Spatial reorganisation of muscle activity correlates with change in tangential force variability during isometric contractions

Abstract

The aim of this study was to quantify the effects of spatial reorganisation of muscle activity on task-related and tangential components of force variability during sustained contractions. Three-dimensional forces were measured from isometric elbow flexion during submaximal contractions (50 s, 5-50% of maximal voluntary contraction (MVC)) and total excursion of the centre of pressure was extracted. Spatial electromyographic (EMG) activity was recorded from the biceps brachii muscle. The centroids of the root mean square (RMS) EMG and normalised mutual information (NMI) maps were computed to assess spatial muscle activity and spatial relationship between EMG and task-related force variability, respectively. Result showed that difference between the position of the centroids at the beginning and at the end of the contraction of the RMS EMG and the NMI maps were different in the medial-lateral direction (P < 0.05), reflecting that muscle regions modulate their activity without necessarily modulating the contribution to the taskrelated force variability over time. Moreover, this difference between shifts of the centroids was positively correlated with the total excursion of the centre of pressure at the higher levels of contractions (>30% MVC, R2 > 0.30, P < 0.05), suggesting that changes in spatial muscle activity could impact on the modulation of tangential forces. Therefore, withinmuscle adaptations do not necessarily increase force variability, and this interaction can be quantified by analysing the RMS EMG and the NMI map centroids.3

Test-Retest Reliability of Trunk Motor Variability Measured By Large-Array Surface Electromyography

“…Both of these variables, especially the centroid, were extensively used in fundamental EMG researches. 2,5,7,18,19 However, this study is the first one that analyzed the reliability of these variables. The dispersion variable representing the area of the centroid's displacement for each phase showed moderate to strong correlations at the beginning (P1) and during the later stages of muscle fatigue (P4, P5) and very strong correlations at the exhaustion phase (P6).…”

Modulation of motor variability related to experimental muscle pain during elbow-flexion contractions

“…The selected period avoided errors in the initial part of the contraction. Force standard deviation (FSD) was calculated to quantify force variability in the task-related direction, and tangential force variability was estimated using the total excursion of the center of pressure (CoP) (Mista et al, 2013;Salomoni & Graven-Nielsen, 2012a, 2012b. In addition to the CoP, a two-dimensional histogram of tangential force components was derived using 5 bins to represent the range of the force.…”

“…Center of gravity and entropy (histogram: 256 bins) were derived from grid EMG recordings to assess within-muscle activity redistribution in the m. biceps brachii (Farina, Leclerc, Arendt-Nielsen, Buttelli, & Madeleine, 2008;Mista et al, 2013;Samani & Holtermann, 2010). Furthermore, root mean square (RMS) EMG amplitudes were assessed in non-overlapping windows of 300 ms for each bipolar recording and for each channel of the grid during the selected period.…”

“…Visual feedback was presented through a two-dimensional plot on a computer screen (Mista, Salomoni, & Graven-Nielsen, 2013). Force components parallel to the axial plane of the wrist ( Fig.…”

Normalised Mutual Information of High-Density Surface Electromyography during Muscle Fatigue

“…Unlike correlation based measures, MI can be used to measure both linear and nonlinear relationships [29]. MI has recently been used to assess dependences between sEMG signals [30][31][32][33][34]. However, because MI quantifies the amount of shared information between two variables, its value is relative to the total information content of the variables and its maximum value is defined by the variable entropies.…”