Intramuscular and surface electromyogram changes during muscle fatigue

Twelve male subjects were tested to determine the effects of motor unit (MU) recruitment and firing frequency on the surface electromyogram (EMG) frequency power spectra during sustained maximal voluntary contraction (MVC) and 50% MVC of the biceps brachii muscle. Both the intramuscular MU spikes and surface EMG were recorded simultaneously and analyzed by means of a computer-aided intramuscular spike amplitude-frequency histogram and frequency power spectral analysis, respectively. Results indicated that both mean power frequency (MPF) and amplitude (rmsEMG) of the surface EMG fell significantly (P less than 0.001) together with a progressive reduction in MU spike amplitude and firing frequency during sustained MVC. During 50% MVC there was a significant decline in MPF (P less than 0.001), but this decline was accompanied by a significant increase in rmsEMG (P less than 0.001) and a progressive MU recruitment as evidenced by an increased number of MUs with relatively large spike amplitude. Our data suggest that the surface EMG amplitude could better represent the underlying MU activity during muscle fatigue and the frequency powers spectral shift may or may not reflect changes in MU recruitment and rate-coding patterns.     

Simulation analysis of interference EMG during fatiguing voluntary contractions. Part II--changes in amplitude and spectral characteristics.

Capabilities of amplitude and spectral methods for information extraction from interference EMG signals were assessed through simulation and preliminary experiment. Muscle was composed of 4 types of motor units (MUs). Different hypotheses on changes in firing frequency of individual MUs, intracellular action potential (IAP) and muscle fibre propagation velocity (MFPV) during fatigue were analyzed. It was found that changes in amplitude characteristics of interference signals (root mean square, RMS, or integrated rectified value, IEMG) detected by intramuscular and surface electrodes differed. RMS and IEMG of surface detected interference signals could increase even under MU firing rate reduction and without MU synchronisation. IAP profile lengthening can affect amplitude characteristics more significantly than MU firing frequency. Thus, an increase of interference EMG amplitude is unreliable to reflect changes in the neural drive. The ratio between EMG amplitude and contraction response can hardly characterise the so-called 'neuromuscular efficiency'. The recently proposed spectral fatigue indices can be used for quantification of interference EMG signals. The indices are practically insensitive to MU firing frequency. IAP profile lengthening and decrease in MFPV enhanced the index value, while recruitment of fast fatigable MUs reduced it. Sensitivity of the indices was higher than that of indices traditionally used.     

Using two-dimensional spatial information in decomposition of surface EMG signals.

Recently, high-density surface EMG electrode grids and multi-channel amplifiers became available for non-invasive recording of human motor units (MUs). We present a way to decompose surface EMG signals into MU firing patterns, whereby we concentrate on the importance of two-dimensional spatial differences between the MU action potentials (MUAPs). Our method is exemplified with high-density EMG data from the vastus lateralis muscle of a single subject. Bipolar and Laplacian spatial filtering was applied to the monopolar raw signals. From the single recording in this subject six different simultaneously active MUs could be distinguished using the spatial differences between MUAPs in the direction perpendicular to the muscle fiber direction. After spike-triggered averaging, 125-channel two-dimensional MUAP templates were obtained. Template-matching allowed tracking of all MU firings. The impact of spatial information was measured by using subsets of the MUAP templates, either in parallel or perpendicular to the muscle fiber direction. The use of one-dimensional spatial information perpendicular to the muscle fiber direction was superior to the use of a linear array electrode in the longitudinal direction. However, to detect the firing events of the MUs with a high accuracy, as needed for instance for estimation of firing synchrony, two-dimensional information from the complete grid electrode appears essential.     

Automatic localisation of innervation zones: A simulation study of the external anal sphincter

Traumas of the innervation zone (IZ) of the external anal sphincter (EAS), e.g. during delivery, can promote the development of faecal incontinence. Recently developed probes allow high-resolution detection of EMG signals from the EAS. The analysis of pelvic floor muscles by surface EMG (in particular, the estimation of the location of the IZ) has potential applications in the diagnosis and investigation of the mechanisms of incontinence.An automatic method (based on matched filter approach) for the estimation of the IZ distribution of EAS from surface EMG is discussed and tested using an analytical model of generation of EMG signals from sphincter muscles. Simulations are performed varying length of the fibres, thickness of the mucosa, position of the motor units, and force level. Different distributions of IZs are simulated.The performance of the proposed method in the estimation of the IZ distribution is affected by surface MUAP amplitude (as the estimation made by visual inspection), by mucosa thickness (performance decreases when fibre length is higher) and by different MU distributions. However, in general the method is able to identify the position of two IZ locations and can measure asymmetry of the IZ distribution. This strengthens the potential applications of high density surface EMG in the prevention and investigation of incontinence.     

