Motor unit recruitment strategies investigated by surface EMG variables.

During isometric contractions of increasing strength, motor units (MUs) are recruited by the central nervous system in an orderly manner starting with the smallest, with muscle fibers that usually show the lowest conduction velocity (CV). Theory predicts that the higher the velocity of propagation of the action potential, the higher the power at high frequencies of the detected surface signal. These considerations suggest that the power spectral density of the surface detected electromyogram (EMG) signal may give indications about the MU recruitment process. The purpose of this paper is to investigate the potential and limitations of spectral analysis of the surface EMG signal as a technique for the investigation of muscle force control. The study is based on a simulation approach and on an experimental investigation of the properties of surface EMG signals detected from the biceps brachii during isometric linearly increasing torque contractions. Both simulation and experimental data indicate that volume conductor properties play an important role as confounding factors that may mask any relation between EMG spectral variables and estimated CV as a size principle parameter during ramp contractions. The correlation between spectral variables and CV is thus significantly lower when the MU pool is not stable than during constant-torque isometric contractions. Our results do not support the establishment of a general relationship between spectral EMG variables and torque or recruitment strategy.     

Influence of amplitude cancellation on the simulated surface electromyogram.

The purpose of the study was to quantify the influence of selected motor unit properties and patterns of activity on amplitude cancellation in the simulated surface electromyogram (EMG). The study involved computer simulations of a motor unit population with physiologically defined recruitment and rate coding characteristics that activated muscle fibers whose potentials were recorded on the skin over the muscle. Amplitude cancellation was quantified as the percent difference in signal amplitude when motor unit potentials were summed before and after rectification. The simulations involved varying the level of activation for the motor unit population, the recording configuration, the upper limit of motor unit recruitment, peak discharge rates, the amount of motor unit synchronization, muscle fiber length, the thickness of the subcutaneous tissue, and the motor unit properties that change with advancing age. The results confirmed a previous experimental report (Day SJ and Hulliger M, J Neurophysiol 86: 2144-2158, 2001) that amplitude cancellation in the surface EMG can reach 62% at maximal activation. A decrease in the range of amplitudes of the motor unit potentials, as can occur during fatiguing contractions, increased amplitude cancellation up to approximately 85%. Differences in the amount of amplitude cancellation were observed across all simulated conditions, and resulted in substantial changes in the absolute magnitude of the EMG signal. The most profound factors influencing amplitude cancellation were the number of active motor units and the duration of the action potentials. The effects of amplitude cancellation were minimal (<5%) when the EMG amplitude was normalized to maximal values, with the exception of variations in peak discharge rate and recruitment range, which resulted in differences up to 17% in the normalized EMG signal across conditions. These results indicate the amount of amplitude cancellation that can occur in various experimental conditions and its influence on absolute and relative measures of EMG amplitude.     

Nonlinear time-course of lumbar muscle fatigue using recurrence quantifications

 Isometric skeletal muscle fatigue is usually assumed to be a linear process based upon the monotonic decrease in spectral frequency of the EMG. Since spectral analysis by fast Fourier transform (FFT) constitutes a linear transformation of the data, the present study was designed to reevaluate the time-course of muscle fatigue with a nonlinear tool, recurrence quantification analysis (RQA). Surface EMG recordings were obtained from the multifidus muscle of 17 human subjects during isometric posture-holding of the upper torso. The process of muscle fatigue was found to be linear for 59% of the subjects by FFT criteria, but nonlinear for 76% by RQA criteria. As a demonstrative control, both slow and fast transients occurring within a nonlinear mathematical process could be accurately depicted by RQA, but not by FFT. It is concluded that assessment of EMG patterns by nonlinear techniques can give insight into the time-course of fatiguing muscles attributed to the summation of several nonlinear and competing processes. Received: 12 November 1998 / Accepted in revised form: 29 November 1999     

RQA在肌电分析中的应用

介绍了递归图的生成方法和定量递归分析（RQA）中递归点的百发数,确定性线段的百分数,线段分布香农熵等分析量的意义。应用RQA分析肱二头肌及肱桡肌在不同负重下的肌电信号,发现肽二头肌肌电信号的递归点百分数的比肱肌高,有较强的周期性嵌入。与同一信号所作的FFT谱分析相比较,RQA法有较同的区分灵敏性,是肌电分析的一种新方法,它在其他复杂的生理信号处理中也有十分广阔的应用前景。     

Assessment of low back muscle fatigue by surface EMG signal analysis: methodological aspects.

