Estimation of single motor unit conduction velocity from surface electromyogram signals detected with linear electrode arrays

Neuromuscular Responses and Perceptions of Health Status and Pain-Related Constructs in End-Stage Knee Osteoarthritis During Resistance Training With Blood Flow Restriction

ABSTRACT

Ogrezeanu, DC, López-Bueno, L, Sanchís-Sánchez, E, Carrasco, JJ, Cuenca-Martínez, F, Suso-Martí, L, López-Bueno, R, Cruz-Montecinos, C, Martinez-Valdes, E, Casaña, J, and Calatayud, J. Neuromuscular responses and perceptions of health status and pain-related constructs in end-stage knee osteoarthritis during resistance training with blood flow restriction. J Strength Cond Res 38(4): 762-772, 2024-We aimed to evaluate the neuromuscular responses and their relationship with health status, kinesiophobia, pain catastrophizing, and chronic pain self-efficacy in patients with end-stage knee osteoarthritis during acute resistance training with different levels of blood flow restriction (BFR). Seventeen patients with end-stage knee osteoarthritis participated in 3 experimental sessions separated by 3 days, performing 4 sets of knee extensions with low load and 3 levels of concurrent BFR performed in a random order: control (no BFR), BFR at 40% arterial occlusion pressure (AOP), and BFR at 80% AOP. Normalized root-mean-square (nRMS), nRMS spatial distribution (centroid displacement, modified entropy, and coefficient of variation), and normalized median frequency (nFmed) were calculated from the vastus medialis (VM) and lateralis (VL) using high-density surface electromyography. Subjects were asked to report adverse effects after the sessions. In the VM, nRMS was higher with 80% AOP than with 40% AOP ( p = 0.008) and control ( p < 0.001), whereas there were no differences between conditions in the VL. Normalized root-mean-square also showed an association with pain catastrophizing, chronic pain self-efficacy, and health status (VM: -0.50, 0.49, -0.42; VL: -0.39, 0.27, -0.33). Spatial distribution varied between conditions but mostly in the VL. Overall, nFmed did not vary, with only a slight increase in the VL with 40% AOP, between set 3 and 4. BFR during knee extensions at 80% AOP increases VM activity and VL amplitude distribution more than 40% AOP and control. Importantly, muscle activity increases are modulated by pain catastrophizing, chronic pain self-efficacy, and health status in these patients, and kinesiophobia seems to especially modulate entropy.

Shear Wave Tensiometry Can Detect Loading Differences Between Operated and Unaffected Achilles Tendon

BACKGROUND

The clinically relevant healing process of a ruptured and repaired Achilles tendon (AT) can last more than a year. The purpose of this cross-sectional study was to test if shear wave tensiometry is able to detect AT loading changes between a surgically managed AT rupture versus the unaffected contralateral tendon. Our secondary aims were to evaluate differences in mechanical properties when measured with myotonometry and morphological properties of the tendons measured with ultrasonographic imaging.

METHODS

Twenty-one patients with surgically treated AT ruptures were investigated 12-37 months after surgery. Tendon load was measured using a shear wave tensiometer composed of an array of 4 accelerometers fixed on the tendon. Shear wave speed along the Achilles tendon was evaluated at different levels of ankle torque for both the operated and the unaffected side. Mechanical properties of the tendons were evaluated using MyotonPRO and morphological properties using ultrasonographic imaging. Friedman test was used to assess differences in AT wave speed, stiffness, thickness, and cross-sectional area between the operated and the unaffected tendon.

RESULTS

We found a significant shear wave speed difference between sides at every ankle joint torque (P < .05) with a large effect size for the lowest ankle torque and small to medium effect sizes for higher ankle torque. Stiffness, thickness, and cross-sectional area of the operated tendon remained significantly higher compared to the unaffected side.

CONCLUSION

In this cohort, we found that shear wave tensiometry can detect differences between operated and unaffected AT during a standardized loading procedure. The shear wave speed along the operated tendon, as well as the mechanical and morphologic properties, remains higher for 1-3 years after a rupture.

LEVEL OF EVIDENCE

Level III, case-control study.

Non-invasive estimation of muscle fibre size from high-density electromyography

Because of the biophysical relation between muscle fibre diameter and the propagation velocity of action potentials along the muscle fibres, motor unit conduction velocity could be a non-invasive index of muscle fibre size in humans. However, the relation between motor unit conduction velocity and fibre size has been only assessed indirectly in animal models and in human patients with invasive intramuscular EMG recordings, or it has been mathematically derived from computer simulations. By combining advanced non-invasive techniques to record motor unit activity in vivo, i.e. high-density surface EMG, with the gold standard technique for muscle tissue sampling, i.e. muscle biopsy, here we investigated the relation between the conduction velocity of populations of motor units identified from the biceps brachii muscle, and muscle fibre diameter. We demonstrate the possibility of predicting muscle fibre diameter (R2  = 0.66) and cross-sectional area (R2  = 0.65) from conduction velocity estimates with low systematic bias (∼2% and ∼4% respectively) and a relatively low margin of individual error (∼8% and ∼16%, respectively). The proposed neuromuscular interface opens new perspectives in the use of high-density EMG as a non-invasive tool to estimate muscle fibre size without the need of surgical biopsy sampling. The non-invasive nature of high-density surface EMG for the assessment of muscle fibre size may be useful in studies monitoring child development, ageing, space and exercise physiology, although the applicability and validity of the proposed methodology need to be more directly assessed in these specific populations by future studies. KEY POINTS: Because of the biophysical relation between muscle fibre size and the propagation velocity of action potentials along the sarcolemma, motor unit conduction velocity could represent a potential non-invasive candidate for estimating muscle fibre size in vivo. This relation has been previously assessed in animal models and humans with invasive techniques, or it has been mathematically derived from simulations. By combining high-density surface EMG with muscle biopsy, here we explored the relation between the conduction velocity of populations of motor units and muscle fibre size in healthy individuals. Our results confirmed that motor unit conduction velocity can be considered as a novel biomarker of fibre size, which can be adopted to predict muscle fibre diameter and cross-sectional area with low systematic bias and margin of individual error. The proposed neuromuscular interface opens new perspectives in the use of high-density EMG as a non-invasive tool to estimate muscle fibre size without the need of surgical biopsy sampling.

Motor Unit Discharge Characteristics and Conduction Velocity of the Vastii Muscles in Long-Term Resistance-Trained Men

PURPOSE

Adjustments in motor unit (MU) discharge properties have been shown after short-term resistance training; however, MU adaptations in long-term resistance-trained (RT) individuals are less clear. Here, we concurrently assessed MU discharge characteristics and MU conduction velocity in long-term RT and untrained (UT) men.

METHODS

Motor unit discharge characteristics (discharge rate, recruitment, and derecruitment threshold) and MU conduction velocity were assessed after the decomposition of high-density electromyograms recorded from vastus lateralis (VL) and vastus medialis (VM) of RT (>3 yr; n = 14) and UT ( n = 13) during submaximal and maximal isometric knee extension.