Single motor unit and fiber action potentials during fatigue

Muscle fatigue is defined as a loss of tension development during constant stimulation. Although the relationship is not well documented, muscle fatigue has been inferred from electromyogram (EMG) signals. The purpose of this study was to determine the relationship between the amplitude and duration of single motor unit action potentials (MUAPs) and the loss of tension development (fatigue) in the medial gastrocnemius muscles of cats. Single motor units were fatigued by continuous stimulation at 10 or 80 Hz or with trains of 40-Hz stimuli. When motor units were stimulated at 10 Hz and with trains at 40 Hz (low frequency), tension declined and remained depressed during recovery. The changes in the MUAP correlated poorly with changes in tension. During and after stimulation at 80 Hz (high frequency), changes in the amplitude and duration of MUAPs correlated highly with changes in tension development. Since the EMG signal is dependent on a summation and cancellation of individual MUAPs, the EMG provides a reasonable estimate of high-frequency fatigue but an unreliable measure of low-frequency fatigue.     

Selective fatigue of fast motor units after electrically elicited muscle contractions.

The aim of the present study was to elucidate the electrophysiological manifestations of selective fast motor unit (MU) activation by electrical stimulation (ES) of knee extensor muscles. In six male subjects, test contraction measurement at 40% maximal voluntary contraction (MVC) was performed before and at every 5 min (5, 10, 15 and 20 min) during 20-min low intensity intermittent exercise of either ES or voluntary contractions (VC) at 10% MVC (5-s isometric contraction and 5-s rest cycles). Both isolated intramuscular MU spikes obtained from three sets of bipolar fine-wire electrodes and surface electromyogram (EMG) were simultaneously recorded and were analyzed by means of a computer-aided intramuscular spike amplitude-frequency analysis and frequency power spectral analysis, respectively. Results indicated that mean MU spike amplitude, particularly those MUs with relatively large amplitude, was significantly reduced while those MUs with small spike amplitude increased their firing rate during the 40% MVC test contraction after the ES. This was accompanied by the increased amplitude of surface EMG (rmsEMG). However, no such significant changes in the intramuscular and surface EMGs were observed after VC. These findings indicated differential MU activation patterns in terms of MU recruitment and rate coding characteristics during ES and VC, respectively. Our data strongly suggest the possibility of "an inverse size principle" of MU recruitment during ES.     

Oxygen availability and motor unit activity in humans.

Six men were studied to determine the interrelationships among blood supply, motor unit (MU) activity and lactate concentrations during intermittent isometric contractions of the hand grip muscles. The subjects performed repeated contractions at 20% of maximal voluntary contraction (MVC) for 2 s followed by 2-s rest for 4 min with either unhindered blood circulation or arterial occlusion given between the 1st and 2nd min. The simultaneously recorded intramuscular MU spikes and surface electromyogram (EMG) data indicated that mean MU spike amplitude, firing frequency and the parameters of surface EMG power spectra (mean power frequency and root mean square amplitude) remained constant during the experiment with unhindered circulation, providing no electrophysiological signs of muscle fatigue. Significant increases in mean MU spike amplitude and frequency were, however, evident during the contractions with arterial occlusion. Similar patterns of significant changes in the surface EMG spectra parameters and venous lactate concentration were also observed, while the integrated force-time curves remained constant. These data would suggest that the metabolic state of the active muscles may have played an important role in the regulation of MU recruitment and rate coding patterns during exercise.     

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.     

