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Interindividual variability of electromyographic patterns and pedal force profiles in trained cyclists.


The aim of this study was to determine whether high inter-individual variability of the electromyographic (EMG) patterns during pedaling is accompanied by variability in the pedal force application patterns. Eleven male experienced cyclists were tested at two submaximal power outputs (150 and 250 W). Pedal force components (effective and total forces) and index of mechanical effectiveness were measured continuously using instrumented pedals and were synchronized with surface electromyography signals measured in ten lower limb muscles. The intersubject variability of EMG and mechanical patterns was assessed using standard deviation, mean deviation, variance ratio and coefficient of cross-correlation (_R(0), with lag time = 0). The results demonstrated a high intersubject variability of EMG patterns at both exercise intensities for biarticular muscles as a whole (and especially for Gastrocnemius lateralis and Rectus femoris) and for one monoarticular muscle (Tibialis anterior). However, this heterogeneity of EMG patterns is not accompanied by a so high intersubject variability in pedal force application patterns. A very low variability in the three mechanical profiles (effective force, total force and index of mechanical effectiveness) was obtained in the propulsive downstroke phase, although a greater variability in these mechanical patterns was found during upstroke and around the top dead center, and at 250 W when compared to 150 W. Overall, these results provide additional evidence for redundancy in the neuromuscular system.


  • Publisher Full Text
  • Authors

    Hug F, Drouet JM, Champoux Y, Couturier A, Dorel S


    European journal of applied physiology 104:4 2008 Nov pg 667-78


    Biomechanical Phenomena
    Models, Biological
    Muscle Contraction
    Muscle Strength
    Muscle, Skeletal
    Observer Variation
    Young Adult

    Pub Type(s)

    Journal Article
    Research Support, Non-U.S. Gov't



    PubMed ID