Amplitude cancellation reduces the size of motor unit potentials averaged from the surface EMG

Adaptive EMG decomposition in dynamic conditions based on online learning metrics with tunable hyperparameters

Objective. Developing neural decoders robust to non-stationary conditions is essential to ensure their long-term accuracy and stability. This is particularly important when decoding the neural drive to muscles during dynamic contractions, which pose significant challenges for stationary decoders.Approach. We propose a novel adaptive electromyography (EMG) decomposition algorithm that builds on blind source separation methods by leveraging the Kullback-Leibler divergence and kurtosis of the signals as metrics for online learning. The proposed approach provides a theoretical framework to tune the adaptation hyperparameters and compensate for non-stationarities in the mixing matrix, such as due to dynamic contractions, and to identify the underlying motor neuron (MN) discharges. The adaptation is performed in real-time (∼22 ms of computational time per 100 ms batches).Main results. The hyperparameters of the proposed adaptation captured anatomical differences between recording locations (forearm vs wrist) and generalised across subjects. Once optimised, the proposed adaptation algorithm significantly improved all decomposition performance metrics with respect to the absence of adaptation in a wide range of motion of the wrist (80∘). The rate of agreement, sensitivity, and precision were⩾90%in⩾80%of the cases in both simulated and experimentally recorded data, according to a two-source validation approach.Significance. The findings demonstrate the suitability of the proposed online learning metrics and hyperparameter optimisation to compensate the induced modulation and accurately decode MN discharges in dynamic conditions. Moreover, the study proposes an experimental validation method for EMG decomposition in dynamic tasks.

Comparison of strategies for assessment of rate of torque development in older and younger adults

There is increasing appreciation of the role of rate of torque development (RTD) in physical function of older adults (OAs). This study compared various RTD strategies and electromyography (EMG) in the knee extensors and focused on discriminating groups with potential limitations in voluntary activation (VA) and associations of different RTD indices with functional tests that may be affected by VA in OAs. Neuromuscular function was assessed in 20 younger adults (YAs, 22.0 ± 1.7 years) and 50 OAs (74.4 ± 7.0 years). Isometric ballistic and peak torque during maximal voluntary contractions (pkTMVC), doublet stimulation and surface EMG were assessed and used to calculate VA during pkTMVC and RTD and rate of EMG rise during ballistic contractions. Select mobility tests (e.g., gait speed, 5× chair rise) were also assessed in the OAs. Voluntary RTD and RTD normalized to pkTMVC, doublet torque, and peak doublet RTD were compared. Rate of EMG rise and voluntary RTD normalized to pkTMVC did not differ between OAs and YAs, nor were they associated with functional test scores. Voluntary RTD indices normalized to stimulated torque parameters were significantly associated with VA (r = 0.319-0.459), and both indices were significantly lower in OAs vs YAs (all p < 0.020). These RTD indices showed significant association with the majority of mobility tests, but there was no clear advantage among them. Thus, voluntary RTD normalized to pkTMVC was ill-suited for use in OAs, while results suggests that voluntary RTD normalized to stimulated torque parameters may be useful for identifying central mechanisms of RTD impairment in OAs.Clinical trial registration number NCT02505529; date of registration 07/22/2015.

Optimal Motor Unit Subset Selection for Accurate Motor Intention Decoding: Towards Dexterous Real-Time Interfacing

OBJECTIVE

Motor unit (MU) discharge timings encode human motor intentions to the finest degree. Whilst tapping into such information can bring significant gains to a range of applications, current approaches to MU decoding from surface signals do not scale well with the demands of dexterous human-machine interfacing (HMI). To optimize the forward estimation accuracy and time-efficiency of such systems, we propose the inclusion of task-wise initialization and MU subset selection.

METHODS

Offline analyses were conducted on data recorded from 11 non-disabled subjects. Task-wise decomposition was applied to identify MUs from high-density surface electromyography (HD-sEMG) pertaining to 18 wrist/forearm motor tasks. The activities of a selected subset of MUs were extracted from test data and used for forward estimation of intended motor tasks and joint kinematics. To that end, various combinations of subset selection and estimation algorithms (both regression and classification-based) were tested for a range of subset sizes.

RESULTS

The mutual information-based minimum Redundancy Maximum Relevance (mRMR-MI) criterion retained MUs with the highest predicative power. When the portion of tracked MUs was reduced down to 25%, the regression performance decreased only by 3% (R2=0.79) while classification accuracy dropped by 2.7% (accuracy = 74%) when kernel-based estimators were considered.

CONCLUSION AND SIGNIFICANCE

Careful selection of tracked MUs can optimize the efficiency of MU-driven interfacing. In particular, prioritization of MUs exhibiting strong nonlinear relationships with target motions is best leveraged by kernel-based estimators. Hence, this frees resources for more robust and adaptive MU decoding techniques to be implemented in future.