Investigation of motor unit recruitment during stimulated contractions of tibialis anterior muscle

This work investigated motor unit (MU) recruitment during transcutaneous electrical stimulation (TES) of the tibialis anterior (TA) muscle, using experimental and simulated data. Surface electromyogram (EMG) and torque were measured during electrically-elicited contractions at different current intensities, on eight healthy subjects.EMG detected during stimulation (M-wave) was simulated selecting the elicited MUs on the basis of: (a) the simulated current density distribution in the territory of each MU and (b) the excitation threshold characteristic of the MU. Exerted force was simulated by adding the contribution of each of the elicited MUs. The effects of different fat layer thickness (between 2 and 8 mm), different distributions of excitation thresholds (random excitation threshold, higher threshold for larger MUs or smaller MUs), and different MU distributions within the muscle (random distribution, larger MU deeper in the muscle, smaller MU deeper) on EMG variables and torque were tested.Increase of the current intensity led to a first rapid increase of experimental M-wave amplitude, followed by a plateau. Further increases of the stimulation current determined an increase of the exerted force, without relevant changes of the M-wave. Similar results were obtained in simulations.Rate of change of conduction velocity (CV) and leading coefficient of the second order polynomial interpolating the force vs. stimulation level curve were estimated as a function of increasing current amplitudes. Experimental data showed an increase of estimated CV with increasing levels of the stimulation current (for all subjects) and a positive leading coefficient of force vs. stimulation current curve (for five of eight subjects). Simulations matched the experimental results only when larger MUs were preferably located deeper in the TA muscle (in line with a histochemical study). Marginal effect of MU excitation thresholds was observed, suggesting that MUs closer to the stimulation electrode are recruited first during TES regardless of their excitability.     

Detection of individual motor units of the puborectalis muscle by non-invasive EMG electrode arrays

PURPOSE: The purpose of the study was to demonstrate that anatomical features of individual motor units of the puborectalis muscle can be detected with non-invasive electromyography (EMG) and to evaluate differences in electrophysiological properties of the puborectalis muscles in a small group of healthy and pathologic subjects. METHODS: Multichannel EMG was recorded by means of a flexible probe applied on the gloved index finger and carrying an array of eight equally spaced (1.15 mm) electrodes. A multichannel EMG amplifier provided seven outputs corresponding to the pairs of adjacent electrodes. Tests were performed in three different positions (dorsal, left and right) over the puborectalis muscle on 20 subjects (nine healthy, seven constipated and four incontinent patients). Motor unit action potentials (MUAPs) generated at the innervation zone of a MU and propagating along the muscle fibers generated repetitive characteristic patterns on the seven output channels allowing identification of anatomical features of the motor units. RESULTS: MUAPs were observed travelling in either one or both directions with the array in dorsal position, and mainly in ventral-to-dorsal direction in either lateral position. MUAP amplitude was lower in constipated and incontinent patients with respect to healthy subjects. The conduction velocity estimated on the identified MUAPs was lower for constipated patients with respect to healthy subjects suggesting different mechanical properties of the active motor units. CONCLUSIONS: This technique allows the extraction of relevant information about the anatomical features (innervation zone position and overlapping of motor unit branches) of the puborectalis muscle and its electrophysiological properties and maybe can be applied as an novel methodology for assessing the anorectal function in patients.     

Non-invasive characterization of single motor unit electromyographic and mechanomyographic activities in the biceps brachii muscle.

The aim of the study was to investigate amplitude and frequency content of single motor unit (MU) electromyographic (EMG) and mechanomyographic (MMG) responses. Multi-channel surface EMG and MMG signals were detected from the dominant biceps brachii muscle of 10 volunteers during isometric voluntary contractions at 20%, 50%, and 80% of the maximal voluntary contraction (MVC) force. Each contraction was performed three times in the experimental session which was repeated in three non-consecutive days. Single MU action potentials were identified from the surface EMG signals and their times of occurrence used to trigger the averaging of the MMG signal. At each contraction level, the MUs with action potentials of highest amplitude were identified. Single MU EMG and MMG amplitude and mean frequency were estimated with normalized standard error of the mean within subjects (due to repetition of the measure in different trials and experimental sessions) smaller than 15% and 7%, respectively, in all conditions. The amplitude of the action potentials of the detected MUs increased with increasing force (mean +/- SD, 244 +/- 116 microV at 20% MVC, and 1426 +/- 638 microV at 80% MVC; P < 0.001) while MU MMG amplitude increased from 20% to 50% MVC (40.5 +/- 20.9 and 150 +/- 88.4 mm/s(2), respectively; P<0.001) and did not change significantly between 50% and 80% MVC (129 +/ -82.7 mm/s(2) at 80% MVC). MU EMG mean frequency decreased with contraction level (20% MVC: 97.2 +/- 13.9 Hz; 80% MVC: 86.2 +/- 11.4 Hz; P < 0.001) while MU MMG mean frequency increased (20% MVC: 33.2 +/- 6.8 Hz; 80% MVC: 40.1 +/- 6.1 Hz; P < 0.001). EMG peak-to-peak amplitude and mean frequency of individual MUs were not correlated with the corresponding variables of MMG at any contraction level.     

