The chapter starts by reviewing existing technologies for obtaining a control signal that is usable for a FES neuroprosthesis. This is followed by a discussion of the promise that recent advances in brain-machine interfaces (BMIs) hold for more natural user interfaces. Differences in the information content of potential signal sources suggest that enhanced control signals may be generated through an efficient combination of the available sources from each individual. Finally, the chapter discusses the relation between off-line decoder accuracy and online user performance.

Original languageEnglish (US)
Title of host publicationIntroduction to Neural Engineering for Motor Rehabilitation
PublisherWiley-IEEE Press
Pages377-400
Number of pages24
ISBN (Electronic)9781118628522
ISBN (Print)9780470916735
DOIs
StatePublished - Jul 15 2013

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Keywords

  • Brain-machine interfaces (BMIs)
  • Cerebral cortex
  • Closed-loop control
  • Combining signal sources
  • Functional electrical stimulation (FES)
  • Neuroprosthesis

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)

Cite this

Corbett, E. A., Ethier, C., Oby, E. R., Kording, K. P., Perreault, E., & Miller, L. E. (2013). Advanced User Interfaces for Upper Limb Functional Electrical Stimulation. In Introduction to Neural Engineering for Motor Rehabilitation (pp. 377-400). Wiley-IEEE Press. https://doi.org/10.1002/9781118628522.ch19