Characterization of Motor Unit Firing and Twitch Properties for Decoding Musculoskeletal Force in the Human Ankle Joint In Vivo

Understanding how motor units (MUs) contribute to skeletal mechanical force is crucial for unraveling the underlying mechanism of human movement. Alterations in MU firing, contractile and force-generating properties emerge in response to physical training, aging or injury. However, how changes in MU firing and twitch properties dictate skeletal muscle force generation in healthy and impaired individuals remains an open question. In this work, we present a MU-specific approach to identify firing and twitch properties of MU samples and employ them to decode musculoskeletal function in vivo. First, MU firing events were decomposed offline from high-density electromyography (HD-EMG) of six lower leg muscles involved in ankle plantar-dorsi flexion. We characterized their twitch responses based on the statistical distributions of their firing properties and employed them to compute MU-specific activation dynamics. Subsequently, we decoded ankle joint moments by linking our framework to a subject-specific musculoskeletal model. We validated our approach at different ankle positions and levels of activation and compared it with traditional EMG-driven models. Our proposed MU-specific formulation achieves higher generalization across conditions than the EMG-driven models, with significantly lower coefficients of variation in torque predictions. Furthermore, our approach shows distinct neural strategies across a large repertoire of contractile conditions in different muscles. Our proposed approach may open new avenues for characterizing the relationship between MU firing and twitch properties and their influence on force capacity. This can facilitate the development of targeted rehabilitation strategies tailored to individuals with specific neuromuscular conditions.

Surface electromyographic frequency characteristics of the quadriceps differ between continuous high- and low-torque isometric knee extension to momentary failure

Surface EMG (sEMG) has been used to compare loading conditions during exercise. Studies often explore mean/median frequencies. This potentially misses more nuanced electrophysiological differences between exercise tasks. Therefore, wavelet-based analysis was used to evaluate electrophysiological characteristics in the sEMG signal of the quadriceps under both higher- and lower-torque (70 % and 30 % of MVC, respectively) isometric knee extension performed to momentary failure. Ten recreationally active adult males with previous resistance training experience were recruited. Using a within-session, repeated-measures, randomised crossover design, participants performed isometric knee extension whilst sEMG was collected from the vastus medialis (VM), rectus femoris (RF) and vastus lateralis (VL). Mean signal frequency showed similar characteristics in each condition at momentary failure. However, individual wavelets revealed different frequency component changes between the conditions. All frequency components increased during the low-torque condition. But low-frequency components increased, and high-frequency components decreased, in intensity throughout the high-torque condition. This resulted in convergence of the low-torque and high-torque trial wavelet characteristics towards the end of the low-torque trial. Our results demonstrate a convergence of myoelectric signal properties between low- and high-torque efforts with fatigue via divergent signal adaptations. Further work should disentangle factors influencing frequency characteristics during exercise tasks.

Sex differences in the detection of motor unit action potentials identified using high-density surface electromyography

Sex-related disparities in force production of humans have been widely observed. Previous literature has attributed differences in peripheral traits, such as muscle size, to explain these disparities. However, less is known about potential sex-related differences in central neuromuscular traits and many comparable studies, not exploring sex-related differences, exhibit a selection-bias in the recruitment of subjects making the generalization of their findings difficult. Utilizing high-density electromyography arrays and motor unit (MU) decomposition, the aim of the current study is to compare MU yield and discharge properties of the tibialis anterior between male and female humans. Twenty-four subjects (10 females) performed two submaximal (20%) isometric dorsiflexion contractions. On average, males yielded nearly twice the amount of MUs as females. Further, females had significantly higher MU discharge rate, lower MU action potential amplitude, and lower MU action potential frequency content than males despite similar levels of torque and MU discharge variability. These findings suggest differences in central neuromuscular control of force production between sexes; however, it is unclear how lower yield counts affect the accuracy of these results.

Greater Neuromuscular Fatigue Following Low Load Blood Flow Restriction than Non Blood Flow Restriction Resistance Exercise Among Recreationally Active Men

PURPOSE

The purpose of this study was to examine the acute effects of low-load blood flow restriction (LLBFR) and low-load non-BFR (LL) on neuromuscular function following a bout of standardized, fatiguing leg extension muscle actions.

METHODS

Fourteen men (mean age ± SD = 23±4 yrs) volunteered to participate in this investigation and randomly performed LLBFR and LL on separate days. Resistance exercise consisted of 75 isotonic, unilateral leg extension muscle actions performed at 30% of one-repetition maximum. Prior to (pretest) and after (posttest) performing each bout of exercise, strength and neural assessments were determined.

RESULTS

There was no pretest to posttest differences between LLBFR and LL for maximal voluntary isometric contraction (MVIC) torque or V-wave/M-wave responses (muscle compound action potentials assessed during a superimposed MVIC muscle action) which exhibited decreases (collapsed across condition) of 41.2% and 26.2%, respectively. There were pretest to posttest decreases in peak twitch torque (36.0%) and sEMG (29.5%) for LLBFR but not LL, and larger decreases in voluntary activation for LLBFR (11.3%) than LL (4.5%).

CONCLUSIONS

These findings suggested that LLBFR elicited greater fatigue-induced decreases in several indices of neuromuscular function relative to LL. Despite this, both LLBFR and LL resulted in similar decrements in performance as assessed by maximal strength.

Far-field electric potentials provide access to the output from the spinal cord from wrist-mounted sensors

OBJECTIVE

Neural interfaces need to become more unobtrusive and socially acceptable to appeal to general consumers outside rehabilitation settings.

APPROACH

We developed a non-invasive neural interface that provides access to spinal motor neuron activities from the wrist, which is the preferred location for a wearable. The interface decodes far-field potentials present at the tendon endings of the forearm muscles using blind source separation. First, we evaluated the reliability of the interface to detect motor neuron firings based on far-field potentials, and thereafter we used the decoded motor neuron activity for the prediction of finger contractions in offline and real-time conditions.

MAIN RESULTS

The results showed that motor neuron activity decoded from the far-field potentials at the wrist accurately predicted individual and combined finger commands and therefore allowed for highly accurate real-time task classification.

