The Accurate Assessment of Muscle Excitation Requires the Detection of Multiple Surface Electromyograms

When sampling electromyograms (EMGs) with one pair of electrodes, it seems implicitly assumed the detected signal reflects the net muscle excitation. However, this assumption is discredited by observations of local muscle excitation. Therefore, we hypothesize that the accurate assessment of muscle excitation requires multiple EMG detection and consideration of electrode-fiber alignment. We advise prudence when drawing inferences from individually collected EMGs

Young, Healthy Subjects Can Reduce the Activity of Calf Muscles When Provided with EMG Biofeedback in Upright Stance

Recent evidence suggests the minimization of muscular effort rather than of the size of bodily sway may be the primary, nervous system goal when regulating the human, standing posture. Different programs have been proposed for balance training; none however has been focused on the activation of postural muscles during standing. In this study we investigated the possibility of minimizing the activation of the calf muscles during standing through biofeedback. By providing subjects with an audio signal that varied in amplitude and frequency with the amplitude of surface electromyograms (EMG) recorded from different regions of the gastrocnemius and soleus muscles, we expected them to be able to minimize the level of muscle activation during standing without increasing the excursion of the center of pressure (CoP). CoP data and surface EMG from gastrocnemii, soleus and tibialis anterior muscles were obtained from 10 healthy participants while standing at ease and while standing with EMG biofeedback. Four sensitivities were used to test subjects' responsiveness to the EMG biofeedback. Compared with standing at ease, the two most sensitive feedback conditions induced a decrease in plantar flexor activity (~15%; P < 0.05) and an increase in tibialis anterior EMG (~10%; P < 0.05). Furthermore, CoP mean position significantly shifted backward (~30 mm). In contrast, the use of less sensitive EMG biofeedback resulted in a significant decrease in EMG activity of ankle plantar flexors with a marginal increase in TA activity compared with standing at ease. These changes were not accompanied by greater CoP displacements or significant changes in mean CoP position. Key results revealed subjects were able to keep standing stability while reducing the activity of gastrocnemius and soleus without loading their tibialis anterior muscle when standing with EMG biofeedback. These results may therefore posit the basis for the development of training protocols aimed at assisting subjects in more efficiently controlling leg muscle activity during standing

Design and Characterization of a Textile Electrode System for the Detection of High-Density sEMG

Muscle activity monitoring in dynamic conditions is a crucial need in different scenarios, ranging from sport to rehabilitation science and applied physiology. The acquisition of surface electromyographic (sEMG) signals by means of grids of electrodes (High-Density sEMG, HD-sEMG) allows obtaining relevant information on muscle function and recruitment strategies. During dynamic conditions, this possibility demands both a wearable and miniaturized acquisition system and a system of electrodes easy to wear, assuring a stable electrode-skin interface. While recent advancements have been made on the former issue, detection systems specifically designed for dynamic conditions are at best incipient. The aim of this work is to design, characterize, and test a wearable, HD-sEMG detection system based on textile technology. A 32-electrodes, 15 mm inter-electrode distance textile grid was designed and prototyped. The electrical properties of the material constituting the detection system and of the electrode-skin interface were characterized. The quality of sEMG signals was assessed in both static and dynamic contractions. The performance of the textile detection system was comparable to that of conventional systems in terms of stability of the traces, properties of the electrode-skin interface and quality of the collected sEMG signals during quasi-isometric and highly dynamic tasks

Detecting anatomical characteristics of single motor units by combining high density electromyography and ultrafast ultrasound: a simulation study

Muscle force production is the result of a sequence of electromechanical events that translate the neural drive issued to the motor units (MUs) into tensile forces on the tendon. Current technology allows this phenomenon to be investigated non-invasively. Single MU excitation and its mechanical response can be studied through high-density surface electromyography (HDsEMG) and ultrafast ultrasound (US) imaging respectively. In this study, we propose a method to integrate these two techniques to identify anatomical characteristics of single MUs. Specifically, we tested two algorithms, combining the tissue velocity sequence (TVS, obtained from ultrafast US images), and the MU firings (extracted from HDsEMG decomposition). The first is the Spike Triggered Averaging (STA) of the TVS based on the occurrences of individual MU firings, while the second relies on the correlation between the MU firing patterns and the TVS spatio-temporal independent components (STICA). A simulation model of the muscle contraction was adapted to test the algorithms at different degrees of neural excitation (number of active MUs) and MU synchronization. The performances of the two algorithms were quantified through the comparison between the simulated and the estimated characteristics of MU territories (size, location). Results show that both approaches are negatively affected by the number of active MU and synchronization levels. However, STICA provides a more robust MU territory estimation, outperforming STA in all the tested conditions. Our results suggest that spatio-temporal independent component decomposition of TVS is a suitable approach for anatomical and mechanical characterization of single MUs using a combined HDsEMG and ultrafast US approach

Changes in tibialis anterior architecture affect the amplitude of surface electromyograms

BACKGROUND: Variations in the amplitude of surface electromyograms (EMGs) are typically considered to advance inferences on the timing and degree of muscle activation in different circumstances. Surface EMGs are however affected by factors other than the muscle neural drive. In this study, we use electrical stimulation to investigate whether architectural changes in tibialis anterior (TA), a key muscle for balance and gait, affect the amplitude of surface EMGs. METHODS: Current pulses (500 μs; 2 pps) were applied to the fibular nerve of ten participants, with the ankle at neutral, full dorsi and full plantar flexion positions. Ultrasound images were collected to quantify changes in TA architecture with changes in foot position. The peak-to-peak amplitude of differential M waves, detected with a grid of surface electrodes (16 × 4 electrodes; 10 mm inter-electrode distance), was considered to assess the effect of changes in TA architecture on the surface recordings. RESULTS: On average, both TA pennation angle and width increased by respectively 7 deg. and 9 mm when the foot moved from plantar to dorsiflexion (P < 0.02). M-wave amplitudes changed significantly with ankle position. M waves elicited in dorsiflexion and neutral positions were ~25% greater than those obtained during plantar flexion, regardless of where they were detected in the grid (P < 0.001). This figure increased to ~50% when considering bipolar M waves. CONCLUSIONS: Findings reported here indicate the changes in EMG amplitude observed during dynamic contractions, especially when changes in TA architecture are expected (e.g., during gait), may not be exclusively conceived as variations in TA activation