RESULTS

Resistance-trained men were on average 42% stronger (maximal voluntary force [MVF], 976.7 ± 85.4 N vs 685.5 ± 123.1 N; P < 0.0001), but exhibited similar relative MU recruitment (VL, 21.3% ± 4.3% vs 21.0% ± 2.3% MVF; VM, 24.5% ± 4.2% vs 22.7% ± 5.3% MVF) and derecruitment thresholds (VL, 20.3% ± 4.3% vs 19.8% ± 2.9% MVF; VM, 24.2% ± 4.8% vs 22.9% ± 3.7% MVF; P ≥ 0.4543). There were also no differences between groups in MU discharge rate at recruitment and derecruitment or at the plateau phase of submaximal contractions (VL, 10.6 ± 1.2 pps vs 10.3 ± 1.5 pps; VM, 10.7 ± 1.6 pps vs 10.8 ± 1.7 pps; P ≥ 0.3028). During maximal contractions of a subsample population (10 RT, 9 UT), MU discharge rate was also similar in RT compared with UT (VL, 21.1 ± 4.1 pps vs 14.0 ± 4.5 pps; VM, 19.5 ± 5.0 pps vs 17.0 ± 6.3 pps; P = 0.7173). Motor unit conduction velocity was greater in RT compared with UT individuals in both VL (4.9 ± 0.5 m·s -1 vs 4.5 ± 0.3 m·s -1 ; P < 0.0013) and VM (4.8 ± 0.5 m·s -1 vs 4.4 ± 0.3 m·s -1 ; P < 0.0073).

CONCLUSIONS

Resistance-trained and UT men display similar MU discharge characteristics in the knee extensor muscles during maximal and submaximal contractions. The between-group strength difference is likely explained by superior muscle morphology of RT as suggested by greater MU conduction velocity.

Differences in motor unit behavior during isometric contractions in patients with diabetic peripheral neuropathy at various disease severities

The aim of this study was to determine whether HD-sEMG is sensitive to detecting changes in motor unit behavior amongst healthy adults and type 2 diabetes mellitus (T2DM) patients presenting diabetic peripheral neuropathy (DPN) at different levels. Healthy control subjects (CON, n = 8) and T2DM patients presenting no DPN symptoms (ABS, n = 8), moderate DPN (MOD, n = 18), and severe DPN (SEV, n = 12) performed isometric ankle dorsiflexion at 30 % maximum voluntary contraction while high-density surface EMG (HD-sEMG) was recorded from the tibialis anterior muscle. HD-sEMG signals were decomposed, providing estimates of discharge rate, motor unit conduction velocity (MUCV), and motor unit territory area (MUTA). As a result, the ABS group presented reduced MUCV compared to CON. The groups with diabetes presented significantly larger MUTA compared to the CON group (p < 0.01), and the SEV group presented a significantly lower discharge rate compared to CON and ABS (p < 0.01). In addition, the SEV group presented significantly higher CoV_force compared to CON and MOD. These results support the use of HD-SEMG as a method to detect peripheral and central changes related to DPN.

Differences between vastus medialis and lateralis excitation onsets are dependent on the relative distance of surface electrodes placement from the innervation zone location

Conflictual results between the onset of vastus medialis (VM) and vastus lateralis (VL) excitation may arise from methodological aspects related to the detection of surface electromyograms. In this study we used an array of surface electrodes to assess the effect of detection site, relative to the muscle innervation zone, on the difference between VM and VL excitation onsets. Ten healthy males performed moderate isometric knee extension at 40 % of their maximal voluntary isometric contraction. After the actual VM-VL onset was defined (estimated when action potentials were generated at the neuromuscular junctions of both muscles), we calculated the largest bias that the detection site may introduce in the VM-VL onset estimation. We also assessed whether the location often considered for positioning bipolar electrodes on each muscle leads to VM-VL onset estimations comparable to the actual VM-VL onset. Our main results revealed that a maximum absolute bias of 20.48 ms may be introduced in VM-VL onset estimations due to the electrodes' detection site. In addition, mean differences of ∼ 12 ms in VM-VL onset estimations were attributable to largest possible discrepancies in the paired position of channels with respect to the innervation zone for VL and VM. When considering the classical location for positioning the bipolar electrodes over these muscles, differences error was subtle (∼3.4 ms) when compared with the actual VM-VL onset. Nonetheless, when accounting for the effect of relative differences in electrode position between muscles is not possible, our results suggest that a systematic absolute error of ∼ 12 ms should be considered in future studies regarding VM-VL onset estimations, suggesting that onset differences lower than that might not be clinically relevant.

Measurement of Achilles tendon loading using shear wave tensiometry: A reliability study

BACKGROUND

Shear wave tensiometry is a recent promising technology which can be used to evaluate tendon loading. Knowing the clinimetric features (e.g., reliability) of this technology is important for use in clinical and research settings.

OBJECTIVES

To evaluate the inter-session reliability of a novel shear wave tensiometer for the assessment of Achilles tendon loading. A further aim was to test the construct validity of this device by evaluating its precision in detecting Achilles tendon loading changes induced by a plantar flexor isometric contraction of increasing intensity.

METHOD

Ten healthy participants were recruited. Five measurements were performed at different time points to evaluate inter-session reliability. Shear wave speed along the Achilles tendon was evaluated during different isometric contractions using a shear wave tensiometer composed of an array of four accelerometers fixed on the tendon, ranging from 4 to 8.5 cm from the calcaneal insertion of the tendon. Test-retest, intra- and inter-session reliability were determined using intraclass correlation coefficient (ICC_3.1). Absolute reliability was calculated using the standard error of measurement and minimal detectable change.

RESULTS

Test-retest reliability was good to excellent (ICC_3.1 0.87-0.99) for each of the contraction levels examined. Intra-session reliability was good to excellent (ICC_3.1 0.85-0.96) and inter-session reliability was also good to excellent (ICC_3.1 0.75-0.93) for each of the contraction levels.

CONCLUSIONS

This study confirms the reliability of this novel device. Future studies analyzing participants with Achilles tendinopathy are needed to evaluate the capability of shear wave tensiometry to detect transient changes in loading due to pathology.

A Comparison of Delay-and-Add and Maximum Likelihood Estimation for Velocity-Selective Recording Using Multi-Electrode Cuffs

Extracting information from the peripheral nervous system with implantable devices remains a significant challenge that limits the advancement of closed-loop neural prostheses. Linear electrode arrays can record neural signals with both temporal and spatial selectivity, and velocity selective recording using the delay-and-add algorithm can enable classification based on fibre type. The maximum likelihood estimation method also measures velocity and is frequently used in electromyography but has never been applied to electroneurography. Therefore, this study compares the two algorithms using in-vivo recordings of electrically evoked compound action potentials from the ulnar nerve of a pig. The performance of these algorithms was assessed using the velocity quality factor (Q-factor), computational time and the influence of the number of channels. The results show that the performance of both algorithms is significantly influenced by the number of channels in the recording array, with accuracies ranging from 77% with only two channels to 98% for 11 channels. Both algorithms were comparable in accuracy and Q-factor for all channels, with the delay-and-add having a slight advantage in the Q-factor.

Recruitment order of motor neurons promoted by epidural stimulation in individuals with spinal cord injury

Spinal cord epidural stimulation (scES) combined with activity-based training can promote motor function recovery in individuals with motor complete spinal cord injury (SCI). The characteristics of motor neuron recruitment, which influence different aspects of motor control, are still unknown when motor function is promoted by scES. Here, we enrolled five individuals with chronic motor complete SCI implanted with a scES unit to study the recruitment order of motor neurons during standing enabled by scES. We recorded high-density electromyography (HD-EMG) signals on the vastus lateralis muscle, and inferred the order of recruitment of motor neurons from the relation between amplitude and conduction velocity of the scES-evoked EMG responses along the muscle fibers. Conduction velocity of scES-evoked responses was modulated over time, while stimulation parameters and standing condition remained constant, with average values ranging between 3.0±0.1 and 4.4±0.3 m/s. We found that the human spinal circuitry receiving epidural stimulation can promote both orderly (according to motor neuron size) and inverse trends of motor neuron recruitment, and that the engagement of spinal networks promoting rhythmic activity may favor orderly recruitment trends. Conversely, the different recruitment trends did not appear to be related with time since injury or scES implant, nor to the ability to achieve independent knees extension, nor to the conduction velocity values. The proposed approach can be implemented to investigate the effects of stimulation parameters and training-induced neural plasticity on the characteristics of motor neuron recruitment order, contributing to improve mechanistic understanding and effectiveness of epidural stimulation-promoted motor recovery after SCI.