Motor unit activity and surface electromyogram power spectrum during increasing force of contraction

Twelve male subjects were tested to determine the relationship between motor unit (MU) activities and surface electromyogram (EMG) power spectral parameters with contractions increasing linearly from zero to 80% of maximal voluntary contraction (MVC). Intramuscular spike and surface EMG signals recorded simultaneously from biceps brachii were analyzed by means of a computer-aided intramuscular MU spike amplitude-frequency (ISAF) histogram and an EMG frequency power spectral analysis. All measurements were made in triplicate and averaged. Results indicate that there were highly significant increases in surface EMG amplitude (71 +/- 31.3 to 505 +/- 188 microV, p less than 0.01) and mean power frequency (89 +/- 13.3 to 123 +/- 23.5 Hz, p less than 0.01) with increasing force. These changes were accompanied by progressive increases in the firing frequency of MU's initially recruited, and of newly recruited MU's with relatively larger spike amplitudes. The group data in the ISAF histograms revealed significant increases in mean spike amplitude (412 +/- 79 to 972 +/- 117 microV, p less than 0.01) and mean firing frequency (17.8 +/- 5.4 to 24.7 +/- 4.1 Hz, p less than 0.01). These data suggest that surface EMG spectral analysis can provide a sensitive measure of the relative changes in MU activity during increasing force output.     

Motor Unit Characteristics after Targeted Muscle Reinnervation

Targeted muscle reinnervation (TMR) is a surgical procedure used to redirect nerves originally controlling muscles of the amputated limb into remaining muscles above the amputation, to treat phantom limb pain and facilitate prosthetic control. While this procedure effectively establishes robust prosthetic control, there is little knowledge on the behavior and characteristics of the reinnervated motor units. In this study we compared the m. pectoralis of five TMR patients to nine able-bodied controls with respect to motor unit action potential (MUAP) characteristics. We recorded and decomposed high-density surface EMG signals into individual spike trains of motor unit action potentials. In the TMR patients the MUAP surface area normalized to the electrode grid surface (0.25 ± 0.17 and 0.81 ± 0.46, p < 0.001) and the MUAP duration (10.92 ± 3.89 ms and 14.03 ± 3.91 ms, p < 0.01) were smaller for the TMR group than for the controls. The mean MUAP amplitude (0.19 ± 0.11 mV and 0.14 ± 0.06 mV, p = 0.07) was not significantly different between the two groups. Finally, we observed that MUAP surface representation in TMR generally overlapped, and the surface occupied by motor units corresponding to only one motor task was on average smaller than 12% of the electrode surface. These results suggest that smaller MUAP surface areas in TMR patients do not necessarily facilitate prosthetic control due to a high degree of overlap between these areas, and a neural information—based control could lead to improved performance. Based on the results we also infer that the size of the motor units after reinnervation is influenced by the size of the innervating motor neuron.     

The linear electrode array: a useful tool with many applications.

In this review we describe the basic principles of operation of linear electrode arrays for the detection of surface EMG signals, together with their most relevant current applications. A linear array of electrodes is a system which detects surface EMG signals in a number of points located along a line. A spatial filter is usually placed in each point for signal detection, so that the recording of EMG signals with linear arrays corresponds to the sampling in one spatial direction of a spatially filtered version of the potential distribution over the skin. Linear arrays provide indications on motor unit (MU) anatomical properties, such as the locations of the innervation zones and tendons, and the fiber length. Such systems allow the investigation of the properties of the volume conductor and its effect on surface detected signals. Moreover, linear arrays allow to estimate muscle fiber conduction velocity with a very low standard deviation of estimation (of the order of 0.1-0.2 m/s), thus providing reliable indications on muscle fiber membrane properties and their changes in time (for example with fatigue or during treatment). Conduction velocity can be estimated from a signal epoch (global estimate) or at the single MU level. In the latter case, MU action potentials are identified from the interference EMG signals and conduction velocity is estimated for each detected potential. In this way it is possible, in certain conditions, to investigate single MU control and conduction properties with a completely non-invasive approach. Linear arrays provide valuable information on the neuromuscular system properties and appear to be promising tools for applied studies and clinical research.     