SIGNIFICANCE

These findings demonstrate the feasibility of a non-invasive, neural interface at the wrist for precise real-time control based on the output of the spinal cord.

Distribution of motor unit properties across human muscles

The purpose of our review was to compare the distribution of motor unit properties across human muscles of different sizes and recruitment ranges. Although motor units can be distinguished based on several different attributes, we focused on four key parameters that have a significant influence on the force produced by muscle during voluntary contractions: the number of motor units, average innervation number, the distributions of contractile characteristics, and discharge rates within motor unit pools. Despite relatively few publications on this topic, current data indicate that the most influential factor in the distribution of these motor unit properties between muscles is innervation number. Nonetheless, despite a fivefold difference in innervation number between a hand muscle (first dorsal interosseus) and a lower leg muscle (tibialis anterior), the general organization of their motor unit pools, and the range of discharge rates appear to be relatively similar. These observations provide foundational knowledge for studies on the control of movement and the changes that occur with aging and neurological disorders.

Antagonist surface electromyogram decomposition and the case of the missing motor units

Reece & Herda (2021) reported that an antagonist muscle exhibited an organized motor unit (MU) recruitment scheme during isometric elbow flexion contractions. This control scheme, however, differed from the typical MU control scheme in that MU firing rates did not change between force levels (40% and 70% MVC) in the triceps brachii when it acted as an antagonist to isometric elbow flexion. Here we suggest technological considerations with evidence that may have affected these findings. Additionally, we highlight how this paper offers a promising starting point from which further insight into antagonist MU behaviour can be gathered non-invasively, and suggest future research directions to improve our understanding of MU activity of antagonist muscles in the upper limb.

Physiological complexity: influence of ageing, disease and neuromuscular fatigue on muscle force and torque fluctuations

NEW FINDINGS

What is the topic of this review? Physiological complexity in muscle force and torque fluctuations, specifically the quantification of complexity, how neuromuscular complexityis altered by perturbations and the potential mechanism underlying changes in neuromuscular complexity. What advances does it highlight? The necessity to calculate both magnitude- and complexity-based measures for the thorough evaluation of force/torque fluctuations. Also the need for further research on neuromuscular complexity, particularly how it relates to the performance of functional activities (e.g. manual dexterity, balance, locomotion).

ABSTRACT

Physiological time series produce inherently complex fluctuations. In the last 30 years, methods have been developed to characterise these fluctuations, and have revealed that they contain information about the function of the system producing them. Two broad classes of metrics are used: (1) those which quantify the regularity of the signal (e.g. entropy metrics); and (2) those which quantify the fractal properties of the signal (e.g. detrended fluctuation analysis). Using these techniques, it has been demonstrated that ageing results in a loss of complexity in the time series of a multitude of signals, including heart rate, respiration, gait and, crucially, muscle force or torque output. This suggests that as the body ages, physiological systems become less adaptable (i.e. the systems' ability to respond rapidly to a changing external environment is diminished). More recently, it has been shown that neuromuscular fatigue causes a substantial loss of muscle torque complexity, a process that can be observed in a few minutes, rather than the decades it requires for the same system to degrade with ageing. The loss of torque complexity with neuromuscular fatigue appears to occur exclusively above the critical torque (at least for tasks lasting up to 30 min). The loss of torque complexity can be exacerbated with previous exercise of the same limb, and reduced by the administration of caffeine, suggesting both peripheral and central mechanisms contribute to this loss. The mechanisms underpinning the loss of complexity are not known but may be related to altered motor unit behaviour as the muscle fatigues.

Recovery from Fatigue after Cycling Time Trials in Elite Endurance Athletes

INTRODUCTION

We determined the recovery from neuromuscular fatigue in six professional (PRO) and seven moderately trained (MOD) cyclists after repeated cycling time trials of various intensities/durations.

METHOD

Participants performed two 1-min (1minTT) or two 10-min (10minTT) self-paced cycling time trials with 5 min of recovery in between. Central and peripheral fatigue were quantified via preexercise to postexercise (15-s through 15-min recovery) changes in voluntary activation (VA) and potentiated twitch force. VA was measured using the interpolated twitch technique, and potentiated twitch force was evoked by single (QTsingle) and paired (10-Hz (QT10) and 100-Hz (QT100)) electrical stimulations of the femoral nerve.

RESULTS

Mean power output was 32%-72% higher during all the time trials and decreased less (-10% vs -13%) from the first to second time trial in PRO compared with MOD (P < 0.05). Conversely, exercise-induced reduction in QTsingle and QT10/QT100 was significantly lower in PRO after every time trial (P < 0.05). Recovery from fatigue from 15 s to 2 min for QTsingle and QT10/QT100 was slower in PRO after every time trial (P < 0.05). In both groups, the reduction in QTsingle was lower after the 10minTTs compared with 1minTTs (P < 0.05). Conversely, VA decreased more after the 10minTTs compared with 1minTTs (P < 0.05).

CONCLUSION

Our findings showed that excitation-contraction coupling was preserved after exercise in PRO compared with MOD. This likely contributed to the improved performance during repeated cycling time trials of various intensity/duration in PRO, despite a slower rate of recovery in its early phase. Finally, the time course of recovery from neuromuscular fatigue in PRO was dependent on the effects of prolonged low-frequency force depression.