The Effects of Spinal Manipulation on Motor Unit Behavior

Over recent years, a growing body of research has highlighted the neural plastic effects of spinal manipulation on the central nervous system. Recently, it has been shown that spinal manipulation improved outcomes, such as maximum voluntary force and limb joint position sense, reflecting improved sensorimotor integration and processing. This study aimed to further evaluate how spinal manipulation can alter neuromuscular activity. High density electromyography (HD sEMG) signals from the tibialis anterior were recorded and decomposed in order to study motor unit changes in 14 subjects following spinal manipulation or a passive movement control session in a crossover study design. Participants were asked to produce ankle dorsiflexion at two force levels, 5% and 10% of maximum voluntary contraction (MVC), following two different patterns of force production (“ramp” and “ramp and maintain”). A significant decrease in the conduction velocity (p = 0.01) was observed during the “ramp and maintain” condition at 5% MVC after spinal manipulation. A decrease in conduction velocity suggests that spinal manipulation alters motor unit recruitment patterns with an increased recruitment of lower threshold, lower twitch torque motor units.

Inverse modelling to reduce crosstalk in high density surface electromyogram

Surface electromyogram (EMG) has a relatively large detection volume, so that it could include contributions both from the target muscle of interest and from nearby regions (i.e., crosstalk). This interference can prevent a correct interpretation of the activity of the target muscle, limiting the use of surface EMG in many fields. To counteract the problem, selective spatial filters have been proposed, but they reduce the representativeness of the data from the target muscle. A better solution would be to discard only crosstalk from the signal recorded in monopolar configuration (thus, keeping most information on the target muscle). An inverse modelling approach is here proposed to estimate the contributions of different muscles, in order to focus on the one of interest. The method is tested with simulated monopolar EMGs from superficial nearby muscles contracted at different force levels (either including or not model perturbations and noise), showing statistically significant improvements in information extraction from the data. The median over the entire dataset of the mean squared error in representing the EMG of the muscle under the detection electrode was reduced from 11.2% to 4.4% of the signal energy (5.3% if noisy data were processed); the median bias in conduction velocity estimation (from 3 monopolar channels aligned to the muscle fibres) was decreased from 2.12 to 0.72 m/s (1.1 m/s if noisy data were processed); the median absolute error in the estimation of median frequency was reduced from 1.02 to 0.67 Hz in noise free conditions and from 1.52 to 1.45 Hz considering noisy data.

Reproducibility of muscle fibre conduction velocity during linearly increasing force contractions

Muscle fibre conduction velocity (MFCV) is a basic physiological parameter biophysically related to the diameter of muscle fibres and properties of the sarcolemma. The aim of this study was to assess the intersession reproducibility of the relation between voluntary force and estimates of average muscle fibre conduction velocity (MFCV) from multichannel high-density surface electromyographic recordings (HDsEMG). Ten healthy men performed six linearly increasing isometric ankle dorsiflexions on two separate experimental sessions, 4 weeks apart. Each session involved the recordings of voluntary force during maximal isometric (MViF) and submaximal ramp contractions at 35-50-70% of MViF. Concurrently, the HDsEMG activity was detected from the tibialis anterior muscle and MFCV estimates were derived in 250-ms epochs. Absolute and relative reproducibility of MFCV initial value (intercept) and rate of change (regression slope) as a function of force were assessed by within-subject coefficient of correlation (CV_w) and with intraclass correlation coefficient (ICC). MFCV was positively correlated with voluntary force (R² = 0.75 ± 0.12) in all individuals and test conditions (P < 0.001). Average CV_w for MFCV intercept and slope were of 2.6 ± 2.0% and 11.9 ± 3.2% and ICC values of 0.96 and 0.94, respectively. Overall, MFCV regression coefficients showed a high degree of intersession reproducibility in both absolute and relative terms. These results may have important practical implications in the tracking of training-induced neuromuscular changes and/or in the monitoring of the progress of neuromuscular disorders when a full sEMG signal decomposition is problematic or not possible.

Peripheral nerve transfers change target muscle structure and function

Selective nerve transfers surgically rewire motor neurons and are used in extremity reconstruction to restore muscle function or to facilitate intuitive prosthetic control. We investigated the neurophysiological effects of rewiring motor axons originating from spinal motor neuron pools into target muscles with lower innervation ratio in a rat model. Following reinnervation, the target muscle's force regenerated almost completely, with the motor unit population increasing to 116% in functional and 172% in histological assessments with subsequently smaller muscle units. Muscle fiber type populations transformed into the donor nerve's original muscles. We thus demonstrate that axons of alternative spinal origin can hyper-reinnervate target muscles without loss of muscle force regeneration, but with a donor-specific shift in muscle fiber type. These results explain the excellent clinical outcomes following nerve transfers in neuromuscular reconstruction. They indicate that reinnervated muscles can provide an accurate bioscreen to display neural information of lost body parts for high-fidelity prosthetic control.

An application of higher order multivariate cumulants in modelling of myoelectrical activity of porcine uterus during early pregnancy

The analysis of the uterine contraction have become a general practice in an effort to improve the clinical management of uterine contractions during pregnancy and labour in human beings. The fluctuations in uterine activity may occur without affecting progress of gestation, however the painful and fashion contractions may be the first threat of miscarriage. While pigs were considered as an referential preclinical model, the computational modelling of spontaneous myoelectrical activity of complex systems of porcine myometrium in peri-fertilization period has been proposed. The higher order statistic, multivariate cumulants and Joint Skewness Band Selection method, have been applied to study the dependence structure of electromyographic (EMG) signal with an effective EMG feature. Than the model of recognition of multivariate, myoelectricaly changes according to crucial stages for successful fertilization and early pregnancy maintenance has been estimated. We found that considering together time and frequency features of EMG signal was extremely non-Gaussian distributed and the higher order multivariate statistics such as cumulants, have to be used to determine the pattern of myoelectrical activity in reproductive tract. We confirmed the expectance that the probabilistic model changes on a daily base. We demonstrated the changes in proposed model at the crucial time points of in peri-fertilization period. We speculate the activity of the middle of uterine horn and the power (minimum and maximum) and pauses between myoelectrical burst features are essential for the functional role of uterine contractility in peri-fertilization period.

Decoding motor neuron activity from epimysial thin-film electrode recordings following targeted muscle reinnervation

OBJECTIVE

Surface electromyography (EMG) is currently used as a control signal for active prostheses in amputees who underwent targeted muscle reinnervation (TMR) surgery. Recent research has shown that it is possible to access the spiking activity of spinal motor neurons from multi-channel surface EMG. In this study, we propose the use of multi-channel epimysial EMG electrodes as an interface for decoding motor neurons activity following TMR.

APPROACH

We tested multi-channel epimysial electrodes (48 detection sites) built with thin-film technology in an animal model of TMR. Eight animals were tested 12 weeks after reinnervation of the biceps brachii lateral head by the ulnar nerve. We identified the position of the innervation zone and the muscle fiber conduction velocity of motor units decoded from the multi-channel epimysial recordings. Moreover, we characterized the pick-up volume by the distribution of the motor unit action potential amplitude over the epimysium surface.

