
Abstract Introduction: The probability density function (PDF) of the surface electromyogram (sEMG) depends on contraction force. This dependence, however, has so far been investigated by having the subject generate force at a few fixed percentages of MVC. Here, we examined how the shape of the sEMG PDF changes with contraction force when this force was gradually increased from zero. Methods: Voluntary surface EMG signals were recorded from the vastus lateralis of healthy subjects as force was increased in a continuous manner vs. in a step-wise fashion. The sEMG filling process was examined by measuring the EMG filling factor, computed from the non-central moments of the rectified sEMG signal. Results: (1) For many subjects, as contraction force increased from 0 to 10% MVC, the sEMG PDF shape oscillated back and forth between the semi-degenerate and the Gaussian distribution. (2) The PDF-force relation varied greatly among subjects for forces between 0 and ~ 10% MVC, but this variability was largely reduced for forces above 10% MVC. (3) The pooled analysis showed that, as contraction force gradually increased, the sEMG PDF evolved rapidly from the semi-degenerate towards the Laplacian distribution from 0 to 5% MVC, and then more slowly from the Laplacian towards the Gaussian distribution for higher forces. Conclusions: The study demonstrated that the dependence of the sEMG PDF shape on contraction force can only be reliably assessed by gradually increasing force from zero, and not by performing a few constant-force contractions. The study also showed that the PDF-force relation differed greatly among individuals for contraction forces below 10% MVC, but this variability was largely reduced when force increased above 10% MVC.
Male, Adult, Gaussianity, Filling factor, Electromyography, Research, Signal Processing, Computer-Assisted, Surface EMG, Quadriceps Muscle, Biomechanical Phenomena, Young Adult, Interference pattern analysis, Medical technology, Humans, Female, R855-855.5, Probability density function (PDF), Muscle Contraction, Probability
Male, Adult, Gaussianity, Filling factor, Electromyography, Research, Signal Processing, Computer-Assisted, Surface EMG, Quadriceps Muscle, Biomechanical Phenomena, Young Adult, Interference pattern analysis, Medical technology, Humans, Female, R855-855.5, Probability density function (PDF), Muscle Contraction, Probability
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