Are the myoelectric manifestations of fatigue distributed regionally in the human medial gastrocnemius muscle?

Alessio Gallina, Roberto Merletti, Taian M.M. Vieira

Research output: Contribution to journalArticlepeer-review

37 Citations (Scopus)

Abstract

Myoelectric fatigue typically manifests as variations in the amplitude and spectrum of surface electromyograms (EMGs). Interestingly, these variations seem to be represented locally in different muscles. In this study, we ask whether such a regional distribution of myoelectric fatigue extends to the medial gastrocnemius (MG) muscle. If the MG muscle is activated locally during fatiguing contractions, or if the most fatigable MG fibers are located at distinct muscle regions, then, the myoelectric manifestations of MG fatigue are expected to appear locally in a grid of surface electrodes. With a matrix of surface electrodes (7 × 15 single-differential EMGs) we show that myoelectric fatigue, indeed, manifests regionally in the MG muscle of 12 subjects, who exerted intermittent, fatiguing plantar flections at 50% of their maximal effort. Contrary to the root mean square amplitude, the median frequency of surface EMGs varied consistently across subjects throughout the plantar flections (P = 0.002). On average, changes in EMG spectrum were represented at 78–93 (interquartile interval) out of the 105 channels in the matrix, though with different degrees across channels. For all participants, about 29% of the channels detected significantly greater reductions in median frequency when compared to all channels in the matrix (P < 0.003). Strikingly, these channels were not sparsely distributed; they rather occupied localized skin regions across subjects. Physiologically, our results suggest that, during sub-maximal fatiguing tasks, myoelectric manifestations of MG fatigue are represented in spatially localized muscle regions. Technically, the possibility of studying myoelectric fatigue in the MG muscle appears to depend on the electrode location.
Original languageEnglish
JournalJournal of Electromyography and Kinesiology
Volume21
Issue number6
DOIs
Publication statusPublished - Dec 2011

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