MAIN RESULTS

The electrodes provided high quality signals with average signal-to-noise ratio  >30 dB across 95 identified motor units. The motor unit action potential amplitude decreased with increasing distance of the electrode from the muscle fibers (P [Formula: see text] 0.001). The decrease was more pronounced for bipolar compared to monopolar derivations. The average muscle fiber conduction velocity was 2.46  ±  0.83 m s^-1. Most of the neuromuscular junctions were close to the region where the nerve was neurotized, as observed from the EMG recordings and imaging data.

SIGNIFICANCE

These results show that epimysial electrodes can be used for selective recordings of motor unit activities with a pick-up volume that included the entire muscle in the rat hindlimb. Epimysial electrodes can thus be used for detecting motor unit activity in muscles with specific fascicular territories associated to different functions following TMR surgery.

Muscle fiber conduction velocity of the vastus medilais and lateralis muscle after eccentric exercise induced-muscle damage

Change in muscle fiber conduction velocity (MFCV) has been reported after eccentric exercise induces muscle fiber damage, most likely due to a change in membrane permeability of the injured fiber. The extent of damage to the muscle fiber depends on the morphological and architectural characteristics of the muscle fibers. Morphological and architectural characteristics of the VMO muscle fibers are different from VL muscle. Thus, it is expected that eccentric exercise of quadriceps muscle results in a non-uniform fiber damage within the VMO and VL muscle and, as a consequence, non-uniform changes in membrane excitability and conduction velocity. The aim of the study was to investigate MFCV of the VMO and VL muscles before and 24 h after eccentric exercise. Multichannel surface EMG signals were concurrently recorded from the right VMO and VL muscles of 15 healthy men during sustained isometric contractions at 50% of the maximal force. Maximal voluntary force significantly reduced after eccentric exercise with respect to the pre-exercise condition (P < 0.0001). MFCV decreased over time during the sustained contractions at faster rates when assessed 24 h after exercise (VMO = -26.1; VL = -20.1) with respect to the pre-exercise condition (VMO = -9.1; VL = -13.7, P < 0.0001). Moreover, VMO showed a greater rate of reduction in MFCV over sustained contraction (26.1 ± 10.7%) in comparison with VL muscle (20.1 ± 8.5%, P < 0.025) 24 h after eccentric exercise. The result indicates that eccentric exercise contributes to a larger reduction in MFCV within the VMO muscle as compared to the VL muscle. This may abolish the ability of VMO to counteract the lateral pull of the VL muscle during knee extension, thereby leaving the knee complex more vulnerable to injury.

Higher muscle fiber conduction velocity and early rate of torque development in chronically strength-trained individuals

Strength-trained individuals (ST) develop greater levels of force compared with untrained subjects. These differences are partly of neural origin and can be explained by training-induced changes in the neural drive to the muscles. In the present study we hypothesize a greater rate of torque development (RTD) and faster recruitment of motor units with greater muscle fiber conduction velocity (MFCV) in ST compared with a control cohort. MFCV was assessed during maximal voluntary isometric explosive contractions of the elbow flexors in eight ST and eight control individuals. MFCV was estimated from high-density surface electromyogram recordings (128 electrodes) in intervals of 50 ms starting from the onset of the electromyogram. RTD and MFCV were computed and normalized to their maximal voluntary torque (MVT) values. The explosive torque of the ST was greater than in the control group in all time intervals analyzed ( P < 0.001). The absolute MFCV values were also greater for the ST than for controls at all time intervals ( P < 0.001). ST also achieved greater normalized RTD in the first 50 ms of contraction [887.6 (152) vs. 568.5 (148.66)%MVT/s, mean (SD), P < 0.001] and normalized MFCV before the rise in force compared with controls. We have shown for the first time that ST can recruit motor units with greater MFCV in a shorter amount of time compared with untrained subjects during maximal voluntary isometric explosive contractions.

NEW & NOTEWORTHY Strength-trained individuals show neuromuscular adaptations. These adaptations have been partly related to changes in the neural drive to the muscles. Here, we show for the first time that during the initial phase of a maximal isometric explosive contraction, strength-trained individuals achieve higher levels of force and recruit motor units with greater conduction velocities.

Does vibration superimposed on low-level isometric contraction alter motor unit recruitment strategy?

OBJECTIVE

Beneficial effects, including improved muscle strength and power performance, have been observed during vibration exercise (VE) and partially ascribed to a specific reflex mechanism referred to as Tonic vibration reflex (TVR). TVR involves motor unit (MU) activation synchronized and un-synchronized with the vibration cycle; this suggests VE to alter the temporal MU recruitment strategy. However, the effects of VE on MU recruitment remain poorly understood. This study aims to elucidate the influence of VE on MU recruitment indirectly, by investigating the effects of low-intensity VE on muscle activation.

APPROACH

Twenty volunteers performed isometric contractions on the biceps brachii of the right arm at a baseline (low) force equal to 30% of the maximum voluntary contraction without vibration (control) and with vibration at 20, 30, 40, and 55 Hz. Three vibration amplitudes were employed at 12.5%, 25%, and 50% of the baseline. Mean muscle-fiber conduction velocity (mCV), mean frequency (MF), and root mean square (RMS) value were estimated from surface electromyography as indicators of the alteration in MU recruitment strategies.

MAIN RESULTS

The mCV estimates during VE were significantly (p  <  0.05) higher compared to the control condition. Furthermore, six VE conditions produced significantly larger RMS values compared to control condition. The estimated MF did not show any consistent trend.

SIGNIFICANCE

These results suggest that vibration superimposed on low-level isometric contraction alters the MU recruitment strategy, activating larger and faster MUs.

Robust and accurate decoding of motoneuron behaviour and prediction of the resulting force output

KEY POINTS

The spinal alpha motoneuron is the only cell in the human CNS whose discharge can be routinely recorded in humans. We have reengineered motor unit collection and decomposition approaches, originally developed in humans, to measure the neural drive to muscle and estimate muscle force generation in the in vivo cat model. Experimental, computational, and predictive approaches are used to demonstrate the validity of this approach across a wide range of modes to activate the motor pool. The utility of this approach is shown through the ability to track individual motor units across trials, allowing for better predictions of muscle force than the electromyography signal, and providing insights in to the stereotypical discharge characteristics in response to synaptic activation of the motor pool. This approach now allows for a direct link between the intracellular data of single motoneurons, the discharge properties of motoneuron populations, and muscle force generation in the same preparation.

ABSTRACT

The discharge of a spinal alpha motoneuron and the resulting contraction of its muscle fibres represents the functional quantum of the motor system. Recent advances in the recording and decomposition of the electromyographic signal allow for the identification of several tens of concurrently active motor units. These detailed population data provide the potential to achieve deep insights into the synaptic organization of motor commands. Yet most of our understanding of the synaptic input to motoneurons is derived from intracellular recordings in animal preparations. Thus, it is necessary to extend the new electrode and decomposition methods to recording of motor unit populations in these same preparations. To achieve this goal, we use high-density electrode arrays and decomposition techniques, analogous to those developed for humans, to record and decompose the activity of tens of concurrently active motor units in a hindlimb muscle in the in vivo cat. Our results showed that the decomposition method in this animal preparation was highly accurate, with conventional two-source validation providing rates of agreement equal to or superior to those found in humans. Multidimensional reconstruction of the motor unit action potential provides the ability to accurately track the same motor unit across multiple contractions. Additionally, correlational analyses demonstrate that the composite spike train provides better estimates of whole muscle force than conventional estimates obtained from the electromyographic signal. Lastly, stark differences are observed between the modes of activation, in particular tendon vibration produced quantal interspike intervals at integer multiples of the vibration period.

