Analysis of motor unit spike trains estimated from high-density surface electromyography is highly reliable across operators

There is a growing interest in decomposing high-density surface electromyography (HDsEMG) into motor unit spike trains to improve knowledge on the neural control of muscle contraction. However, the reliability of decomposition approaches is sometimes questioned, especially because they require manual editing of the outputs. We aimed to assess the inter-operator reliability of the identification of motor unit spike trains. Eight operators with varying experience in HDsEMG decomposition were provided with the same data extracted using the convolutive kernel compensation method. They were asked to manually edit them following established procedures. Data included signals from three lower leg muscles and different submaximal intensities. After manual analysis, 126 ± 5 motor units were retained (range across operators: 119–134). A total of 3380 rate of agreement values were calculated (28 pairwise comparisons × 11 contractions/muscles × 4–28 motor units). The median rate of agreement value was 99.6%. Inter-operator reliability was excellent for both mean discharge rate and time at recruitment (intraclass correlation coefficient > 0.99). These results show that when provided with the same decomposed data and the same basic instructions, operators converge toward almost identical results. Our data have been made available so that they can be used for training new operators.     

Inter-operator agreement in decomposition of motor unit firings from high-density surface EMG.

High-density surface EMG can be used to obtain a spatially selective representation of several motor unit action potentials. Recently, a decomposition of the signal into the underlying motor neuron firing patterns has been described. The reliability of the algorithm has not yet been tested. Eleven healthy subjects participated. High-density surface EMG was recorded from the vastus lateralis muscle during an isometric knee extension. Two independent operators analyzed the signals. After operator-supervised cluster analysis of spikes, motor unit action potential templates were constructed and an automatic template matching was performed. The decomposition was adjusted by hand. Agreement between operators was calculated for the number of coincident firings. Bland-Altman plots of peak-to-peak amplitude were constructed and limits of agreement were calculated. For completely decomposed motor unit action potential trains the between-operator agreement of firing events was very high. The peak-to-peak amplitude of monopolar motor unit action potentials was 115microV (SD 74microV). The agreement was within 3microV and independent of amplitude. With partial decomposition agreement within 26microV was achieved. For bipolarly derived motor unit action potentials the peak-to-peak amplitude was 54microV (SD 49microV), the agreement was within 3microV. Only for recordings obtained from a force level below 5% of the maximum voluntary contraction full decomposition was possible. It was concluded that when full decomposition is achieved, two independent operators are likely to arrive at nearly identical firing patterns.     

A method for editing motor unit potential trains obtained by decomposition of surface electromyographic signals

Rather than discarding motor unit potential trains (MUPTs) because they do not meet 100% validity criteria, we describe and evaluate a novel editing routine that preserves valid discharge times, based on decreasing shape variability (variance ratio, VR) within a MUPT. The error filtered estimation (EFE) algorithm is then applied to the remaining ‘high confidence’ discharge times to estimate inter-discharge interval (IDI) statistics. Decomposed surface EMG data from the flexor carpi radialis recorded from 20 participants during 60% MVC wrist flexion was used. There were two levels of denoising criteria (relaxed and strict) criteria for removing MUPs to decrease the VR and increase the signal-to-noise ratio (SNR) of a MUPT. In total, VR decreased 24.88% and SNR increased 6.0% (p’s < 0.05). The MUP template peak-to-peak (P-P) amplitude and P-P duration were dependent on the level of denoising (p’s < 0.05). The standard error of the estimate (SEE) of the mean IDI before and after editing using the relaxed criteria (3.2% versus 3.69%), was very similar (p > 0.05). The same was true for the SEE between denoising criteria, which increased only to 5.14% for the strict criteria (p > 0.05). Editing the MUPTs resulted in a significant decrease in MUP shape variability and in the measures extracted from the MUP templates, with trivial differences between the SEE of the mean IDI between the edited and unedited MUPTs.     

Measuring the accuracies of motor unit firing times and action potential waveforms derived from surface electromyographic decomposition

This study included spike trigger averaging (STA) procedures to examine the acceptability of the Precision Decomposition (PD) III derived motor unit action potential (MUAP) trains that met the >90% accuracy criteria from the reconstruct-and-test. MUs met the >90% accuracy criteria from the reconstruct-and-test with STA procedures then applied. Y-intercepts and slopes were calculated for the firing rate- and MUAP amplitude-recruitment threshold relationships. Gaussian noise (1% of the SD of the mean interspike interval) was added to the firing times with the changes in MUAPs quantified. A total of 455 MUs were decomposed with 155 MUs removed as a result of the reconstruct-and-test. Five additional MUs were excluded via the STA criteria. The MUAP waveforms deteriorated with the inclusion of Gaussian noise. There were differences in the derived action potentials amplitudes of higher-threshold MUs between the PD III algorithm and the STA procedure. There was excellent agreement among the slopes and y-intercepts between the relationships that included or excluded MUs that did not meet the STA criteria. There was good agreement between the MUAP amplitude-recruitment threshold relationships derived from the PD III and STA procedure. The addition of the STA procedures did not alter the MU-derived relationships.     