This paper focuses on methodological issues related to surface electromyographic (EMG) signal detection from the low back muscles. In particular, we analysed (1) the characteristics (in terms of propagating components) of the signals detected from these muscles; (2) the effect of electrode location on the variables extracted from surface EMG; (3) the effect of the inter-electrode distance (IED) on the same variables; (4) the possibility of assessing fatigue during high and very low force level contractions. To address these issues, we detected single differential surface EMG signals by arrays of eight electrodes from six locations on the two sides of the spine, at the levels of the first (L1), the second (L2), and the fifth (L5) lumbar vertebra. In total, 42 surface EMG channels were acquired at the same time during both high and low force, short and long duration contractions. The main results were: (1) signal quality is poor with predominance of non-travelling components; (2) as a consequence of point (1), in the majority of the cases it is not possible to reliably estimate muscle fiber conduction velocity; (3) despite the poor signal quality, it was possible to distinguish the fatigue properties of the investigated muscles and the fatigability at different contraction levels; (4) IED affects the sensitivity of surface EMG variables to electrode location and large IEDs are suggested when spectral and amplitude analysis is performed; (5) the sensitivity of surface EMG variables to changes in electrode location is on average larger than for other muscles with less complex architecture; (6) IED influences amplitude initial values and slopes, and spectral variable initial values; (7) normalized slopes for both amplitude and spectral variables are not affected by IED and, thus, are suggested for fatigue analysis at different postures or during movement, when IED may change in different conditions (in case of separated electrodes); (8) the surface EMG technique at the global level of amplitude and spectral analysis cannot be used to characterize fatigue properties of low back muscles during very low level, long duration contractions since in these cases the non-stable MU pool has a major influence on the EMG variables. These considerations clarify issues only partially investigated in past studies. The limitations indicated above are important and should be carefully discussed when presenting surface EMG results as a means for low back muscle assessment in clinical practice.     

The extraction of neural strategies from the surface EMG.

This brief review examines some of the methods used to infer central control strategies from surface electromyogram (EMG) recordings. Among the many uses of the surface EMG in studying the neural control of movement, the review critically evaluates only some of the applications. The focus is on the relations between global features of the surface EMG and the underlying physiological processes. Because direct measurements of motor unit activation are not available and many factors can influence the signal, these relations are frequently misinterpreted. These errors are compounded by the counterintuitive effects that some system parameters can have on the EMG signal. The phenomenon of crosstalk is used as an example of these problems. The review describes the limitations of techniques used to infer the level of muscle activation, the type of motor unit recruited, the upper limit of motor unit recruitment, the average discharge rate, and the degree of synchronization between motor units. Although the global surface EMG is a useful measure of muscle activation and assessment, there are limits to the information that can be extracted from this signal.     

Limitations of the surface electromyography technique for estimating motor unit synchronization

Motor unit synchronization was estimated from the surface electromyograms (EMG) of the first dorsal interosseus muscle of human volunteers by a simplified surface-EMG technique (Milner-Brown et al. 1973, 1975). Single motor units were identified from intramuscular recordings and were used to obtain a spike-triggered average of the surface-EMG. The discharge rate of a reference motor unit was controlled at two levels (high and low), and the effect of motor unit activity on the surface-EMG estimate of synchronization was studied in 56 motor units. The surface-EMG estimate of motor unit synchronization was significantly higher when the reference motor unit discharged at the high rate than when it discharged at the low rate. A regression analysis indicated that the synchronization ratio calculated from the surface EMG was significantly correlated with the level of EMG activity in the muscle. Motor unit synchronization was also estimated from surface-EMG measurements that were derived by computer simulation. The simulation permitted manipulation of motor unit activity (discharge rate and recruitment) with a complete absence of synchrony among the units in the pool. The stimulated surface-EMG index was influenced by an artifact associated with signal rectification, and this effect changed non-monotonically with motor unit activity. Furthermore, the increase in the motor unit activity reduced the signal-to-noise ratio of the spike-triggered surface EMG average, and consequently decreased the sensitivity of the surface-EMG index as an estimate of motor unit synchronization. We conclude that the simplified surface-EMG method (Milner-Brown et al. 1973, 1975) does not provide a useful index of motor unit synchronization due to its inability to accurately distinguish the synchronization from methodological effects related to a rectification artifact and variation in the signal-to-noise ratio.     

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.     

Surface EMG signal processing during isometric contractions

This paper provides an overview of techniques suitable for the estimation, interpretation and understanding of time variations that affect the surface electromyographic (EMG) signal during sustained voluntary or electrically elicited contractions. These variations concern amplitude variables, spectral variables and muscle fiber conduction velocity, are interdependent and are referred to as the ‘fatigue plot'. The fatigue plot provides information suitable for the classification of muscle behavior. In addition, the information obtainable by means of linear electrode arrays is discussed, and applications of mathematical models for the interpretation of array signals are presented. The model approach provides additional ways for the classification of muscle behavior.     

M-wave properties during progressive motor unit activation by transcutaneous stimulation.

