Electromyogram and force fluctuation during different linearly varying isometric motor tasks

J Electromyogr Kinesiol. 2010 Aug;20(4):732-41. doi: 10.1016/j.jelekin.2010.03.005. Epub 2010 Apr 14.

Abstract

The purpose of this work was to verify if deviation from the mirror-like behaviour of the motor units activation strategy (MUAS) and de-activation strategy (MUDS) and the degree of the error of the motor control system, during consecutive linearly increasing-decreasing isometric tension tasks, depend on the maximum reached tension and/or on the rate of tension changes. In 12 male subjects the surface EMG and force produced by the first dorsal interosseus activity were recorded during two (a and b) trapezoid isometric contractions with different plateau (a: 50% maximal voluntary contraction (MVC) and b: 100% MVC) and rate of tension changes (a: 6.7% MVC/s and b: 13.3% MVC/s) during up-going (UGR) and down-going (DGR) ramps. Ten steps (ST) 6s long at 5, 10, 20, 30, 40, 50, 60, 70, 80 and 90% MVC were also recorded. The root mean square (RMS) and mean frequency (MF) from EMG and the relative error of actual force output with respect to the target (% ERR) were computed. The EMG-RMS/% MVC and EMG-MF/% MVC relationships were not overlapped when the ST and DGR as well as the UGR and DGR data were compared. The % ERR/% MVC relationships during a and b contractions differed from ST data only below 20% MVC. It can be concluded that MUAS and MUDS are not mirroring one each other because MU recruitment or de-recruitment threshold may be influenced by the maximum effort and by the % MVC/s of UGR and DGR. The role of MUs mechanical and/or central nervous system hysteresis on force decrement control is discussed.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Biomechanical Phenomena
  • Electromyography*
  • Fingers
  • Humans
  • Isometric Contraction / physiology*
  • Male
  • Motor Neurons / physiology*
  • Muscle, Skeletal / innervation
  • Muscle, Skeletal / physiology*
  • Recruitment, Neurophysiological*
  • Signal Processing, Computer-Assisted