Myoelectric Prostheses and Targeted Reinnervation

Levi Hargrove*, Erik Scheme, Kevin Englehart

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Scopus citations

Abstract

A number of factors have led to a resurgence of myoelectric control research since the early 2000s. First, low-power electronics have developed to the point where multichannel pattern recognition algorithms can readily be implemented on an embedded system. Second, due to a large number of high-level amputees resulting from recent military conflicts, governments have initiated well-funded programs to improve neural interfaces for prosthetics. Finally, new and innovative neural-machine interfaces, such as targeted muscle reinnervation (TMR), have been developed to provide a rich source of neural information from which control signals can be derived. This chapter provides an overview of existing myoelectric control strategies, highlighting the benefits and limitations of both conventional and pattern recognition techniques, and TMR. The chapter concludes with a summary of exciting emerging technologies that have the potential to further enhance the field of myoelectric control.

Original languageEnglish (US)
Title of host publicationIntroduction to Neural Engineering for Motor Rehabilitation
PublisherWiley-IEEE Press
Pages291-310
Number of pages20
ISBN (Electronic)9781118628522
ISBN (Print)9780470916735
DOIs
StatePublished - Jul 15 2013

Keywords

  • Multichannel pattern recognition algorithms
  • Myoelectric prostheses
  • Neural-machine interfaces
  • Targeted muscle reinnervation (TMR)

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)

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