Surface electromyographic amplitude does not identify differences in neural drive to synergistic muscles

Surface electromyographic (EMG) signal amplitude is typically used to compare the neural drive to muscles. We experimentally investigated this association by studying the motor unit (MU) behavior and action potentials in the vastus medialis (VM) and vastus lateralis (VL) muscles. Eighteen participants performed isometric knee extensions at four target torques [10, 30, 50, and 70% of the maximum torque (MVC)] while high-density EMG signals were recorded from the VM and VL. The absolute EMG amplitude was greater for VM than VL ( P < 0.001), whereas the EMG amplitude normalized with respect to MVC was greater for VL than VM ( P < 0.04). Because differences in EMG amplitude can be due to both differences in the neural drive and in the size of the MU action potentials, we indirectly inferred the neural drives received by the two muscles by estimating the synaptic inputs received by the corresponding motor neuron pools. For this purpose, we analyzed the increase in discharge rate from recruitment to target torque for motor units matched by recruitment threshold in the two muscles. This analysis indicated that the two muscles received similar levels of neural drive. Nonetheless, the size of the MU action potentials was greater for VM than VL ( P < 0.001), and this difference explained most of the differences in EMG amplitude between the two muscles (~63% of explained variance). These results indicate that EMG amplitude, even following normalization, does not reflect the neural drive to synergistic muscles. Moreover, absolute EMG amplitude is mainly explained by the size of MU action potentials.

NEW & NOTEWORTHY Electromyographic (EMG) amplitude is widely used to compare indirectly the strength of neural drive received by synergistic muscles. However, there are no studies validating this approach with motor unit data. Here, we compared between-muscles differences in surface EMG amplitude and motor unit behavior. The results clarify the limitations of surface EMG to interpret differences in neural drive between muscles.

Distribution of muscle fibre conduction velocity for representative samples of motor units in the full recruitment range of the tibialis anterior muscle

AIM

Motor units are recruited in an orderly manner according to the size of motor neurones. Moreover, because larger motor neurones innervate fibres with larger diameters than smaller motor neurones, motor units should be recruited orderly according to their conduction velocity (MUCV). Because of technical limitations, these relations have been previously tested either indirectly or in small motor unit samples that revealed weak associations between motor unit recruitment threshold (RT) and MUCV. Here, we analyse the relation between MUCV and RT for large samples of motor units.

METHODS

Ten healthy volunteers completed a series of isometric ankle dorsiflexions at forces up to 70% of the maximum. Multi-channel surface electromyographic signals recorded from the tibialis anterior muscle were decomposed into single motor unit action potentials, from which the corresponding motor unit RT, MUCV and action potential amplitude were estimated. Established relations between muscle fibre diameter and CV were used to estimate the fibre size.

RESULTS

Within individual subjects, the distributions of MUCV and fibre diameters were unimodal and did not show distinct populations. MUCV was strongly correlated with RT (mean (SD) R²  = 0.7 (0.09), P < 0.001; 406 motor units), which supported the hypothesis that fibre diameter is associated with RT.

CONCLUSION

The results provide further evidence for the relations between motor neurone and muscle fibre properties for large samples of motor units. The proposed methodology for motor unit analysis has also the potential to open new perspectives in the study of chronic and acute neuromuscular adaptations to ageing, training and pathology.

Tracking motor units longitudinally across experimental sessions with high-density surface electromyography

KEY POINTS

Classic motor unit (MU) recording and analysis methods do not allow the same MUs to be tracked across different experimental sessions, and therefore, there is limited experimental evidence on the adjustments in MU properties following training or during the progression of neuromuscular disorders. We propose a new processing method to track the same MUs across experimental sessions (separated by weeks) by using high-density surface electromyography. The application of the proposed method in two experiments showed that individual MUs can be identified reliably in measurements separated by weeks and that changes in properties of the tracked MUs across experimental sessions can be identified with high sensitivity. These results indicate that the behaviour and properties of the same MUs can be monitored across multiple testing sessions. The proposed method opens new possibilities in the understanding of adjustments in motor unit properties due to training interventions or the progression of pathologies.

ABSTRACT

A new method is proposed for tracking individual motor units (MUs) across multiple experimental sessions on different days. The technique is based on a novel decomposition approach for high-density surface electromyography and was tested with two experimental studies for reliability and sensitivity. Experiment I (reliability): ten participants performed isometric knee extensions at 10, 30, 50 and 70% of their maximum voluntary contraction (MVC) force in three sessions, each separated by 1 week. Experiment II (sensitivity): seven participants performed 2 weeks of endurance training (cycling) and were tested pre-post intervention during isometric knee extensions at 10 and 30% MVC. The reliability (Experiment I) and sensitivity (Experiment II) of the measured MU properties were compared for the MUs tracked across sessions, with respect to all MUs identified in each session. In Experiment I, on average 38.3% and 40.1% of the identified MUs could be tracked across two sessions (1 and 2 weeks apart), for the vastus medialis and vastus lateralis, respectively. Moreover, the properties of the tracked MUs were more reliable across sessions than those of the full set of identified MUs (intra-class correlation coefficients ranged between 0.63-0.99 and 0.39-0.95, respectively). In Experiment II, ∼40% of the MUs could be tracked before and after the training intervention and training-induced changes in MU conduction velocity had an effect size of 2.1 (tracked MUs) and 1.5 (group of all identified motor units). These results show the possibility of monitoring MU properties longitudinally to document the effect of interventions or the progression of neuromuscular disorders.

Associations between motor unit action potential parameters and surface EMG features

The surface interference EMG signal provides some information on the neural drive to muscles. However, the association between neural drive to muscle and muscle activation has long been debated with controversial indications due to the unavailability of motor unit population data. In this study, we clarify the potential and limitations of interference EMG analysis to infer motor unit recruitment strategies with an experimental investigation of several concurrently active motor units and of the associated features of the surface EMG. For this purpose, we recorded high-density surface EMG signals during linearly increasing force contractions of the tibialis anterior muscle, up to 70% of maximal force. The recruitment threshold (RT), conduction velocity (MUCV), median frequency (MDF_MU), and amplitude (RMS_MU) of action potentials of 587 motor units from 13 individuals were assessed and associated with features of the interference EMG. MUCV was positively associated with RT (R² = 0.64 ± 0.14), whereas MDF_MU and RMS_MU showed a weaker relation with RT (R² = 0.11 ± 0.11 and 0.39 ± 0.24, respectively). Moreover, the changes in average conduction velocity estimated from the interference EMG predicted well the changes in MUCV (R² = 0.71), with a strong association to ankle dorsiflexion force (R² = 0.81 ± 0.12). Conversely, both the average EMG MDF and RMS were poorly associated with motor unit recruitment. These results clarify the limitations of EMG spectral and amplitude analysis in inferring the neural strategies of muscle control and indicate that, conversely, the average conduction velocity could provide relevant information on these strategies.NEW & NOTEWORTHY The surface EMG provides information on the neural drive to muscles. However, the associations between EMG features and neural drive have been long debated due to unavailability of motor unit population data. Here, by using novel highly accurate decomposition of the EMG, we related motor unit population behavior to a wide range of voluntary forces. The results fully clarify the potential and limitation of the surface EMG to provide estimates of the neural drive to muscles.