Influence of motor units recruitment and firing rate on the soundmyogram and EMG characteristics in cat gastrocnemius

The separate contributions of the recruitment level and of the firing rate of the motor units on the soundmyogram and electromyogram time domain parameters were investigated during stimulation of the motor nerve of the cat gastrocnemius muscle. Upon orderly increase in the number of active motor units at a fixed firing rate, both the peak to peak amplitude (P-P_max) and the root mean square (RMS) of the sound myogram increased. At full recruitment the increase in firing rate from 2.5 to 50 Hz induced an exponential decline in the P-P_max. The RMS, however, followed this trend only from 15 to 50 Hz while showing an increase from 2.5 to 10 Hz. During simultaneous changes of recruitment and firing rate, the effect of increasing the number of motor units on the P-P_max and RMS is dampened by the increasing firing rate. The peak to peak amplitude of the EMG compound action potential increased with the number of active motor units. Moreover, its amplitude was not influenced by the firing rate. The EMG RMS, however, increases as a function of the firing rate. The results indicate that both the number and the firing rate of the active motor units contribute to the determination of the soundmyogram characteristics. Moreover, the peculiar changes of the soundmyogram time domain properties, compared to the ones of the EMG, allow one to differentiate the influence of the motor units number and firing rate on the electrical and mechanical performance of the muscle when stimulated.     

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

The purpose of the study was to evaluate the influence of selected physiological parameters on amplitude cancellation in the simulated surface electromyogram (EMG) and the consequences for spike-triggered averages of motor unit potentials derived from the interference and rectified EMG signals. The surface EMG was simulated from prescribed recruitment and rate coding characteristics of a motor unit population. The potentials of the motor units were detected on the skin over a hand muscle with a bipolar electrode configuration. Averages derived from the EMG signal were generated using the discharge times for each of the 24 motor units with lowest recruitment thresholds from a population of 120 across three conditions: 1) excitation level; 2) motor unit conduction velocity; and 3) motor unit synchronization. The area of the surface-detected potential was compared with potentials averaged from the interference, rectified, and no-cancellation EMGs. The no-cancellation EMG comprised motor unit potentials that were rectified before they were summed, thereby preventing cancellation between the opposite phases of the potentials. The percent decrease in area of potentials extracted from the rectified EMG was linearly related to the amount of amplitude cancellation in the interference EMG signal, with the amount of cancellation influenced by variation in excitation level and motor unit conduction velocity. Motor unit synchronization increased potentials derived from both the rectified and interference EMG signals, although cancellation limited the increase in area for both potentials. These findings document the influence of amplitude cancellation on motor unit potentials averaged from the surface EMG and the consequences for using the procedure to characterize motor unit properties.     

Evolution of surface electromyography: From muscle electrophysiology towards neural recording and interfacing

Surface electromyography (EMG) comprises a recording of electrical activity from the body surface generated by muscle fibres during muscle contractions. Its characteristics depend on the fibre membrane potentials and the neural activation signal sent from the motor neurons to the muscles. EMG has been classically used as the primary investigation tool in kinesiology studies in a variety of applications. More recently, surface EMG techniques have evolved from single-channel methods to high-density systems with hundreds of electrodes. High-density EMG recordings can be deconvolved to estimate the discharge times of spinal motor neurons innervating the recorded muscles, with algorithms that have been developed and validated in the last two decades. Within limits and with some variability across muscles, these techniques provide a non-invasive method to study relatively large populations of motor neurons in humans. Surface EMG is thus evolving from a peripheral measure of muscle electrical activity towards a neural recording and neural interfacing signal. These advances in technology have had a major impact on our fundamental understanding of the neural control of movement and have exposed new perspectives in neurotechnologies. Here we provide an overview and perspective of modern EMG technology, as derived from past achievements, and its impact in neurophysiology and neural engineering.     

