Relationships between surface EMG variables and motor unit firing rates

Abstract

Although surface electromyography (sEMG) is a widely used electrophysiological technique, its physiological interpretation remains somewhat controversial. This study examined the relationship between motor unit firing rates (MUFR) and the root mean square (RMS) amplitude and mean power frequency (MPF) of the sEMG signal in the biceps brachii. Eleven subjects performed maximal isometric elbow flexion while indwelling and sEMG recordings were obtained from the biceps. The RMS amplitude and MPF of the surface signal, and the mean MUFR from the indwelling signal, were calculated over 500 ms epochs. Group means showed a strong MUFR-RMS amplitude relationship (r (2) = 0.91), but a weak MUFR-MPF relationship (r (2) = 0.20). Using all trials, the MUFR-RMS amplitude (r (2) = 0.19) and MUFR-MPF (r (2) = 0.0037) relationships were much weaker. Within individual subjects, the MUFR-RMS amplitude (mean r (2) = 0.13 +/- 0.17) and the MUFR-MPF (mean r (2) = 0.040 +/- 0.041) relationships were also weak. These results suggest that MUFR cannot be predicted from the characteristics of the sEMG signal.

Neural, biomechanical, and physiological factors involved in sex-related differences in the maximal rate of isometric torque development

“…Slight plantar flexion was chosen as previous research has shown that a certain degree of plantar flexion produces a maximal torque and 110° may place the TA closer to optimal length for both maximal evoked and voluntary dorsiflexion torque production, which considers the lever arm length (Marsh et al 1981). A load cell (JR3, Woodland, CA, USA) was secured under the foot plate of which the foot was restrained by a minimally padded steel bar located proximal to the metatarsals for all torque recordings (Christie et al 2009). There were 3 days of testing to assess the reliability of the measures as participants can exhibit a learning effect during maximal strength assessment (Green et al 2014).…”

Improving the Transparency of an Exoskeleton Knee Joint Based on the Understanding of Motor Intent Using Energy Kernel Method of EMG

“…Referring to (7), both the firing rate and intensity are proportional to the square root of E . Interestingly, the exact expression of RMS is actually contained in (7), explaining why RMS can be applied to force estimation, while it also tells the reason why RMS cannot be used to extract firing rate [14]. In effect, (7) builds the relationship between the energy of the control signal (EMG) and that of the output (force or power of muscle).…”

“…For this purpose, the semiphenomenological biomechanical/cybernetic model of skeletal muscle established in our previous work [13] would be applied in this paper. As for motion decoding using EMG, many methods, such as RMS, MPF [14], wavelet, fractal, and FIR [15]- [17], etc., have been proposed, while for dynamic control, the real-time performance, robustness, and the accuracy of existent methods are still at issue. To extract reliably the activation level from EMG, a promising way is to find the physical correspondence between the energy of the signal and the power of muscle based on the biomechanical relationship between the firing behavior of motoneuron and muscular contraction [18].…”

The Isokinetic and Electromyographic Assessment of Knee Muscles Strength in the Short- and Long-Term Type 2 Diabetes

“…Muscular weakness in T2DM could be due to insulin resistance, intracellular lipid accumulation, mitochondria dysfunction, sarcopenia and neuromuscular impairments (8-15). The electromyographic (EMG) assessment of muscle as a sarcolemma output provides more information about the properties of motor units to control neuromuscular function (16). EMG frequency, an indicator of muscle fiber conduction velocity, and EMG amplitude, a sign of neural excitation (17).…”

“…The most electrophysiological assessments in T2DM were limited to measure nerve conduction velocity (20) and compound muscle action potentials that showed reduction in nerve conduction velocity and density of fibers and motor unit in the diabetic polyneuropathy (6, 15, 16). Watanabe et al compared the root mean squared (RMS) activity of vastus lateralis in 10% MVC for 120 seconds between healthy and T2DM by 64 multi-channel EMG.…”