Continuous decoding of finger position from surface EMG signals for the control of powered prostheses

Ryan J. Smith, Francesco Tenore, David Huberdeau, Ralph Etienne-Cummings, Nitish V. Thakor

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

Abstract

As development toward multi-fingered dexterous prosthetic hands continues, there is a growing need for more flexible and intuitive control schemes. Through the use of generalized electrode placement and well-established methods of pattern recognition, we have developed a basis for asynchronous decoding of finger positions. With the present method, correlations as large as 0.91 and mean overall decoding errors of ∼11% have been achieved with average decoding errors of between decoded and actual conformation of the metacarpophalangeal joints of individual fingers. It is hoped that these results will serve as a foundation from which to encourage further investigation into more intuitive methods of myoelectric control of powered upper limb prostheses.

Original languageEnglish (US)
Title of host publicationProceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
Pages197-200
Number of pages4
StatePublished - Dec 1 2008
Event30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - Vancouver, BC, Canada
Duration: Aug 20 2008Aug 25 2008

Publication series

NameProceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology"

Other

Other30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
CountryCanada
CityVancouver, BC
Period8/20/088/25/08

ASJC Scopus subject areas

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

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