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.

Detection of Multiple Innervation Zones from Multi-Channel Surface EMG Recordings with Low Signal-to-Noise Ratio Using Graph-Cut Segmentation

Knowledge of the location of muscle Innervation Zones (IZs) is important in many applications, e.g. for minimizing the quantity of injected botulinum toxin for the treatment of spasticity or for deciding on the type of episiotomy during child delivery. Surface EMG (sEMG) can be noninvasively recorded to assess physiological and morphological characteristics of contracting muscles. However, it is not often possible to record signals of high quality. Moreover, muscles could have multiple IZs, which should all be identified. We designed a fully-automatic algorithm based on the enhanced image Graph-Cut segmentation and morphological image processing methods to identify up to five IZs in 60-ms intervals of very-low to moderate quality sEMG signal detected with multi-channel electrodes (20 bipolar channels with Inter Electrode Distance (IED) of 5 mm). An anisotropic multilayered cylinder model was used to simulate 750 sEMG signals with signal-to-noise ratio ranging from -5 to 15 dB (using Gaussian noise) and in each 60-ms signal frame, 1 to 5 IZs were included. The micro- and macro- averaged performance indices were then reported for the proposed IZ detection algorithm. In the micro-averaging procedure, the number of True Positives, False Positives and False Negatives in each frame were summed up to generate cumulative measures. In the macro-averaging, on the other hand, precision and recall were calculated for each frame and their averages are used to determine F1-score. Overall, the micro (macro)-averaged sensitivity, precision and F1-score of the algorithm for IZ channel identification were 82.7% (87.5%), 92.9% (94.0%) and 87.5% (90.6%), respectively. For the correctly identified IZ locations, the average bias error was of 0.02±0.10 IED ratio. Also, the average absolute conduction velocity estimation error was 0.41±0.40 m/s for such frames. The sensitivity analysis including increasing IED and reducing interpolation coefficient for time samples was performed. Meanwhile, the effect of adding power-line interference and using other image interpolation methods on the deterioration of the performance of the proposed algorithm was investigated. The average running time of the proposed algorithm on each 60-ms sEMG frame was 25.5±8.9 (s) on an Intel dual-core 1.83 GHz CPU with 2 GB of RAM. The proposed algorithm correctly and precisely identified multiple IZs in each signal epoch in a wide range of signal quality and is thus a promising new offline tool for electrophysiological studies.

Towards Real-Time Estimation of Muscle-Fiber Conduction Velocity Using Delay-Locked Loop

Decrease in muscle-fiber conduction velocity (MFCV) during sustained contraction has been widely accepted as myoelectric manifestation of muscle fatigue. Several methods have been proposed in the literature for MFCV estimation by analysing surface electromyography (EMG), e.g., cross-correlation (CC) function and maximum likelihood (ML). However, for all the availablemethods, windowing of the EMG signal and computationally demanding calculations are required, limiting the possibility to continuously monitor muscle fatigue in real time. In the present study, an adaptive scheme is proposed that permits real-time estimation of MFCV. The proposed scheme is based on a delay-lockedloop (DLL). Asecond-orderloop is adopted to track the delay variationover time. An error filter is employed to approximate a ML estimation in case of colored noise. Furthermore, the DLL system is extended for multichannel CV estimation. The performance of the proposed method is evaluated by both dedicated simulations and real EMG signals. Our results show the accuracy of the proposed method to be comparable to that of theML method formuch lower (1/40) computational complexity, especially suited for real-time MFCV measurements. Use of this method can enable new studies onmyoelectric fatigue, possibly leading to new insight on the underlying physiological processes.

The effect of lymph drainage on the myoelectric manifestation of vastus lateralis fatigue: Preliminary results

Variations in surface electromyograms (EMGs) collected from the vastus lateralis muscle during isometric fatiguing contractions were investigated pre-post lymphatic drainage (intervention group, N=3) and pre-post rest (control group, N=3). The slope of conduction velocity and of EMG amplitude and spectral descriptors was computed from the start to the failure time; the instant after which subjects could not endure contractions. When compared to subjects in the control group, those in the intervention group endured longer. Similarly, muscle fatigue affected to a lesser extent EMGs following lymphatic drainage than following rest. These preliminary results suggest the lymphatic drainage may potentially delay muscle fatigue.

High-density surface electromyography provides reliable estimates of motor unit behavior

OBJECTIVE

To assess the intra- and inter-session reliability of estimates of motor unit behavior and muscle fiber properties derived from high-density surface electromyography (HDEMG).

METHODS

Ten healthy subjects performed submaximal isometric knee extensions during three recording sessions (separate days) at 10%, 30%, 50% and 70% of their maximum voluntary effort. The discharge timings of motor units of the vastus lateralis and medialis muscles were automatically identified from HDEMG by a decomposition algorithm. We characterized the number of detected motor units, their discharge rates, the coefficient of variation of their inter-spike intervals (CoVisi), the action potential conduction velocity and peak-to-peak amplitude. Reliability was assessed for each motor unit characteristics by intra-class correlation coefficient (ICC). Additionally, a pulse-to-noise ratio (PNR) was calculated, to verify the accuracy of the decomposition.

RESULTS

Good to excellent reliability within and between sessions was found for all motor unit characteristics at all force levels (ICCs>0.8), with the exception of CoVisi that presented poor reliability (ICC<0.6). PNR was high and similar for both muscles with values ranging between 45.1 and 47.6dB (accuracy>95%).

CONCLUSION

Motor unit features can be assessed non-invasively and reliably within and across sessions over a wide range of force levels.

SIGNIFICANCE

These results suggest that it is possible to characterize motor units in longitudinal intervention studies.

Motor Neuron Pools of Synergistic Thigh Muscles Share Most of Their Synaptic Input

Neural control of synergist muscles is not well understood. Presumably, each muscle in a synergistic group receives some unique neural drive and some drive that is also shared in common with other muscles in the group. In this investigation, we sought to characterize the strength, frequency spectrum, and force dependence of the neural drive to the human vastus lateralis and vastus medialis muscles during the production of isometric knee extension forces at 10 and 30% of maximum voluntary effort. High-density surface electromyography recordings were decomposed into motor unit action potentials to examine the neural drive to each muscle. Motor unit coherence analysis was used to characterize the total neural drive to each muscle and the drive shared between muscles. Using a novel approach based on partial coherence analysis, we were also able to study specifically the neural drive unique to each muscle (not shared). The results showed that the majority of neural drive to the vasti muscles was a cross-muscle drive characterized by a force-dependent strength and bandwidth. Muscle-specific neural drive was at low frequencies (<5 Hz) and relatively weak. Frequencies of neural drive associated with afferent feedback (6-12 Hz) and with descending cortical input (∼20 Hz) were almost entirely shared by the two muscles, whereas low-frequency (<5 Hz) drive comprised shared (primary) and muscle-specific (secondary) components. This study is the first to directly investigate the extent of shared versus independent control of synergist muscles at the motor neuron level.

SIGNIFICANCE STATEMENT

Precisely how the nervous system coordinates the activity of synergist muscles is not well understood. One possibility is that muscles of a synergy share a common neural drive. In this study, we directly compared the relative strength of shared versus independent neural drive to synergistically activated thigh muscles in humans. The results of this analysis support the notion that synergistically activated muscles share most of their neural drive. Scientifically, this study addressed an important gap in our current understanding of how neural drive is delivered to synergist muscles. We have also demonstrated the feasibility of a novel approach to the study of muscle synergies based on partial coherence analysis of motor unit activity.

