The effects of electrode size and orientation on the sensitivity of myoelectric pattern recognition systems to electrode shift

Aaron J. Young*, Levi J. Hargrove, Todd A. Kuiken

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

215 Scopus citations

Abstract

Myoelectric pattern recognition systems for prosthesis control are often studied in controlled laboratory settings, but obstacles remain to be addressed before they are clinically viable. One important obstacle is the difficulty of maintaining system usability with socket misalignment. Misalignment inevitably occurs during prosthesis donning and doffing, producing a shift in electrode contact locations. We investigated how the size of the electrode detection surface and the placement of electrode poles (electrode orientation) affected system robustness with electrode shift. Electrodes oriented parallel to muscle fibers outperformed electrodes oriented perpendicular to muscle fibers in both shift and no-shift conditions (p < 0.01). Another finding was the significant difference (p < 0.01) in performance for the direction of electrode shift. Shifts perpendicular to the muscle fibers reduced classification accuracy and real-time controllability much more than shifts parallel to the muscle fibers. Increasing the size of the electrode detection surface was found to help reduce classification accuracy sensitivity to electrode shifts in a direction perpendicular to the muscle fibers but did not improve the real-time controllability of the pattern recognition system. One clinically important result was that a combination of longitudinal and transverse electrodes yielded high controllability with and without electrode shift using only four physical electrode pole locations.

Original languageEnglish (US)
Article number5872014
Pages (from-to)2537-2544
Number of pages8
JournalIEEE Transactions on Biomedical Engineering
Volume58
Issue number9
DOIs
StatePublished - Sep 2011

Keywords

  • Electrode shift
  • electromyography (EMG)
  • pattern recognition
  • virtual reality prosthesis control

ASJC Scopus subject areas

  • Biomedical Engineering

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