Inter-operator agreement in decomposition of motor unit firings from high-density surface EMG

J Electromyogr Kinesiol. 2008 Aug;18(4):652-61. doi: 10.1016/j.jelekin.2007.01.010. Epub 2007 Mar 23.

Abstract

High-density surface EMG can be used to obtain a spatially selective representation of several motor unit action potentials. Recently, a decomposition of the signal into the underlying motor neuron firing patterns has been described. The reliability of the algorithm has not yet been tested. Eleven healthy subjects participated. High-density surface EMG was recorded from the vastus lateralis muscle during an isometric knee extension. Two independent operators analyzed the signals. After operator-supervised cluster analysis of spikes, motor unit action potential templates were constructed and an automatic template matching was performed. The decomposition was adjusted by hand. Agreement between operators was calculated for the number of coincident firings. Bland-Altman plots of peak-to-peak amplitude were constructed and limits of agreement were calculated. For completely decomposed motor unit action potential trains the between-operator agreement of firing events was very high. The peak-to-peak amplitude of monopolar motor unit action potentials was 115microV (SD 74microV). The agreement was within 3microV and independent of amplitude. With partial decomposition agreement within 26microV was achieved. For bipolarly derived motor unit action potentials the peak-to-peak amplitude was 54microV (SD 49microV), the agreement was within 3microV. Only for recordings obtained from a force level below 5% of the maximum voluntary contraction full decomposition was possible. It was concluded that when full decomposition is achieved, two independent operators are likely to arrive at nearly identical firing patterns.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Action Potentials
  • Adult
  • Electromyography*
  • Female
  • Humans
  • Isometric Contraction / physiology
  • Male
  • Motor Neurons / physiology*
  • Observer Variation