Estimation of maximal muscle electromyographic activity from the relationship between muscle activity and voluntary activation

Maximal muscle activity recorded with surface electromyography (EMG) is an important neurophysiological measure. It is frequently used to normalize EMG activity recorded during passive or active movement. However, the true maximal muscle activity cannot be determined in people with impaired capacity to voluntarily activate their muscles. Here, we determined whether maximal muscle activity can be estimated from muscle activity produced during submaximal voluntary activation. Twenty-five able-bodied adults (18 males, mean age 29 yr, range 19-64 yr) participated in the study. Participants were seated with the knee flexed 90° and the ankle in 5° of dorsiflexion from neutral. Participants performed isometric voluntary ankle plantarflexion contractions at target torques, in random order: 1, 5, 10, 15, 25, 50, 75, 90, 95, and 100% of maximal voluntary torque. Ankle torque, muscle activity in soleus, medial and lateral gastrocnemius muscles, and voluntary muscle activation determined using twitch interpolation were recorded. There was a strong log_e-linear relationship between measures of muscle activation and muscle activity in all three muscles tested. Linear mixed models were fitted to muscle activation and log_e-transformed EMG data. Each 1% increase in muscle activation increased muscle activity by a mean of 0.027 ln(mV) [95% confidence interval (CI) 0.025 to 0.029 ln(mV)] in soleus, 0.025 ln(mV) [0.022 to 0.028 ln(mV)] in medial gastrocnemius, and 0.028 ln(mV) [0.026 to 0.030 ln(mV)] in lateral gastrocnemius. The relationship between voluntary muscle activation and muscle activity can be described with simple mathematical functions. In future, it should be possible to normalize recorded muscle activity using these types of functions.NEW & NOTEWORTHY Muscle activity is often normalized to maximal muscle activity; however, it is difficult to obtain accurate measures of maximal muscle activity in people with impaired voluntary neural drive. We determined the relationship between voluntary muscle activation and plantarflexor muscle activity across a broad range of muscle activation values in able-bodied people. The relationship between voluntary muscle activation and muscle activity can be described with simple mathematical functions capable of estimating maximal muscle activity.

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.

Compound maximal motor unit response is modulated by contraction intensity, but not contraction type in tibialis anterior

Determining a single compound maximal motor response (MMAX ) or an average superimposed MMAX response (MSUP ) are commonly used reference values in experiments eliciting raw electromyographic, motor evoked potentials, H-reflexes, and V-waves. However, existing literature is limited in detailing the most appropriate method to normalize these electrophysiological measures. Due to the accessibility of assessment from a cortical and spinal perspective, the tibialis anterior is increasingly used in literature and hence investigated in this study. The aims of the present study were to examine the differences and level of agreement in MMAX /MSUP under different muscle actions and contraction intensities. Following a familiarization session, 22 males visited the laboratory on a single occasion. MMAX was recorded under 10% isometric and 25% and 100% shortening and lengthening maximal voluntary contractions (MVC) at an angular velocity of 15° sec-1 . MSUP was also recorded during 100% shortening and lengthening with an average of five responses recorded. There were no differences in MMAX or MSUP between contraction types. All variables showed large, positive correlations (P < 0.001, r2  ≥ 0.64). MMAX amplitude was larger (P < 0.001) at 100% shortening and lengthening intensity compared to MMAX amplitude at 10% isometric and 25% lengthening MVC. Bland-Altman plots revealed a bias toward higher MMAX at the higher contraction intensities. Despite MSUP being significantly smaller than MMAX (P < 0.001) at 100% MVC, MSUP showed a large positive correlation (P < 0.001, r2  ≥ 0.64) with all variables. It is our recommendation that MMAX should be recorded at specific contraction intensity but not necessarily a specific contraction type.

Multichannel Surface EMG Decomposition Based on Measurement Correlation and LMMSE

A method based on measurement correlation (MC) and linear minimum mean square error (LMMSE) for multichannel surface electromyography (sEMG) signal decomposition was developed in this study. This MC-LMMSE method gradually and iteratively increases the correlation between an optimized vector and a reconstructed matrix that is correlated with the measurement matrix. The performance of the proposed MC-LMMSE method was evaluated with both simulated and experimental sEMG signals. Simulation results show that the MC-LMMSE method can successfully reconstruct up to 53 innervation pulse trains with a true positive rate greater than 95%. The performance of the MC-LMMSE method was also evaluated using experimental sEMG signals collected with a 64-channel electrode array from the first dorsal interosseous muscles of three subjects at different contraction levels. A maximum of 16 motor units were successfully extracted from these multichannel experimental sEMG signals. The performance of the MC-LMMSE method was further evaluated with multichannel experimental sEMG data by using the "two sources" method. The large population of common MUs extracted from the two independent subgroups of sEMG signals demonstrates the reliability of the MC-LMMSE method in multichannel sEMG decomposition.

Neurophysiological Mechanisms Underpinning Stretch-Induced Force Loss

It is well known that prolonged passive muscle stretch reduces maximal muscle force production. There is a growing body of evidence suggesting that adaptations occurring within the nervous system play a major role in this stretch-induced force reduction. This article reviews the existing literature, and some new evidence, regarding acute neurophysiological changes in response to passive muscle stretching. We discuss the possible contribution of supra-spinal and spinal structures to the force reduction after passive muscle stretch. In summary, based on the recent evidence reviewed we propose a new hypothesis that a disfacilitation occurring at the motoneuronal level after passive muscle stretch is a major factor affecting the neural efferent drive to the muscle and, subsequently, its ability to produce maximal force.

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.

Motor Unit Action Potential Clustering-Theoretical Consideration for Muscle Activation during a Motor Task

During dynamic or sustained isometric contractions, bursts of muscle activity appear in the electromyography (EMG) signal. Theoretically, these bursts of activity likely occur because motor units are constrained to fire temporally close to one another and thus the impulses are "clustered" with short delays to elicit bursts of muscle activity. The purpose of this study was to investigate whether a sequence comprised of "clustered" motor unit action potentials (MUAP) can explain spectral and amplitude changes of the EMG during a simulated motor task. This question would be difficult to answer experimentally and thus, required a model to study this type of muscle activation pattern. To this end, we modeled two EMG signals, whereby a single MUAP was either convolved with a randomly distributed impulse train (EMG-rand) or a "clustered" sequence of impulses (EMG-clust). The clustering occurred in windows lasting 5-100 ms. A final mixed signal of EMG-clust and EMG-rand, with ratios (1:1-1:10), was also modeled. A ratio of 1:1 would indicate that 50% of MUAP were randomly distributed, while 50% of "clustered" MUAP occurred in a given time window (5-100 ms). The results of the model showed that clustering MUAP caused a downshift in the mean power frequency (i.e., ~30 Hz) with the largest shift occurring with a cluster window of 10 ms. The mean frequency shift was largest when the ratio of EMG-clust to EMG-rand was high. Further, the clustering of MUAP also caused a substantial increase in the amplitude of the EMG signal. This model potentially explains an activation pattern that changes the EMG spectra during a motor task and thus, a potential activation pattern of muscles observed experimentally. Changes in EMG measurements during fatiguing conditions are typically attributed to slowing of conduction velocity but could, per this model, also result from changes of the clustering of MUAP. From a clinical standpoint, this type of muscle activation pattern might help describe the pathological movement issues in people with Parkinson's disease or essential tremor. Based on our model, researchers moving forward should consider how MUAP clustering influences EMG spectral and amplitude measurements and how these changes influence movements.

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.

Intensity-Dependent Contribution of Neuromuscular Fatigue after Constant-Load Cycling

PURPOSE

We tested the hypothesis that central and peripheral fatigue after constant-load cycling exercise would vary with exercise intensity and duration.

METHODS

Twelve well-trained male cyclists (V˙O2max, 4.49 ± 0.35 L·min) completed three constant-load cycling trials to the limit of tolerance in a randomized crossover design. Exercise intensities were set according to the respiratory responses to a preliminary ramp test to elicit cardiorespiratory and metabolic responses consistent with exercise in the severe and heavy exercise domains: 1) at power at V˙O2max (S+, 379 ± 31 W), 2) at 60% of the difference between gas exchange threshold and V˙O2max (S-, 305 ± 23 W), and 3) at the respiratory compensation point (RCP, 254 ± 26 W). Pre- and postexercise twitch responses from the quadriceps to the electrical stimulation of the femoral nerve and magnetic stimulation of the motor cortex were recorded to assess neuromuscular and corticospinal function, respectively.

RESULTS

Exercise time was 3.14 ± 0.59, 11.11 ± 1.86, and 42.14 ± 9.09 min for S+, S-, and RCP, respectively. All trials resulted in similar reductions in maximum voluntary force (P = 0.61). However, the degree of peripheral fatigue varied in an intensity-dependent manner, with greater reductions in potentiated twitch force after S+ (-33% ± 9%) compared with both S- (-16% ± 9%, P < 0.001) and RCP trials (-11% ± 9%, P < 0.001) and greater after S- compared with RCP (P < 0.05). For central fatigue, this trend was reversed, with smaller reductions in voluntary activation after S+ compared with RCP (-2.7% ± 2.2% vs -9.0% ± 4.7%, P < 0.01).

CONCLUSION

These data suggest the magnitude of peripheral and central fatigue after locomotor cycling exercise is exacerbated with exercise intensity and duration, respectively.

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.

CHARACTERIZATION OF MOTOR UNIT AT DIFFERENT STRENGTHS WITH MULTI-CHANNEL SURFACE ELECTROMYOGRAPHY

In this study, specific changes in electromyographic characteristics of individual motor units (MUs) associated with different muscle contraction forces are investigated using multi-channel surface electromyography (SEMG). The gradient convolution kernel compensation (GCKC) algorithm is employed to separate individual MUs from their surface interferential electromyography (EMG) signals and provide the discharge instants, which is later used in the spike-triggered averaging (STA) techniques to obtain the complete waveform. The method was tested on experimental SEMG signals acquired during constant force contractions of biceps brachii muscles in five subjects. Electromyographic characteristics including the recruitment number, waveform amplitude, discharge pattern and innervation zone (IZ) are studied. Results show that changes in the action potential of single MU with different contraction force levels are consistent with those for all MUs, and that the amplitude of MU action potentials (MUAPs) provides a useful estimate of the muscle contraction forces.

A new approach for multi-channel surface EMG signal simulation

Simulation models are necessary for testing the performance of newly developed approaches before they can be applied to interpreting experimental data, especially when biomedical signals such as surface electromyogram (SEMG) signals are involved. A new and easily implementable surface EMG simulation model was developed in this study to simulate multi-channel SEMG signals. A single fiber action potential (SFAP) is represented by the sum of three Gaussian functions. SFAP waveforms can be modified by adjusting the amplitude and bandwidth of the Gaussian functions. SEMG signals were successfully simulated at different detected locations. Effects of the fiber depth, electrode position and conduction velocity of SFAP on motor unit action potential (MUAP) were illustrated. Results demonstrate that the easily implementable SEMG simulation approach developed in this study can be used to effectively simulate SEMG signals.

Motor units in the human medial gastrocnemius muscle are not spatially localized or functionally grouped

KEY POINTS

Human medial gastrocnemius (MG) motor units (MUs) are thought to occupy small muscle territories or regions, with low-threshold units preferentially located distally. We used intramuscular recordings to measure the territory of muscle fibres from MG MUs and determine whether these MUs are grouped by recruitment threshold or joint action (ankle plantar flexion and knee flexion). The territory of MUs from the MG muscle varied from somewhat localized to highly distributed, with approximately half the MUs spanning at least half the length and width of the muscle. There was also no evidence of regional muscle activity based on MU recruitment thresholds or joint action. The CNS does not have the means to selectively activate regions of the MG muscle based on task requirements.

ABSTRACT

Human medial gastrocnemius (MG) motor units (MUs) are thought to occupy small muscle territories, with low-threshold units preferentially located distally. In this study, subjects (n = 8) performed ramped and sustained isometric contractions (ankle plantar flexion and knee flexion; range: ∼1-40% maximal voluntary contraction) and we measured MU territory size with spike-triggered averages from fine-wire electrodes inserted along the length (seven electrodes) or across the width (five electrodes) of the MG muscle. Of 69 MUs identified along the length of the muscle, 32 spanned at least half the muscle length (≥ 6.9 cm), 11 of which spanned all recording sites (13.6-17.9 cm). Distal fibres had smaller pennation angles (P < 0.05), which were accompanied by larger territories in MUs with fibres located distally (P < 0.05). There was no distal-to-proximal pattern of muscle activation in ramp contraction (P = 0.93). Of 36 MUs identified across the width of the muscle, 24 spanned at least half the muscle width (≥ 4.0 cm), 13 of which spanned all recording sites (8.0-10.8 cm). MUs were not localized (length or width) based on recruitment threshold or contraction type, nor was there a relationship between MU territory size and recruitment threshold (Spearman's rho = -0.20 and 0.13, P > 0.18). MUs in the human MG have larger territories than previously reported and are not localized based on recruitment threshold or joint action. This indicates that the CNS does not have the means to selectively activate regions of the MG muscle based on task requirements.

The optimal neural strategy for a stable motor task requires a compromise between level of muscle cocontraction and synaptic gain of afferent feedback

Increasing joint stiffness by cocontraction of antagonist muscles and compensatory reflexes are neural strategies to minimize the impact of unexpected perturbations on movement. Combining these strategies, however, may compromise steadiness, as elements of the afferent input to motor pools innervating antagonist muscles are inherently negatively correlated. Consequently, a high afferent gain and active contractions of both muscles may imply negatively correlated neural drives to the muscles and thus an unstable limb position. This hypothesis was systematically explored with a novel computational model of the peripheral nervous system and the mechanics of one limb. Two populations of motor neurons received synaptic input from descending drive, spinal interneurons, and afferent feedback. Muscle force, simulated based on motor unit activity, determined limb movement that gave rise to afferent feedback from muscle spindles and Golgi tendon organs. The results indicated that optimal steadiness was achieved with low synaptic gain of the afferent feedback. High afferent gains during cocontraction implied increased levels of common drive in the motor neuron outputs, which were negatively correlated across the two populations, constraining instability of the limb. Increasing the force acting on the joint and the afferent gain both effectively minimized the impact of an external perturbation, and suboptimal adjustment of the afferent gain could be compensated by muscle cocontraction. These observations show that selection of the strategy for a given contraction implies a compromise between steadiness and effectiveness of compensations to perturbations. This indicates that a task-dependent selection of neural strategy for steadiness is necessary when acting in different environments.

Motor unit number in a small facial muscle, dilator naris

A loss of functioning motor units underlies many neuromuscular disorders. The facial nerve innervates the muscles of facial expression, including nasal muscles, which also play an important role in the regulation of airflow resistance. It is difficult to accurately assess motor unit number in the facial muscles, because the muscles are difficult to activate in isolation. Here, we apply the manual McComas method to estimate the number of motor units in a nasal dilator muscle. EMG of the dilator naris was recorded during graded stimulation of the zygomatic branch of the facial nerve in 26 subjects (12 males and 14 females), aged 20-41 years. Each subject was studied twice, on separate days, to estimate method reproducibility. As a check on our use of the McComas method, we also estimated motor unit number in the first dorsal interosseus muscle (FDI) of six subjects, as the muscle is also small and has been studied with the McComas method. Reproducibility was evaluated with a rigorous statistical approach, the Bland-Altman procedure. We estimate that dilator naris is composed of 75 ± 15.6 (SD) motor units, compared to 144 ± 35.5 in FDI. The coefficient of variation for test-retest reproducibility of dilator naris motor unit estimates was 29.6 %, similar to separate-day reproducibility reported for other muscles. Recording and stimulation were done with surface electrodes, and the recordings were of high quality and reproducible. This simple technique could be applied clinically to track motor neuron loss and to monitor facial nerve integrity.

