A data dependent computer algorithm for the detection of muscle activity onset and offset from EMG recordings

Electroencephalogr Clin Neurophysiol. 1998 Apr;109(2):119-23. doi: 10.1016/s0924-980x(97)00066-0.

Abstract

This paper describes modifications to an algorithm presented by Marple-Horvat and Gilbey (1992) for identifying bursts of muscle activity in electromyographical (EMG) recordings. Our efforts to apply their algorithm to spontaneously moving infants and toddlers resulted in limited success. The modified algorithm makes several parameters dependent on the data being analyzed; these changes enabled it to analyze a variety of EMG recordings more effectively. The original algorithm had a success rate (correctly identified bursts) of 62.9% and combined error rate (number of insertions and deletions) of 73.0% when applied to an independent test data set. The modified algorithm displayed a success rate of 85.4% and combined error rate of 23.6%.

Publication types

  • Clinical Trial
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Algorithms*
  • Child, Preschool
  • Data Interpretation, Statistical
  • Electromyography / statistics & numerical data*
  • Humans
  • Infant
  • Jaw / physiology
  • Microcomputers
  • Muscle, Skeletal / physiology*
  • Reference Values