Clinical applications of high-density surface EMG: A systematic review

High density-surface EMG (HD-sEMG) is a non-invasive technique to measure electrical muscle activity with multiple (more than two) closely spaced electrodes overlying a restricted area of the skin. Besides temporal activity HD-sEMG also allows spatial EMG activity to be recorded, thus expanding the possibilities to detect new muscle characteristics. Especially muscle fiber conduction velocity (MFCV) measurements and the evaluation of single motor unit (MU) characteristics come into view. This systematic review of the literature evaluates the clinical applications of HD-sEMG. Although beyond the scope of the present review, the search yielded a large number of “non-clinical” papers demonstrating that a considarable amount of work has been done and that significant technical progress has been made concerning the feasibility and optimization of HD-sEMG techniques. Twenty-nine clinical studies and four reviews of clinical applications of HD-sEMG were considered. The clinical studies concerned muscle fatigue, motor neuron diseases (MND), neuropathies, myopathies (mainly in patients with channelopathies), spontaneous muscle activity and MU firing rates. In principle, HD-sEMG allows pathological changes at the MU level to be detected, especially changes in neurogenic disorders and channelopathies. We additionally discuss several bioengineering aspects and future clinical applications of the technique and provide recommendations for further development and implementation of HD-sEMG as a clinical diagnostic tool.     

Influence of timing variability between motor unit potentials on M-wave characteristics

The transient enlargement of the compound muscle action potential (M wave) after a conditioning contraction is referred to as potentiation. It has been recently shown that the potentiation of the first and second phases of a monopolar M wave differed drastically; namely, the first phase remained largely unchanged, whereas the second phase underwent a marked enlargement and shortening. This dissimilar potentiation of the first and second phases has been suggested to be attributed to a transient increase in conduction velocity after the contraction. Here, we present a series of simulations to test if changes in the timing variability between motor unit potentials (MUPs) can be responsible for the unequal potentiation (and shortening) of the first and the second M-wave phases. We found that an increase in the mean motor unit conduction velocity resulted in a marked enlargement and narrowing of both the first and second M-wave phases. The enlargement of the first phase caused by a global increase in motor unit conduction velocities was apparent even for the electrode located over the innervation zone and became more pronounced with increasing distance to the innervation zone, whereas the potentiation of the second phase was largely independent of electrode position. Our simulations indicate that it is unlikely that an increase in motor unit conduction velocities (accompanied or not by changes in their distribution) could account for the experimental observation that only the second phase of a monopolar M wave, but not the first, is enlarged after a brief contraction. However, the combination of an increase in the motor unit conduction velocities and a spreading of the motor unit activation times could potentially explain the asymmetric potentiation of the M-wave phases.     

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.     

Spatio-temporal processing of surface EMG signals from the sternocleidomastoideus muscle to assess effects of radiotherapy on motor unit conduction velocity and firing rate—A pilot study

Radiation therapy causes both muscle and nerve tissue damage. However, the evolution and mechanisms of these damages are not fully understood. Information on the state of active muscle fibres and motoneurons can be obtained by measuring sEMG signals and calculating the conduction velocity (CV) and firing rate of individual motor units, respectively. The aim of this pilot study was to evaluate if the multi-channel surface EMG (sEMG) technique could be applied to the sternocleidomastoideus muscle (SCM) of radiotherapy patients, and to assess if the CV and firing rate are altered as a consequence of the radiation.

Surface EMG signals were recorded from the radiated and healthy SCM muscles of 10 subjects, while subjects performed isometric rotation of the head. CV and firing rate were calculated using two recently proposed methods based on spatio-temporal processing of the sEMG signals. The multi-channel sEMG technique was successfully applied to the SCM muscle and CV and firing rates were obtained. The measurements were fast and simple and comfortable for the patients. Sufficient data quality was obtained from both sides of seven and four subjects for the CV and firing rate analysis, respectively. No differences in CV or firing rate were found between the radiated and non-radiated sides (p = 0.13 and p = 0.20, respectively). Firing rate and CV were also obtained from a myokymic discharge pattern. It was found that the CV decreased significantly (p = 0.01) during the bursts.     

