Decoding individuated finger flexions with Implantable MyoElectric Sensors

Justin J. Baker, Dimitri Yatsenko, Jack F. Schorsch, Glenn A. DeMichele, Phil R. Troyk, Douglas T. Hutchinson, Richard F.F. Weir, Gregory Clark, Bradley Greger

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

11 Scopus citations

Abstract

We trained a rhesus monkey to perform randomly cued, individuated finger flexions of the thumb, index, and middle finger. Nine Implantable MyoElectric Sensors (IMES) were then surgically implanted into the finger muscles of the monkey's forearm, without any observable adverse chronic effects. Using an inductive link, we wirelessly recorded EMG from the IMES as the monkey performed a finger flexion task. A principal components analysis (PCA) based algorithm was used to decode which finger switch was pressed based on the recorded EMG. This algorithm correctly decoded which finger was moved 89% of the time. These results demonstrate that IMES offer a safe and highly promising approach for providing intuitive, dexterous control of artificial limbs and hands after amputation.

Original languageEnglish (US)
Title of host publicationProceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
Pages193-196
Number of pages4
StatePublished - Dec 1 2008
Externally publishedYes
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

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ASJC Scopus subject areas

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

Cite this

Baker, J. J., Yatsenko, D., Schorsch, J. F., DeMichele, G. A., Troyk, P. R., Hutchinson, D. T., Weir, R. F. F., Clark, G., & Greger, B. (2008). Decoding individuated finger flexions with Implantable MyoElectric Sensors. In Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 (pp. 193-196). [4649123] (Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology").