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Journal of Applied Physiology, Vol 78, Issue 3 814-822, Copyright © 1995 by American Physiological Society
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C. L. Webber Jr, M. A. Schmidt and J. M. Walsh
Department of Physiology, Loyola University of Chicago, Stritch School of Medicine, Illinois, USA.
The summed electrical discharges generated by a contracting skeletal muscle constitute a dynamic system conveying electromyographic (EMG) information indicative of muscle physiological status. "Steady states" of activity can be achieved with light loads, but with heavy loads the dynamic system experiences continuous status transitions that culminate in task failure. The present study was designed to assess the applicability of two mathematical tools, one linear and the other nonlinear, in addressing the time course of EMG alterations under different loading challenges. Surface EMGs of the biceps brachii muscle were recorded from 14 healthy human volunteers during light and heavy loadings, and task failure occurred at varying times among the subjects. Digitized EMG signals were analyzed by linear spectral analysis (fast Fourier transform) and nonlinear recurrence-plot analysis. With light loading, computed variables from both analyses gave "quasi-steady-state" values over time, with recurrence-plot analysis having the higher variance. With heavy loading, the nonlinear variable (%determinism) increased sooner and exhibited larger changes from control values than decreases in the linear variable (spectral center frequency). Experimental results support the conclusion that both analyses can be combined to give a fuller assessment of the biceps EMG during light or heavy loading. Implications for the detection of muscular fatigue are discussed.
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