Automatic detection of motor unit innervation zones of the external anal sphincter by multichannel surface EMG

A method to detect automatically the location of innervation zones (IZs) from 16-channel surface EMG (sEMG) recordings from the external anal sphincter (EAS) muscle is presented in order to guide episiotomy during child delivery. The new algorithm (2DCorr) is applied to individual motor unit action potential (MUAP) templates and is based on bidimensional cross correlation between the interpolated image of each MUAP template and two images obtained by flipping upside-down (around a horizontal axis) and left–right (around a vertical axis) the original one. The method was tested on 640 simulated MUAP templates of the sphincter muscle and compared with previously developed algorithms (Radon Transform, RT; Template Match, TM). Experimental signals were detected from the EAS of 150 subjects using an intra-anal probe with 16 equally spaced circumferential electrodes. The results of the three algorithms were compared with the actual IZ location (simulated signal) and with IZ location provided by visual analysis (VA) (experimental signals). For simulated signals, the inter quartile error range (IQR) between the estimated and the actual locations of the IZ was 0.20, 0.23, 0.42, and 2.32 interelectrode distances (IED) for the VA, 2DCorr, RT and TM methods respectively.     

Testing of instantaneity hypothesis for blind source separation of extensor indicis and extensor digiti minimi surface electromyograms

Human muscle activity can be assessed with surface electromyography (SEMG). Depending on electrode location and size, the recording volume under the sensor is likely to measure electrical potentials emanating from muscles other than the muscle of interest. This crosstalk issue makes interpretation of SEMG data difficult. The purpose of this paper was to study a crosstalk reduction technique called blind source separation (BSS). Most straightforward separation techniques rely on linearity and instantaneity (LI) of signal mixtures on the sensors. Literature on BSS for SEMG often makes hypothesis of linearity and instantaneity of the mixing model. Using simulation of SEMG mixtures and real SEMG recordings on the human extensor indicis (EI) and extensor digiti minimi (EDM) muscles during a task consisting of selective successive activations of EI and EDM muscles, cross-correlation between the sensors was proven to be directly dependent on instantaneity of the sources. Instantaneity hypothesis testing on real SEMG recordings showed that source instantaneity hypothesis is very sensitive to electrode location along the fibers direction. Source separation gains using JADE BSS algorithm depend strongly on instantaneity hypothesis. Using LI BSS on SEMG requires great attention to electrode positioning; we provide a tool to test these on EI/EDM muscles.     

Comparison of methods for estimating motor unit firing rate time series from firing times

The central nervous system regulates recruitment and firing of motor units to modulate muscle tension. Estimation of the firing rate time series is typically performed by decomposing the electromyogram (EMG) into its constituent firing times, then lowpass filtering a constituent train of impulses. Little research has examined the performance of different estimation methods, particularly in the inevitable presence of decomposition errors. The study of electrocardiogram (ECG) and electroneurogram (ENG) firing rate time series presents a similar problem, and has applied novel simulation models and firing rate estimators. Herein, we adapted an ENG/ECG simulation model to generate realistic EMG firing times derived from known rates, and assessed various firing rate time series estimation methods. ENG/ECG-inspired rate estimation worked exceptionally well when EMG decomposition errors were absent, but degraded unacceptably with decomposition error rates of ⩾1%. Typical EMG decomposition error rates—even after expert manual review—are 3–5%. At realistic decomposition error rates, more traditional EMG smoothing approaches performed best, when optimal smoothing window durations were selected. This optimal window was often longer than the 400 ms duration that is commonly used in the literature. The optimal duration decreased as the modulation frequency of firing rate increased, average firing rate increased and decomposition errors decreased. Examples of these rate estimation methods on physiologic data are also provided, demonstrating their influence on measures computed from the firing rate estimate.     

Consensus for experimental design in electromyography (CEDE) project: Single motor unit matrix

The analysis of single motor unit (SMU) activity provides the foundation from which information about the neural strategies underlying the control of muscle force can be identified, due to the one-to-one association between the action potentials generated by an alpha motor neuron and those received by the innervated muscle fibers. Such a powerful assessment has been conventionally performed with invasive electrodes (i.e., intramuscular electromyography (EMG)), however, recent advances in signal processing techniques have enabled the identification of single motor unit (SMU) activity in high-density surface electromyography (HDsEMG) recordings. This matrix, developed by the Consensus for Experimental Design in Electromyography (CEDE) project, provides recommendations for the recording and analysis of SMU activity with both invasive (needle and fine-wire EMG) and non-invasive (HDsEMG) SMU identification methods, summarizing their advantages and disadvantages when used during different testing conditions. Recommendations for the analysis and reporting of discharge rate and peripheral (i.e., muscle fiber conduction velocity) SMU properties are also provided. The results of the Delphi process to reach consensus are contained in an appendix. This matrix is intended to help researchers to collect, report, and interpret SMU data in the context of both research and clinical applications.     

