Estimation of average muscle fiber conduction velocity from simulated surface EMG in pinnate muscles

Task-related differences in peroneus longus muscle fiber conduction velocity

It has been identified that the peroneus longus presents a regional activity. Specifically, a greater activation of the anterior and posterior compartments has been observed during eversion, whereas a lower activation of the posterior compartment has been reported during plantarflexion. In addition to myoelectrical amplitude, motor unit recruitment can be inferred indirectly from muscle fiber conduction velocity (MFCV). However, there are few reports of MFCV of the regions that make up a muscle, and even less, MFCV of the peroneus longus compartments. This study aimed to analyze the MFCV of peroneus longus compartments during eversion and plantarflexion. Twenty-one healthy individuals were assessed. High-density surface electromyography was recorded from the peroneus longus during eversion and plantarflexion at 10%, 30%, 50%, and 70% of maximal voluntary isometric contraction. The posterior compartment presented a lower MFCV than the anterior compartment during plantarflexion, and both compartments did not show differences in MFCV during eversion; however, the posterior compartment showed an increase in MFCV during eversion compared to plantarflexion. Differences observed in the MFCV of the peroneus longus compartments could support a regional activation strategy and, to some extent, explain different motor unit recruitment strategies of the peroneus longus during ankle movements.

Influence of electrode configuration on muscle-fiber-conduction-velocity estimation using surface electromyography

OBJECTIVE

Muscle fiber conduction velocity (MFCV) is an important myoelectric parameter and can be estimated by analyzing surface electromyography (EMG). Among many factors, electrode configuration plays a key role on MFCV estimation. Most studies adopt bipolar configuration (BC) for CV estimation. However, a thorough understanding of the underlying mechanism is lacking, confusing the design of the most appropriate EMG measurement setup for CV estimation. The aim of this study is therefore to systematically investigate the influence of electrode configuration on MFCV estimation.

METHODS

Four possible configurations are considered, including BC, monopolar configuration (MC), common average reference (CAR), and a special monopolar configuration (SMC) using a fix channel on the active muscle as reference. For each configuration, mathematic models computing the time delay between adjacent channels are derived and evaluated by dedicated simulation as well as real EMG measurements. MFCV was calculated using the maximum likelihood algorithm with and without channel normalization.

RESULTS

The simulation results are in line with the mathematical models. The CVs estimated from the real EMG with and without normalization are 4.30.7 and 7.23.7 m/s, 5.71.3 and 20.44.7 m/s, 9.03.4 and 20.69.8 m/s, and 5.52.5 and 5.52.4 m/s for BC, MC, SMC, and CAR, respectively.

CONCLUSION

Our results show normalized BC to produce the most accurate CV estimation, in line with the mathematical models and the simulation results.

SIGNIFICANCE

These findings enable a better understanding of the influence of electrode configuration on MFCV estimation, providing useful information for EMG measurement setup design aiming at MFCV studies.

Single channel surface electromyogram deconvolution to explore motor unit discharges

Interference surface electromyogram (EMG) reflects many bioelectric properties of active motor units (MU), which are however difficult to estimate due to the asynchronous summation of their discharges. This paper introduces a deconvolution technique to estimate the cumulative firings of MUs. Tests in simulations show that the power spectral density of the estimated MU firings has a low-frequency peak corresponding to the mean firing rate of MUs in the detection volume of the recording system, weighted by the amplitudes of MU action potentials. The peak increases in amplitude and its centroid shifts to a higher frequency when MU synchronization is simulated (mainly due to the shift of discharges of large MUs). The peak is found even at high force levels, when such a contribution does not emerge from the EMG. This result is also confirmed in preliminary applications to experimental data. Moreover, the simulated cumulative firings of MUs are estimated with a correlation above 90% (considering frequency contributions up to 150 Hz), for all force levels. The method requires a single EMG channel, thus being feasible even in applied studies using simple recording systems. It may open many potential applications, e.g., in the study of the modulation of MU firing rate induced by either fatigue or pathology and in coherency analysis. Graphical Abstract Examples of application of the deconvolution (Deconv) algorithm and comparison with the cumulative firings and the cumulated weighted firings (CWF, i.e., each firing pattern is weighted by the root mean squared amplitude of the corresponding MU action potential). Portions of data are shown on the left, the power spectral densities (PSD) on the right (Welch method applied to 3 s of data, sub-epochs of 0.5 s, mean value removed from each of them, 50% of overlap). A) Simulated signal (50% of maximal voluntary contraction, MVC) with random MU firings. B) Simulated signal (50% MVC) with a level of synchronization equal to 10%. C) Experimental data from vastus medialis at 40% MVC (data decomposed by the algorithm of Holobar and Zazula, IEEE Trans. Sig. Proc. 2007; PSD of the cumulated firings almost identical to that of CWF, as few MUs were identified).

