Does normalization of voluntary EMG amplitude to M_MAX account for the influence of electrode location and adiposity?

Abstract

Voluntary surface electromyography (sEMG) amplitude is known to be influenced by both electrode position and subcutaneous adipose tissue thickness, and these factors likely compromise both between- and within-individual comparisons. Normalization of voluntary sEMG amplitude to evoked maximum M-wave parameters (M peak-to-peak [P-P] and Area) may remove the influence of electrode position and subcutaneous tissue thickness. The purpose of this study was to: (a) assess the influence of electrode position on voluntary, evoked (M P-P and Area), and normalized sEMG measurements across the surface of the vastus lateralis (VL; experiment 1: n = 10); and (b) investigate if M normalization removes the confounding influence of subcutaneous tissue thickness [muscle-electrode distance (MED) from ultrasound imaging] on sEMG amplitude (experiment 2; n = 41). Healthy young men performed maximum voluntary contractions (MVCs) and evoked twitch contractions during both experiments. Experiment 1: voluntary sEMG during MVCs was influenced by electrode location (P ≤ 0.046, ES≥1.49 "large"), but when normalized to M P-P showed no differences between VL sites (P = 0.929) which was not the case when normalized to M Area (P < 0.004). Experiment 2: voluntary sEMG amplitude was related to MED, which explained 31%-38% of the variance. Normalization of voluntary sEMG amplitude to M P-P or M Area reduced but did not consistently remove the influence of MED which still explained up to 16% (M P-P) and 23% (M Area) of the variance. In conclusion, M P-P was the better normalization parameter for removing the influence of electrode location and substantially reduced but did not consistently remove the influence of subcutaneous adiposity.

Mechanical and morphological determinants of peak power output in elite cyclists

“…Data in this experiment indicated that peak muscle activation recorded with surface EMG exhibited no relationship with PPO and thus was not a meaningful determinant of PPO in elite cyclists. Therefore, it is possible that more accurate and sensitive measures of neuromuscular activation, perhaps including surface EMG from more muscles and multiple sites per muscle, as well as alternative normalization techniques, might reveal a greater role for activation in determining PPO. However, given that muscle morphology explained 87% of the variability in PPO, the unexplained variance was relatively small (13%) and the contribution of other independent factors, including neuromuscular activation, appears limited for this performance task.…”

Neural adaptations after 4 years vs 12 weeks of resistance training vs untrained

“…Muscle size was included as an additional index of training status and morphological differences between the three groups. MED was measured to allow for the correction of the pronounced, confounding influence of subcutaneous tissue thickness, primarily body fat, on voluntary EMG amplitude…”

“…Correcting EMG amplitude measurements for the amount of subcutaneous tissue at the recording site or using MED as a covariate within statistical testing are approaches that have previously been employed. The MED correction in the current study involved summating the individual's residual absolute agonist EMG amplitude, in comparison to the cohort relationship with MED (eg, agonist EMG amplitude vs MED), with the pooled group mean for absolute agonist EMG amplitude . Overall corrected agonist EMG during all maximum and sub‐maximum contractions was then calculated by averaging the corrected EMG amplitude measurements from each EMG recording site.…”

Reduced corticospinal responses in older compared with younger adults during submaximal isometric, shortening, and lengthening contractions

“…Torque and root-mean-square background EMG activity (RMS EMG) were assessed in the 100ms epoch preceding the stimulus. RMS EMG of TA was normalised to Mmax (RMS/Mmax) in order to remove the confounding effect of electrode location and body fat (65), and account for changes at the skin-electrode interface and differences in propagation along the sarcolemma (83). Torque variability during submaximal contractions was assessed as coefficient of variation (CVtorque = SD torque /mean torque*100) in the 1-second epoch preceding the stimulus.…”