Analysis of motor unit firing characteristics in patients with motor neuron diseases

This study was designed to evaluate firing rate variability in patients with upper/lower motor neuron disorders. Twenty healthy subjects and 19 patients with motor neuron disorders participated in the study. Consecutive motor unit action potential pairs from extensor digitorum communis (EDC) muscle were recorded from each subject with trigger-delay line mode. Patients with motor neuron disorders (17.7?±?10.8?ms) showed significantly higher mean time variability of interpotential interval value than healthy volunteers (10.3?±?0.1?ms) (p?相似文献   

Frequency characteristics of signals and instrumentation: Implication for EMG biofeedback studies

Signals can be analyzed in either the time or frequency domain. In the time domain, the analysis consists of manipulating and measuring one or more characteristics of the signal that may vary with time. One can, for instance, rectify a signal, filter it, calculate its mean value, display the histogram of its amplitude, and so forth. Frequency analysis is less well understood because it requires a lengthy mathematical treatment most easily done by computer. However, it gives exclusive information on a signal. For instance, when the frequency content of a signal is known, it is easy to specify which characteristics an amplifier must have in order to amplify the signal without distortion, or to set the cutoff frequencies of filters to eliminate noise. Also, in many circumstances, frequency spectra are more easily interpreted than the original raw data. Such is the case with the EMG where the random aspect of the signal makes some form of processing (i.e., rectification, filtering, etc.) necessary, but not always as meaningful as we would like. Thus we present here the principal characteristics of frequency analysis, and discuss its usefulness in analyzing EMG signals and its application to biofeedback, clinical practice, and research.The authors acknowledge the technical assistance of F. Kemp, M. Goyette, and C. Goulet. T. Milner kindly reviewed the final version of the text. The preparation of this paper was supported through funds from Health and Welfare Canada (NHRDP) and the Centre de recherche, Institut de réadaptation de Montréal.     

The generation and diversification of spinal motor neurons: signals and responses

Motor neurons are probably the best characterised neuronal class in the vertebrate central nervous system and have become a paradigm for understanding the mechanisms that control the development of vertebrate neurons. For many investigators working on this problem the chick embryo is the model system of choice and from these studies a picture of the steps involved in motor neuron generation has begun to emerge. These findings suggest that motor neuron generation is shaped by extracellular signals that regulate intrinsic, cell-autonomous determinants at sequential steps during development. The chick embryo has played a prominent role in identifying the sources of these signals, defining their molecular identities and determining the cell intrinsic programs they regulate.     

Principles of high-spatial-resolution surface EMG (HSR-EMG): single motor unit detection and application in the diagnosis of neuromuscular disorders

The most detailed information about the structural and functional characteristics of the muscle can be gained from the single motor unit (MU) action potential. In addition, information about the activity of a single MU is essential for the diagnosis of neuromuscular disorders. Due to the low spatial resolution of conventional bipolar surface electromyography (EMG), the resulting signal is a superposition of a large number of simultaneous active MUs. The difficulty is in separating the activity of a single MU from simultaneous active adjacent MUs. In contrast to other non-invasive EMG procedures, the high-spatial-resolution-EMG (HSR-EMG), which is based on the use of a multi-electrode array in combination with a spatial filter procedure, allows the detection of single MU activity in a non-invasive way. It opens access to the excitation spread and enables the determination of the conduction velocity in single MUs, and the localization of the endplate region. In addition, HSR-EMG detects changes in the electrical activities of the MUs which are typical in neuromuscular disorders. Using HSR-EMG it was possible to identify 97% of all investigated volunteers and patients with muscular or neuronal disorders. Therefore, HSR-EMG is suitable as a tool for the non-invasive diagnosis of neuromuscular disorders.     

Analysis of the effects of firing rate and synchronization on spike-triggered averaging of multidirectional motor unit torque

Spike-triggered averaging (STA) of muscle force transients has often been used to estimate motor unit contractile properties, using the discharge of a motor unit within the muscle as the triggering events. For motor units that exert torque about multiple degrees-of-freedom, STA has also been used to estimate motor unit pulling direction. It is well known that motor unit firing rate and weak synchronization of motor unit discharges with other motor units in the muscle can distort STA estimates of contractile properties, but the distortion of STA estimates of motor unit pulling direction has not been thoroughly evaluated. Here, we derive exact equations that predict that STA decouples firing rate and synchronization distortion when used to estimate motor unit pulling direction. We derive a framework for analyzing synchronization, consider whether the distortion due to synchronization can be removed from STA estimates of pulling direction, and show that there are distributions of motor unit pulling directions for which STA is insensitive to synchronization. We conclude that STA may give insight into how motoneuronal synchronization is organized with respect to motor unit pulling direction. Action Editor: David Terman