A computational model to investigate the effect of pennation angle on surface electromyogram of Tibialis Anterior

This study has described and experimentally validated the differential electrodes surface electromyography (sEMG) model for tibialis anterior muscles during isometric contraction. This model has investigated the effect of pennation angle on the simulated sEMG signal. The results show that there is no significant effect of pennation angle in the range 0° to 20° to the single fibre action potential shape recorded on the skin surface. However, the changes with respect to pennation angle are observed in sEMG amplitude, frequency and fractal dimension. It is also observed that at different levels of muscle contractions there is similarity in the relationships with Root Mean Square, Median Frequency, and Fractal Dimension of the recorded and simulated sEMG signals.

Generation of synthetic surface electromyography signals under fatigue conditions for varying force inputs using feedback control algorithm

Surface electromyography is a non-invasive technique used for recording the electrical activity of neuromuscular systems. These signals are random, complex and multi-component. There are several techniques to extract information about the force exerted by muscles during any activity. This work attempts to generate surface electromyography signals for various magnitudes of force under isometric non-fatigue and fatigue conditions using a feedback model. The model is based on existing current distribution, volume conductor relations, the feedback control algorithm for rate coding and generation of firing pattern. The result shows that synthetic surface electromyography signals are highly complex in both non-fatigue and fatigue conditions. Furthermore, surface electromyography signals have higher amplitude and lower frequency under fatigue condition. This model can be used to study the influence of various signal parameters under fatigue and non-fatigue conditions.

A new optical flow model for motor unit conduction velocity estimation in multichannel surface EMG

Many studies have demonstrated the feasibility and benefits of Conduction Velocity (CV) estimation from surface electromyograms (EMGs) in various experimental conditions. Among them, a method based on optical flow was proposed recently, demonstrating relatively accurate CV estimation for EMG signals acquired in monopolar mode. We extended this method by a new data model that compensates more realistically for the spatial Motor Unit Action Potential (MUAP) shape variability and enables accurate CV estimation also in single-differential acquisition mode. The proposed modification was validated on 5000 synthetic Motor Units (MUs) with known CV and direction of fibres. It was shown that, in the noiseless case, the mean CV estimation error was significantly lower for our proposed modification compared to the original CV estimation procedure by up to 2% in the case of monopolar EMG signals and by up to 18.6% for single-differential EMG signals. When estimating fibre directions, the mean error was lower by up to 2.4° (for monopolar EMG signals) and 9.6° (for single-differential EMG signals). The results of tests with 10dB and 20dB noise further demonstrated the robustness of the proposed algorithm to noise in MUAP estimation.

Multichannel EMG-based estimation of fiber conduction velocity during isometric contraction of patients with different stages of diabetic neuropathy

This study compares muscle fiber conduction velocities estimated using surface electromyography during isometric maximal voluntary contraction in different stages of diabetic neuropathy. Eighty-five adults were studied: 16 non-diabetic individuals and 69 diabetic patients classified into four neuropathy stages, defined by a fuzzy expert system: absent (n=26), mild (n=21), moderate (n=11) and severe (n=11). Average muscle fiber conduction velocities of gastrocnemius medialis, tibialis anterior, vastus lateralis and biceps femoris were assessed using linear array electrodes, and were compared by ANOVA. Conduction velocities were significantly decreased in the moderate neuropathy group for the vastus lateralis compared to other groups (from 18% to 21% decrease), and were also decreased in all diabetic groups for the tibialis anterior (from 15% to 20% from control group). Not only the distal anatomical localization of the muscle affects the conduction velocity, but also the proportion of muscle fiber type, where the tibialis anterior with greater type I fiber proportion is affected earlier while the vastus lateralis with greater type II fiber proportion is affected in later stages of the disease. Generally, the muscles of the lower limb have different responsiveness to the effects of diabetes mellitus and show a reduction in the conduction velocity as neuropathy progresses.

Motor unit

Movement is accomplished by the controlled activation of motor unit populations. Our understanding of motor unit physiology has been derived from experimental work on the properties of single motor units and from computational studies that have integrated the experimental observations into the function of motor unit populations. The article provides brief descriptions of motor unit anatomy and muscle unit properties, with more substantial reviews of motoneuron properties, motor unit recruitment and rate modulation when humans perform voluntary contractions, and the function of an entire motor unit pool. The article emphasizes the advances in knowledge on the cellular and molecular mechanisms underlying the neuromodulation of motoneuron activity and attempts to explain the discharge characteristics of human motor units in terms of these principles. A major finding from this work has been the critical role of descending pathways from the brainstem in modulating the properties and activity of spinal motoneurons. Progress has been substantial, but significant gaps in knowledge remain.