Medium-intensity, high-volume "hypertrophic" resistance training did not induce improvements in rapid force production in healthy older men

The aim of the study was to determine whether it is possible to improve both maximum and rapid force production using resistance training that is typically used to induce muscle hypertrophy in previously untrained older men. Subjects (60-72 years) performed 20 weeks of "hypertrophic" resistance training twice weekly (n = 27) or control (n = 11). Maximum dynamic and isometric leg press, as well as isometric force over 0-100 ms, and maximum concentric power tests were performed pre- and post-intervention. Muscle activity was assessed during these tests by surface electromyogram of the vastus lateralis and medialis muscles. Muscle hypertrophy was assessed by panoramic ultrasound of the vastus lateralis. The intervention group increased their maximum isometric (from 2268 ± 544 to 2538 ± 701 N) and dynamic force production (from 137 ± 24 to 165 ± 29 kg), and these changes were significantly different to control (isometric 12 ± 16 vs. 1 ± 9 %; dynamic 21 ± 12 vs. 2 ± 4 %). No within- or between-group differences were observed in rapid isometric force or concentric power. Relative increases in vastus lateralis cross-sectional area trended to be statistically greater in the intervention group (10 ± 8 vs. 3 ± 6 %, P = 0.061). It is recommendable that resistance training programs for older individuals integrate protocols emphasizing maximum force/muscle hypertrophy and rapid force production in order to induce comprehensive health-related and functionally important improvements in this population.

The extraction of neural strategies from the surface EMG: an update

A surface EMG signal represents the linear transformation of motor neuron discharge times by the compound action potentials of the innervated muscle fibers and is often used as a source of information about neural activation of muscle. However, retrieving the embedded neural code from a surface EMG signal is extremely challenging. Most studies use indirect approaches in which selected features of the signal are interpreted as indicating certain characteristics of the neural code. These indirect associations are constrained by limitations that have been detailed previously (Farina D, Merletti R, Enoka RM. J Appl Physiol 96: 1486-1495, 2004) and are generally difficult to overcome. In an update on these issues, the current review extends the discussion to EMG-based coherence methods for assessing neural connectivity. We focus first on EMG amplitude cancellation, which intrinsically limits the association between EMG amplitude and the intensity of the neural activation and then discuss the limitations of coherence methods (EEG-EMG, EMG-EMG) as a way to assess the strength of the transmission of synaptic inputs into trains of motor unit action potentials. The debated influence of rectification on EMG spectral analysis and coherence measures is also discussed. Alternatively, there have been a number of attempts to identify the neural information directly by decomposing surface EMG signals into the discharge times of motor unit action potentials. The application of this approach is extremely powerful, but validation remains a central issue.

The role of muscle synergies in myoelectric control: trends and challenges for simultaneous multifunction control

Myoelectric control is filled with potential to significantly change human-robot interaction due to the ability to non-invasively measure human motion intent. However, current control schemes have struggled to achieve the robust performance that is necessary for use in commercial applications. As demands in myoelectric control trend toward simultaneous multifunctional control, multi-muscle coordinations, or synergies, play larger roles in the success of the control scheme. Detecting and refining patterns in muscle activations robust to the high variance and transient changes associated with surface electromyography is essential for efficient, user-friendly control. This article reviews the role of muscle synergies in myoelectric control schemes by dissecting each component of the scheme with respect to associated challenges for achieving robust simultaneous control of myoelectric interfaces. Electromyography recording details, signal feature extraction, pattern recognition and motor learning based control schemes are considered, and future directions are proposed as steps toward fulfilling the potential of myoelectric control in clinically and commercially viable applications.

Comparison of the power spectral changes of the voluntary surface electromyogram and M wave during intermittent maximal voluntary contractions

INTRODUCTION

To compare the power spectral changes of the voluntary surface electromyogram (sEMG) and of the compound action potential (M wave) in the vastus medialis and vastus lateralis muscles during fatiguing contractions.

METHODS

Interference sEMG and force were recorded during 48 intermittent 3-s isometric maximal voluntary contractions (MVC) from 13 young, healthy subjects. M waves and twitches were evoked using supramaximal femoral nerve stimulation between the successive MVCs. Mean frequency (F mean), and median frequency were calculated from the sEMG and M waves. Muscle fiber conduction velocity (MFCV) was computed by cross-correlation.

RESULTS

The power spectral shift to lower frequencies was significantly greater for the voluntary sEMG than for the M waves (P < 0.05). Over the fatiguing protocol, the overall average decrease in MFCV (~25%) was comparable to that of sEMG F mean (~22%), but significantly greater than that of M-wave F mean (~9%) (P < 0.001). The mean decline in MFCV was highly correlated with the mean decreases in both sEMG and M-wave F mean.

CONCLUSIONS

The present findings indicated that, as fatigue progressed, central mechanisms could enhance the relative weight of the low-frequency components of the voluntary sEMG power spectrum, and/or the end-of-fiber (non-propagating) components could reduce the sensitivity of the M-wave spectrum to changes in conduction velocity.

Motor unit activity after eccentric exercise and muscle damage in humans

It is well known that unaccustomed eccentric exercise leads to muscle damage and soreness, which can produce long-lasting effects on muscle function. How this muscle damage influences muscle activation is poorly understood. The purpose of this brief review is to highlight the effect of eccentric exercise on the activation of muscle by the nervous system, by examining the change in motor unit activity obtained from surface electromyography (EMG) and intramuscular recordings. Previous research shows that eccentric exercise produces unusual changes in the EMG–force relation that influences motor performance during isometric, shortening and lengthening muscle contractions and during fatiguing tasks. When examining the effect of eccentric exercise at the single motor unit level, there are substantial changes in recruitment thresholds, discharge rates, motor unit conduction velocities and synchronization, which can last for up to 1 week after eccentric exercise. Examining the time course of these changes suggests that the increased submaximal EMG after eccentric exercise most likely occurs through a decrease in motor unit conduction velocity and an increase in motor unit activity related to antagonist muscle coactivation and low-frequency fatigue. Furthermore, there is a commonly held view that eccentric exercise produces preferential damage to high-threshold motor units, but the evidence for this in humans is limited. Further research is needed to establish whether there is preferential damage to high-threshold motor units after eccentric exercise in humans, preferably by linking changes in motor unit activity with estimates of motor unit size using selective intramuscular recording techniques.