The aim of this study was to interpret changes in experimentally recorded M waves with progressive motor unit (MU) activation based on simulation of the surface electromyogram. Activation order during transcutaneous electrical stimulation was analyzed by investigating M-wave average rectified value, spectral properties, and conduction velocity (CV) during electrically elicited contractions. M-waves were detected from the biceps brachii muscle of 10 healthy male subjects by a linear adhesive array of eight electrodes. Electrical stimulation was delivered to the motor point at either constant current intensity (40, 60, 80, and 100% of the supramaximal stimulation current) or with linearly increasing current. A model of surface electromyogram generation that varied activation order based on MU size and location was used to interpret the experimental results. From the experimental and model analysis, it was found that 1) MUs tended to be activated from low to high CV and from the superficial to the deep muscle layers with increasing transcutaneous electrical stimulation of the biceps brachii muscle, and 2) characteristic spectral frequencies of the M-wave were affected by many factors other than average CV (such as the activation order by MU location or the spread of the MU innervation zones and CVs), thus decreasing with a concomitant increase in CV during progressive MU activation.     

EMG recurrence quantifications in dynamic exercise

This study was designed to evaluate the suitability of nonlinear recurrence quantification analysis (RQA) in assessing electromyograph (EMG) signals during dynamic exercise. RQA has been proven to be effective in analyzing nonstationary signals. The subject group consisted of 19 male patients diagnosed with low back pain. EMG signals were recorded from left and right paraspinal muscles during isoinertial exercise both before and after 12 weeks of regimented physical therapy. Autorecurrence analysis was performed between the left and right EMG signals individually, and cross-recurrence analysis was performed on the left-right EMG pairs. Spectral analysis of the EMG signals was employed as an independent, objective measure of fatigue. Increase in the RQA variable % determinism during the 90-s dynamic tests was found to be a good marker for fatigue. Before physical therapy, this nonlinear marker revealed simultaneous increases in motor unit recruitment within each pool and between left and right pools. After physical therapy, the motor unit recruitment was less within and between pools, indicative of increased fatigue resistance. Finally, fatigue resistance (less increase in % determinism) correlated well with subjective scores of pain relief. Taken together, these latter results indicate that recurrence analysis may be useful in charting the efficacy of a specific exercise therapy program in reducing low back pain by elevating the fatigue threshold.     

Experimental muscle pain increases mechanomyographic signal activity during sub-maximal isometric contractions.

This study was designed to investigate the local effect of experimental muscle pain on the MMG and the surface EMG during a range of sub-maximal isometric contractions. Muscle pain was induced by injections of hypertonic saline into the biceps brachii muscle in 12 subjects. Injections of isotonic saline served as a control. Pain intensity and location, MMG and surface EMG from the biceps brachii were assessed during static isometric (0%, 10%, 30%, 50% and, 70% of the maximal voluntary contraction) and ramp isometric (0-50% of the maximal voluntary contraction) elbow flexions. MMG and surface EMG signals were analyzed in the time and frequency domain. Experimentally induced muscle pain induced an increase in root mean square values of the MMG signal while no changes were observed in the surface EMG. Most likely this increase reflects changes in the mechanical contractile properties of the muscle and indicates compensatory mechanisms, i.e. decreased firing rate and increased twitch force to maintain a constant force output in presence of experimental muscle pain. Under well-controlled conditions, MMG recordings may be more sensitive than surface EMG recordings and clinically useful for detecting non-invasively increased muscle mechanical contributions during muscle pain conditions.     

Simulations of the alpha motoneuron pool electromyogram reflex at different preactivation levels in man

The alpha motoneuron pool and the surface electromyogram (EMG) of the human soleus muscle are modelled, respectively, by an alpha motoneuron pool model generating the firing patterns in the motor units of e muscle and by a muscle model using these discharge patterns to simulate the surface EMG. In the alpha motoneuron pool model, we use a population of motoneurons in which cellular properties like cell size and membrane conductance are distributed according to experimentally observed data. By calculating the contribution from each motor unit, the muscle model predicts the EMG. Wave forms of the motor unit action potentials in the surface EMG are obtained from experimental data. Using the model, we are able to give a quantitative prediction of the motoneuron pool activity and the reflex EMG output at different preactivation levels. The simulated data are consistent with experimentally obtained results in healthy humans. During static isometric muscle preactivations, the simulations show that the reflex strength is highly dependent on the intrinsic threshold properties of the alpha motoneuron pool. Received: 27 April 1993/Accepted in revised form: 8 September 1993     

Separation of propagating and non propagating components in surface EMG

Surface electromyogram (EMG) detected by electrode arrays along the muscle fibre direction can be approximated by the sum of propagating and non propagating components. A technique to separate propagating and non propagating components in surface EMG signals is developed. The first step is an adaptive filter, which allows obtaining an estimation of the delay between signals detected at different channels and a first estimate of propagating and non propagating components; the second step is used to optimise the estimation of the two components. The method is applicable to signals with one propagating and one non propagating component. It was optimised on simulated signals, and then applied to single motor unit action potentials (MUAP) and to electrically elicited EMG (M-waves).