Analysis of Vibration Exercise at Varying Frequencies by Different Fatigue Estimators

Vibration exercise (VE) has been suggested to improve muscle strength and power performance, due to enhanced neuromuscular demand. However, understanding of the most appropriate VE protocols is lacking, limiting the optimal use of VE in rehabilitation programs. In this study, the fatiguing effect of vibration at different frequencies was investigated by employing a force-modulation VE system. Twenty volunteers performed 12-s isometric contractions of the biceps brachii with a load consisting of a baseline force of 80% of their maximum voluntary contraction (MVC) and a superimposed sinusoidal force at 0 (control condition with no vibration), 20, 30, and 40 Hz. Mechanical fatigue was estimated by assessment of MVC decay after each task while myoelectric fatigue was estimated by analysis of multichannel electromyography (EMG) signals recorded during VE. EMG conduction velocity, spectral compression, power, and fractal dimension were estimated as indicators of myoelectric fatigue. Our results suggest vibration, in particular at 30 Hz, to produce a larger degree of fatigue as compared to control condition. These results motivate further research aiming at introducing VE in rehabilitation programs with improved training protocols.

Motor unit action potential conduction velocity estimated from surface electromyographic signals using image processing techniques

In surface electromyography (surface EMG, or S-EMG), conduction velocity (CV) refers to the velocity at which the motor unit action potentials (MUAPs) propagate along the muscle fibers, during contractions. The CV is related to the type and diameter of the muscle fibers, ion concentration, pH, and firing rate of the motor units (MUs). The CV can be used in the evaluation of contractile properties of MUs, and of muscle fatigue. The most popular methods for CV estimation are those based on maximum likelihood estimation (MLE). This work proposes an algorithm for estimating CV from S-EMG signals, using digital image processing techniques. The proposed approach is demonstrated and evaluated, using both simulated and experimentally-acquired multichannel S-EMG signals. We show that the proposed algorithm is as precise and accurate as the MLE method in typical conditions of noise and CV. The proposed method is not susceptible to errors associated with MUAP propagation direction or inadequate initialization parameters, which are common with the MLE algorithm. Image processing -based approaches may be useful in S-EMG analysis to extract different physiological parameters from multichannel S-EMG signals. Other new methods based on image processing could also be developed to help solving other tasks in EMG analysis, such as estimation of the CV for individual MUs, localization and tracking of innervation zones, and study of MU recruitment strategies.

Spatial variability of muscle activity during human walking: the effects of different EMG normalization approaches

Human leg muscles are often activated inhomogeneously, e.g. in standing. This may also occur in complex tasks like walking. Thus, bipolar surface electromyography (sEMG) may not accurately represent whole muscle activity. This study used 64-electrode high-density sEMG (HD-sEMG) to examine spatial variability of lateral gastrocnemius (LG) muscle activity during the stance phase of walking, maximal voluntary contractions (MVCs) and maximal M-waves, and determined the effects of different normalization approaches on spatial and inter-participant variability. Plantar flexion MVC, maximal electrically elicited M-waves and walking at self-selected speed were recorded in eight healthy males aged 24-34. sEMG signals were assessed in four ways: unnormalized, and normalized to MVC, M-wave or peak sEMG during the stance phase of walking. During walking, LG activity varied spatially, and was largest in the distal and lateral regions. Spatial variability fluctuated throughout the stance phase. Normalizing walking EMG signals to the peak value during stance reduced spatial variability within LG on average by 70%, and inter-participant variability by 67%. Normalizing to MVC reduced spatial variability by 17% but increased inter-participant variability by 230%. Normalizing to M-wave produced the greatest spatial variability (45% greater than unnormalized EMG) and increased inter-participant variability by 70%. Unnormalized bipolar LG sEMG may provide misleading results about representative muscle activity in walking due to spatial variability. For the peak value and MVC approaches, different electrode locations likely have minor effects on normalized results, whereas electrode location should be carefully considered when normalizing walking sEMG data to maximal M-waves.

Novel cross correlation technique allows crosstalk resistant reflex detection from surface EMG

Existing methods for withdrawal reflex detection from surface electromyography (sEMG) do not consider the potential presence of electrical crosstalk, which in practical applications may entail reduced detection accuracy. This study estimated muscle fiber conduction velocities (CV) for the tibialis anterior (TA) and soleus (SOL) muscles of both genuine reflexes and identified crosstalk, measured during antagonistic reflex responses. These estimations were used to develop and assess a novel method for reflex detection resistant to crosstalk. Cross correlations of two single differential (SD) sEMG signals recorded along the muscle fibers were performed and two features were extracted from the resulting correlograms (average CV and maximal cross correlation). Reflex detection based on evaluation of the extracted features was compared to a conventional reflex detection method (thresholding of interval peak z-scores), applied on both SD and double differential (DD) sEMG. Intramuscular electromyography (iEMG) was used as validation for reflex detection. Apparent CV due to electrical crosstalk alone were more than one order of magnitude higher than CV estimated for genuine reflexes. Conventional reflex detection showed excellent sensitivity but poor specificity (0.19-0.76) due to the presence of crosstalk. In contrast, cross correlation analysis allowed reflex detection with significantly improved specificity (0.91-0.97). The developed methodology may be readily implemented for more reliable reflex detection.

Spatial distribution of surface action potentials generated by individual motor units in the human biceps brachii muscle

This study analyses the spatial distribution of individual motor unit potentials (MUPs) over the skin surface and the influence of motor unit depth and recording configuration on this distribution. Multichannel surface (13×5 electrode grid) and intramuscular (wire electrodes inserted with needles of lengths 15 and 25mm) electromyographic (EMG) signals were concurrently recorded with monopolar derivations from the biceps brachii muscle of 10 healthy subjects during 60-s isometric contractions at 20% of the maximum torque. Multichannel monopolar MUPs of the target motor unit were obtained by spike-triggered averaging of the surface EMG. Amplitude and frequency characteristics of monopolar and bipolar MUPs were calculated for locations along the fibers' direction (longitudinal), and along the direction perpendicular (transverse) to the fibers. In the longitudinal direction, monopolar and bipolar MUPs exhibited marked amplitude changes that extended for 16-32mm and 16-24mm over the innervation and tendon zones, respectively. The variation of monopolar and bipolar MUP characteristics was not symmetrical about the innervation zone. Motor unit depth had a considerable influence on the relative longitudinal variation of amplitude for monopolar MUPs, but not for bipolar MUPs. The transverse extension of bipolar MUPs ranged between 24 and 32mm, whereas that of monopolar MUPs ranged between 72 and 96mm. The mean power spectral frequency of surface MUPs was highly dependent on the transverse electrode location but not on depth. This study provides a basis for the interpretation of the contribution of individual motor units to the interference surface EMG signal.

Analysis of muscle fiber conduction velocity enables reliable detection of surface EMG crosstalk during detection of nociceptive withdrawal reflexes

Background

The nociceptive withdrawal reflex (NWR) is a polysynaptic spinal reflex that induces complex muscle synergies to withdraw a limb from a potential noxious stimulus. Several studies indicate that assessment of the NWR is a valuable objective tool in relation to investigation of various pain conditions. However, existing methodologies for NWR assessment evaluate standard surface electromyography (sEMG) measured over just one muscle and do not consider the possible interference of crosstalk originating from adjacent active muscles. The present study had two aims: firstly, to investigate to which extent the presence of crosstalk may affect NWR detection using a standardized scoring criterion (interval peak z-score) that has been validated without taking crosstalk into consideration. Secondly, to investigate whether estimation of muscle fiber conduction velocity can help identifying the propagating and non-propagating nature of genuine reflexes and crosstalk respectively, thus allowing a more valid assessment of the NWR.