Cortical and spinal mechanisms of task failure of sustained submaximal fatiguing contractions

In this and the subsequent companion paper, results are presented that collectively seek to delineate the contribution that supraspinal circuits have in determining the time to task failure (TTF) of sustained submaximal contractions. The purpose of this study was to compare adjustments in supraspinal and spinal excitability taken concurrently throughout the performance of two different fatigue tasks with identical mechanical demands but different TTF (i.e., force-matching and position-matching tasks). On separate visits, ten healthy volunteers performed the force-matching or position-matching task at 15% of maximum strength with the elbow flexors to task failure. Single-pulse transcranial magnetic stimulation (TMS), paired-pulse TMS, paired cortico-cervicomedullary stimulation, and brachial plexus electrical stimulation were delivered in a 6-stimuli sequence at baseline and every 2-3 minutes throughout fatigue-task performance. Contrary to expectations, the force-matching task TTF was 42% shorter (17.5 ± 7.9 min) than the position-matching task (26.9 ± 15.11 min; p<0.01); however, both tasks caused the same amount of muscle fatigue (p = 0.59). There were no task-specific differences for the total amount or rate of change in the neurophysiologic outcome variables over time (p>0.05). Therefore, failure occurred after a similar mean decline in motorneuron excitability developed (p<0.02, ES = 0.35-0.52) coupled with a similar mean increase in measures of corticospinal excitability (p<0.03, ES = 0.30-0.41). Additionally, the amount of intracortical inhibition decreased (p<0.03, ES = 0.32) and the amount of intracortical facilitation (p>0.10) and an index of upstream excitation of the motor cortex remained constant (p>0.40). Together, these results suggest that as fatigue develops prior to task failure, the increase in corticospinal excitability observed in relationship to the decrease in spinal excitability results from a combination of decreasing intracortical inhibition with constant levels of intracortical facilitation and upstream excitability that together eventually fail to provide the input to the motor cortex necessary for descending drive to overcome the spinal cord resistance, thereby contributing to task failure.

Anodal transcranial direct current stimulation alters elbow flexor muscle recruitment strategies

BACKGROUND

Transcranial direct current stimulation (tDCS) is known to reliably alter motor cortical excitability in a polarity dependent fashion such that anodal stimulation increases cortical excitability and cathodal stimulation inhibits cortical excitability. However, the effect of tDCS on agonist and antagonist volitional muscle activation is currently not known.

OBJECTIVE

This study investigated the effect of motor cortical anodal tDCS on EMG/force relationships of biceps brachii (agonist) and triceps brachii (antagonist) using surface electromyography (EMG).

METHODS

Eighteen neurologically intact adults (9 tDCS and 9 controls) participated in this study. EMG/force relationships were established by having subjects perform submaximal isometric contractions at several force levels (12.5%, 25%, 37.5%, and 50% of maximum).

RESULTS

Results showed that anodal tDCS significantly affected the EMG/force relationship of the biceps brachii muscle. Specifically, anodal tDCS increased the magnitude of biceps brachii activation at 37.5% and 50% of maximum. Anodal tDCS also resulted in an increase in the peak force and EMG values during maximal contractions as compared to the control condition. EMG analyses of other elbow muscles indicated that the increase in biceps brachii activation after anodal tDCS was not related to alterations in synergistic or antagonistic muscle activity.

CONCLUSIONS

Our results indicate that anodal tDCS significantly affects the voluntary EMG/force relationship of the agonist muscles without altering the coactivation of the antagonistic muscles. The most likely explanation for the observed greater EMG per unit force after anodal tDCS appears to be related to alterations in motor unit recruitment strategies.

The impact of rectification on the electrically evoked long-latency reflex of the biceps brachii muscle

Long latency reflexes (LLR) were elicited electrically and obtained by full wave rectified and non-rectified data recordings in 10 healthy subjects. After single or train stimuli (sensory radial nerve; interstimulus interval 3ms) amplitude and peak latency values were measured over the bent biceps brachii (BB) muscle, either without or with 1.5kg weight load. After rectification, mean LLR amplitude values made up 30% of the non-rectified data, independent from the stimulus type and weight load. In the non-rectified data, a significant gain in amplitude resulted from train stimuli compared with single stimuli, and from weight load compared to no weight load. No such significant difference was detected when rectified data were analysed. Furthermore, average amplitude values of rectified and non-rectified curves were studied using 11 sine waves and damped sine waves with equal phase intervals that were varied from 0° up to 34.4°. Phase shifts ranging from 10° to 25° resulted in excess amplitude decline of rectified data compared with non-rectified data. The long and polysynaptic course that LLR information takes leads to considerable overlap of responses to subsequent stimuli. This overlap of motor unit potentials forming the LLR obviously results in excess amplitude cancellation after rectification as shown for sine and damped sine waves. Rectification leads to an increase in the frequency content of the data that renders it prone to phase cancellation. In the present study, this cancellation was harmful as it prevented detection of important factors of influence such as stimulus strength and motor unit recruitment level.