Resolving superimposed MUAPs using particle swarm optimization

IEEE Trans Biomed Eng. 2009 Mar;56(3):916-9. doi: 10.1109/TBME.2008.2005953. Epub 2008 Sep 30.

Abstract

This paper presents an algorithm to resolve superimposed action potentials encountered during the decomposition of electromyographic signals. The algorithm uses particle swarm optimization with a variety of features including randomization, crossover, and multiple swarms. In a simulation study involving realistic superpositions of two to five motor-unit action potentials, the algorithm had an accuracy of 98%.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Action Potentials / physiology
  • Algorithms*
  • Computer Simulation
  • Electromyography / methods*
  • Humans
  • Models, Neurological*
  • Motor Neurons / physiology*
  • Sensitivity and Specificity
  • Signal Processing, Computer-Assisted*