The new method was first tested on phenomenological signals constituted by the sum of a propagating and a non propagating signal and then applied to simulated and experimental EMG signals. Simulated signals were generated by a cylindrical, layered volume conductor model. Experimental signals were monopolar surface EMG signals collected from the abductor pollicis brevis muscle and M-waves recorded during transcutaneous electrical stimulation of the biceps muscle. The technique may find different applications: in single motor unit (MU) studies (a) for decreasing the variability and bias of CV estimates due to the presence of the non propagating components, (b) for estimating automatically the length of the muscle fibres from only three detected channels and (c) for removal of the stimulation artifact M-waves.     

Reliability of techniques to assess human neuromuscular function in vivo.

The purpose of this study was to comprehensively evaluate the reliability of a large number of commonly utilized experimental tests of in vivo human neuromuscular function separated by 4-weeks. Numerous electrophysiological parameters (i.e., voluntary and evoked electromyogram [EMG] signals), contractile properties (i.e., evoked forces and rates of force development and relaxation), muscle morphology (i.e., MRI-derived cross-sectional area [CSA]) and performance tasks (i.e., steadiness and time to task failure) were assessed from the plantarflexor muscle group in 17 subjects before and following 4-weeks where they maintained their normal lifestyle. The reliability of the measured variables had wide-ranging levels of consistency, with coefficient of variations (CV) ranging from approximately 2% to 20%, and intraclass correlation coefficients (ICC) between 0.53 and 0.99. Overall, we observed moderate to high-levels of reliability in the vast majority of the variables we assessed (24 out of the 29 had ICC>0.70 and CV<15%). The variables demonstrating the highest reliability were: CSA (ICC=0.93-0.98), strength (ICC=0.97), an index of nerve conduction velocity (ICC=0.95), and H-reflex amplitude (ICC=0.93). Conversely, the variables demonstrating the lowest reliability were: the amplitude of voluntary EMG signal (ICC=0.53-0.88), and the time to task failure of a sustained submaximal contraction (ICC=0.64). Additionally, relatively little systematic bias (calculated through the limits of agreement) was observed in these measures over the repeat sessions. In conclusion, while the reliability differed between the various measures, in general it was rather high even when the testing sessions are separated by a relatively long duration of time.     

A simulation study to examine the use of cross-correlation as an estimate of surface EMG cross talk.

Cross-correlation between surface electromyogram (EMG) signals is commonly used as a means of quantifying EMG cross talk during voluntary activation. To examine the reliability of this method, the relationship between cross talk and the cross-correlation between surface EMG signals was examined by using model simulation. The simulation results illustrate an increase in cross talk with increasing subcutaneous fat thickness. The results also indicate that the cross-correlation function decays more rapidly with increasing distance from the active fibers than cross talk, which was defined as the normalized EMG amplitude during activation of a single muscle. The influence of common drive and short-term motor unit synchronization on the cross-correlation between surface EMG signals was also examined. While common drive did not alter the maximum value of the cross-correlation function, the correlation increased with increasing motor unit synchronization. It is concluded that cross-correlation analysis is not a suitable means of quantifying cross talk or of distinguishing between cross talk and coactivation during voluntary contraction. Furthermore, it is possible that a high correlation between surface EMG signals may reflect an association between motor unit firing times, for example due to motor unit synchronization.     

基于定量分析方法的动作表面肌电信号分析

介绍了非线性数据处理方法递归图法(recurrence plots,RP)及其定量分析方法(recurrence quantifi-cation analysis,RQA),并利用RP和RQA研究了动作表面肌电信号。研究发现,表面肌电信号在不同动作模式下其所对应的RP图在结构上差异明显,通过计算两通道肌电信号的RQA指标递归率,发现不同动作信号的RQA指标递归率值具有不同的聚类分布。该方法为肌电信号的动作模式分类提供了一种新的思路。     

Analysis of motor units with high-density surface electromyography

Although the behaviour of individual motor units is classically studied with intramuscular EMG, recently developed techniques allow its analysis also from EMG recorded in multiple locations over the skin surface (high-density surface EMG). The analysis of motor units from the surface EMG is useful when the insertion of needles is not desirable or not possible. Moreover, surface EMG allows the measure of motor unit properties which are difficult to assess with invasive technology (e.g., muscle fiber conduction velocity or location of innervation zones) and may increase the number of detectable motor units with respect to selective intramuscular recordings. Although some limitations remain, both the discharge pattern and muscle fiber properties of individual motor units can currently be analyzed non-invasively. This review presents the conditions and methodologies which allow the investigation of motor units with surface EMG.