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Trunk extensor endurance and its relationship to electromyogram parameters

J H van Dieën1, H H Oude Vrielink, A F Housheer

  • 1Workstudy and Ergonomics Department, Institute of Agricultural Engineering (IMAG-DLO), Wageningen, The Netherlands.

European Journal of Applied Physiology and Occupational Physiology
|January 1, 1993
PubMed
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Muscle fatigue in trunk extensors can be predicted using electromyogram (EMG) parameters. Specifically, changes in mean power frequency (MPF) and EMG amplitude (RA-EMG) over time correlate with endurance, offering better predictions than force alone.

Area of Science:

  • Biomechanics
  • Neuroscience
  • Exercise Physiology

Background:

  • Muscle fatigue significantly impacts performance and injury risk.
  • Electromyography (EMG) provides insights into muscle activation and fatigue.
  • Trunk extensor muscles are crucial for posture and spinal stability.

Purpose of the Study:

  • To investigate the relationship between EMG parameters and trunk extensor muscle fatigue.
  • To determine if EMG parameters can predict muscle endurance.
  • To compare the predictive power of EMG parameters versus relative force for endurance.

Main Methods:

  • Nine subjects performed isometric trunk extensions at 25% and 40% maximal voluntary contraction.
  • EMG signals from longissimus thoracis, iliocostalis lumborum, multifidus, and latissimus dorsi were recorded.

Related Experiment Videos

  • Analysis focused on changes in EMG amplitude (RA-EMG) and mean power frequency (MPF) over time.

    • Main Results:

    • RA-EMG increased, while MPF decreased consistently during contractions.
    • Time constants of RA-EMG and MPF changes correlated with endurance time.
    • EMG parameters provided better endurance prediction than relative force.
    • MPF changes in multifidus and longissimus muscles were strong endurance predictors.

    Conclusions:

    • EMG parameters, particularly MPF changes, are effective predictors of trunk extensor muscle fatigue and endurance.
    • Monitoring EMG spectral shifts can indicate reduced muscle activation variability during fatigue.
    • This research offers valuable insights for assessing and managing muscle fatigue in clinical and athletic settings.