Results

Evaluation of interval peak z-score did apparently allow reflex detection with high sensitivity and specificity (0.96), but only if the influence of crosstalk was ignored. Distinction between genuine reflexes and crosstalk revealed that evaluation of interval peak z-score incorporating a z-score threshold of 12 was associated with poor reflex detection specificity (0.26-0.62) due to the presence of crosstalk. Two different standardized methods for estimation of muscle fiber conduction velocity were employed to demonstrate that significantly different muscle fiber conduction velocities may be estimated during genuine reflexes and crosstalk, respectively. This discriminative feature was used to develop and evaluate a novel methodology for reflex detection from sEMG that is robust with respect to crosstalk. Application of this conduction velocity analysis (CVA) entailed reflex detection with excellent sensitivity (1.00 and 1.00) and specificity (1.00 and 0.96) for the tibialis anterior and soleus muscles.

Conclusion

This study investigated the negative effect of electrical crosstalk during reflex detection and revealed that the use of a previously validated scoring criterion may result in poor specificity due to crosstalk. The excellent performance of the developed methodology in the presence of crosstalk shows that assessment of muscle fiber conduction velocity allows reliable detection of EMG crosstalk during reflex detection.

Estimation of impulse response between electromyogram signals for use in conduction delay distribution estimation

The time delay between two surface electromyograms (EMGs) acquired along the conduction path is used to estimate mean action potential conduction velocity. Modeling the linear impulse response between "upstream" and "downstream" EMG signals permits an estimate of the distribution of velocities, providing more information. In this work, we analyzed EMG from bipolar electrodes placed on the tibialis anterior of 36 subjects, using an inter-electrode distance of 10 mm. Regularized least squares was used to fit the coefficients of a finite impulse response model. We trained the model on one recording, then tested on two others. The optimum correlation between the model-predicted and actual EMG averaged 0.70. We also compared estimation of the mean conduction delay from the peak time of the impulse response to the "gold standard" peak time of the cross-correlation between the upstream and downstream EMG signals. Optimal models differed from the gold standard by 0.02 ms, on average. Model performance was influenced by the regularization parameters. The impulse responses, however, incorrectly contained substantive power at very low time delays, causing delay distribution estimates to exhibit high probabilities at very short conduction delays. Unrealistic distribution estimates resulted. Larger inter-electrode spacing may be required to alleviate this limitation.

Modeling the impulse response between pairs of EMG signals to estimate conduction delay distribution

Mean electromyogram (EMG) conduction delay is often estimated as the average time delay between two surface EMG recordings arranged along the conduction path. It has previously been shown that the complete distribution of conduction delays can be estimated from the impulse response relating the "upstream" EMG recording to the "downstream" recording. In this work, we examined regularized least squares methods for estimating the impulse response, namely the pseudo-inverse with small singular values discarded and post hoc lowpass filtering. Performance was evaluated by training the model to one recording, then testing on others. Correlation between model-predicted EMG and measured EMG was assessed for 36 subjects, using EMG recordings with 5 mm inter-electrode spacing. The best correlation was 0.86, on average, for both regularization methods. We additionally compared the mean conduction delay computed from the "gold standard" cross-correlation method to the peak time of the impulse response. The best models differed by 0.01 ms, on average, for both regularization methods. Nonetheless, the impulse responses exhibited excessive energy near zero time, causing delay distribution estimates to exhibit high probabilities at unphysiological short time delays. Inter-electrode spacing larger than 5 mm may be required to alleviate this limitation.

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.

Assessment of the electrophysiological properties of the muscle fibers of a transplanted hand

BACKGROUND

The muscle fibers in a transplanted hand remain denervated for a long period of time after the transplant. This prolonged inactivity may change the electrophysiological membrane properties of muscle fibers, as observed in long-term denervation. We investigated whether electrophysiological properties of the muscle fibers are preserved in a transplanted hand even after several months of denervation. Specifically, we assessed the dependence of muscle fiber conduction velocity (CV) on discharge rate in motor units of the abductor digiti minimi muscle.

METHODS

Surface electromyography signals were recorded from the transplanted hand of a patient who was 35 years of age at the time of the transplant. In each of 11 experimental sessions performed over a period of 23 months after the transplant, the subject was asked to linearly increase the activation or to maintain a maximum activation of the abductor digiti minimi muscle for 60 sec. Individual motor unit action potentials were identified from the electromyography recordings and muscle fiber CV was estimated for each action potential as a function of the time interval separating the action potential from the preceding discharge (interspike interval [ISI]).

RESULTS

The baseline (ISI >1000 msec) CV was 3.8±0.3 m/sec. CV decreased monotonically with increasing ISI (R=0.95). For ISI in the range 0 to 10 msec, muscle fiber CV was 24.9%±16.3% higher than the baseline value (P<0.05).

CONCLUSIONS

The results indicate that in the investigated muscle, the baseline value of CV and its dependency on discharge rate were similar as in able-bodied individuals, despite a period of several months of denervation.

History dependence of human muscle-fiber conduction velocity during voluntary isometric contractions

The conduction velocity (CV) of a muscle fiber is affected by the fiber's discharge history going back ∼1 s. We investigated this dependence by measuring CV fluctuations during voluntary isometric contractions of the human brachioradialis muscle. We recorded electromyogram (EMG) signals simultaneously from multiple intramuscular electrodes, identified potentials belonging to the same motor unit using EMG decomposition, and estimated the CV of each discharge from the interpotential interval. In 12 of 14 subjects, CV increased by ∼10% during the first second after recruitment and then fluctuated by about ±2% in a way that mirrored the fluctuations in the instantaneous firing rate. The CV profile could be precisely described in terms of the discharge history by a simple mathematical model. In the other two subjects, and one subject retested after cooling the arm, the CV fluctuations were inversely correlated with instantaneous firing rate. In all subjects, CV was additionally affected by very short interdischarge intervals (<25 ms): it was increased in doublets at recruitment, but decreased in doublets during continuous firing and after short interdischarge intervals in doubly innervated fibers. CV also exhibited a slow trend of about -0.05%/s that did not depend on the immediate discharge history. We suggest that measurements of CV fluctuations during voluntary contractions, or during stimulation protocols that involve longer and more complex stimulation patterns than are currently being used, may provide a sensitive approach for estimating the dynamic characteristics of ion channels in the human muscle-fiber membrane.

On the behavior of surface electromyographic variables during the menstrual cycle

The goal of this work is to study the behavior of electromyographic variables during the menstrual cycle. Ten female volunteers (24.0 ± 2.8 years of age) performed fatiguing isometric contractions, and electromyographic signals were measured on the biceps brachii in four phases of the menstrual cycle. Adaptations of classical algorithms were used for the estimation of the root mean square (RMS) value, absolute rectified value (ARV), mean frequency (MNF), median frequency (MDF), and conduction velocity (CV). The CV estimator had a higher (p = 0.002) rate of decrease at the end of the follicular phase and at the end of the luteal phase. The MDF (p = 0.002) and MNF (p = 0.004) estimators had a higher rate of decrease at the beginning of the follicular phase and at the end of the luteal phase. No significant differences between phases of the menstrual cycle were detected with the ARV and RMS estimators (p > 0.05). These results suggest that the behavior of the muscles in women presents different characteristics during different phases of the menstrual cycle. In particular, women were more susceptible to fatigue at the end of the luteal phase.