Do surface electromyograms provide physiological estimates of conduction velocity from the medial gastrocnemius muscle?

Muscle fiber conduction velocity (CV) is commonly estimated from surface electromyograms (EMGs) collected with electrodes parallel to muscle fibers. If electrodes and muscle fibers are not located in parallel planes, CV estimates are biased towards values far over the physiological range. In virtue of their pinnate architecture, the fibers of muscles such as the gastrocnemius are hardly aligned in planes parallel to surface electrodes. Therefore, in this study we investigate whether physiological CV estimates can be obtained from the gastrocnemius muscle. Specifically, with a large grid of 16×8 electrodes we map CV estimates over the whole gastrocnemius muscle while eleven subjects exerted isometric plantar flexions at three different force levels. CV was estimated for couples of single differential EMGs and estimate locations (i.e., channels) were classified as physiological and non-physiological, depending on whether CV estimates were within the physiological range (3-6ms(-1)) or not. Physiological CV values could be estimated from a markedly small muscle region for eight participants; channels providing physiological CV estimates corresponded to about 5% of the total number of channels. As expected, physiological and non-physiological channels were clustered in distinct regions. CV estimates within the physiological range were obtained for the most distal gastrocnemius portion (ANOVA, P<0.001), where occurrences of propagating potentials were often verified through visual analysis. For the first time, this study shows that CV might be reliably assessed from surface EMGs collected from the most distal gastrocnemius region.

Effect of innervation-zone distribution on estimates of average muscle-fiber conduction velocity

Muscle-fiber conduction velocity (MFCV) may be a diagnostic variable, but the factors affecting its estimate from surface electromyographic (SEMG) signals are still not fully understood. We investigated the effect of innervation-zone distribution on estimates of average MFCV from simulated SEMG signals. Single-fiber action potentials were simulated using a computer model that describes an idealized cylindrical volume conductor comprised of bone, muscle, subcutaneous, and skin tissues. A model describing the characteristics and control of a motor-neuron pool was used to simulate 60 s of SEMG. Five innervation-zone distributions, inclined with respect to the fiber direction, were simulated within the muscle tissue, based on data from the literature and an experimental analysis. Two parameters were varied concurrently: (1) excitation level (5%-100%, 5% increments); and (2) subcutaneous tissue thickness (4 and 10 mm). The MFCV estimates were affected by the distribution of innervation zones with bias varying with excitation level and thickness of subcutaneous tissue. The MFCV estimates ranged from 3.95 to 11.67 m/s for single-differential and from 3.99 to 5.23 m/s for double-differential recordings when all simulated motor units were assigned the same conduction velocity of 4 m/s. Amplitude and characteristic spectral frequencies were also influenced by the distribution of innervation zones. The effect of innervation-zone distribution on MFCV estimates is thus substantial and may be a significant confounding factor in experimental and clinical studies on muscles with diffuse innervation zones.

Reliability of a novel neurostimulation method to study involuntary muscle phenomena

Experimental methods involving painful electrical stimulation of a peripheral nerve showed the existence of a minimum stimulation frequency capable of inducing cramp, termed "threshold frequency" (TF). Our aim was to test an alternative method to induce fasciculations and cramps electrically. Two daily sessions of electrical stimulation of the abductor hallucis muscle were performed in 19 volunteers on 3 days: stimulation trains of 150 monophasic square pulses (duration 152 micros) of increasing frequency (current intensity 30% higher than maximal; frequency of the first trial, 4 pps; recovery between trials, 1 min) were delivered to the main muscle motor point until a cramp developed. Once a cramp was induced the protocol was repeated after 30 min. To verify by electromyography that cramp occurred, a surface electrode array was placed between the motor point and the distal tendon. Ambient and skin temperature were kept constant in all sessions. Fasciculations and cramps were elicited in all subjects. We observed the following median (interquartile range) values of TF: day 1 (session 1), 13 (6) pps; day 1 (session 2), 16 (4) pps; day 2 (session 1), 16 (6) pps; day 2 (session 2), 18 (6) pps; day 3 (session 1), 17 (4) pps; day 3 (session 2), 18 (8) pps. TF intersession intraclass correlation coefficients were 0.82, 0.92, and 0.90 for days 1, 2, and 3, respectively. TF interday intraclass correlation coefficient was 0.85. The absence of pain due to the stimulation and the demonstration of TF reliability support the use of our method for the study of involuntary muscle phenomena.