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.     

Assessment of muscle fatigue in low level monotonous task performance during car driving.

Knowledge of the muscle activation and the development of muscle fatigue may provide more inside in the effects of long-term driving in the occurrence of health problems in the neck/shoulder/back area. The basic assumption behind fatigue detection with electromyography (EMG) is an increase in the EMG amplitude and a decrease of the mean frequency (MF). This study aimed at checking this assumption in monotonous task performance with low level activity during car driving. Surface electromyography was captured from left and right trapezius and deltoid muscles, during a repetitive, non-continuous, driving task (gearing and steering) and the active parts were separated from the non-active parts. Muscle stiffness was reported by more than half of the subjects after a 1 h drive. Only for the active parts a significant decrease of the MF was seen. But also the EMG amplitude decreased significantly. Two possible mechanisms are posted in literature for this finding: no extra recruitment of motor units (MU) and potentiation of muscle fibers. Literature also hypothesizes that low-force occupational work engages only a fraction of the MU available for recruitment and that these units are selectively type I muscle fibers (Cinderella fibers). Initiators of this phenomenon are probably the time lag between activations and the stress from driving and vibration exposure.     

Force generation performance and motor unit recruitment strategy in muscles of contralateral limbs.

The purpose of the present study was to determine whether the motor unit (MU) recruitment strategy of the agonist and antagonist muscles in the dominant arm differs from that in the non-dominant arm. The median frequency (MF) of the power density spectrum (PDS) of the electromyogram (EMG) was used as a tracking parameter to describe the MU recruitment. In 8 subjects the EMG was recorded from the biceps brachii and triceps brachii of each limb during isometric elbow flexion performed in a ramp fashion. Force was increased from 0 to 100% of the maximum voluntary contraction (MVC) in 3 s following a track displayed on an oscilloscope. When comparing the dominant versus non-dominant arm we found no statistical difference in the MU recruitment pattern of the biceps brachii and the triceps. Because the dominant arm was not always the better performing arm, we grouped the data according to the ability of the subjects to track the ramp signal. In this case we found a statistically significant difference between the better and worse performing arm in the full MU recruitment of the biceps. A more precise and accurate control of the increase in force was obtained when the central nervous system selected a slower and prolonged recruitment of MUs in the agonist muscle.     

Automatic decomposition of multichannel intramuscular EMG signals

We describe an automatic algorithm for decomposing multichannel EMG signals into their component motor unit action potential (MUAP) trains, including signals from widely separated recording sites in which MUAPs exhibit appreciable interchannel offset and jitter. The algorithm has two phases. In the clustering phase, the distinct, recurring MUAPs in each channel are identified, the ones that correspond to the same motor units are determined by their temporal relationships, and multichannel templates are computed. In the identification stage, the MUAP discharges in the signal are identified using matched filtering and superimposition resolution techniques. The algorithm looks for the MUAPs with the largest single channel components first, using matches in one channel to guide the search in other channels, and using information from the other channels to confirm or refute each identification. For validation, the algorithm was used to decompose 10 real 6-to-8-channel EMG signals containing activity from up to 25 motor units. Comparison with expert manual decomposition showed that the algorithm identified more than 75% of the total 176 MUAP trains with an accuracy greater than 95%. The algorithm is fast, robust, and shows promise to be accurate enough to be a useful tool for decomposing multichannel signals. It is freely available at http://emglab.stanford.edu.     

Sample entropy analysis of surface EMG for improved muscle activity onset detection against spurious background spikes

Voluntary surface electromyogram (EMG) signal is sometimes contaminated by spurious background spikes of both physiological and extrinsic or accidental origins. A novel method of muscle activity onset detection against such spurious spikes was proposed in this study based primarily on the sample entropy (SampEn) analysis of the surface EMG. The method takes advantage of the nonlinear properties of the SampEn analysis to distinguish voluntary surface EMG signals from spurious background spikes in the complexity domain. To facilitate muscle activity onset detection, the SampEn analysis of surface EMG was first performed to highlight voluntary EMG activity while suppressing spurious background spikes. Then, a SampEn threshold was optimized for muscle activity onset detection. The performance of the proposed method was examined using both semi-synthetic and experimental surface EMG signals. The SampEn based methods effectively reduced the detection error induced by spurious background spikes and achieved improved performance over the methods relying on conventional amplitude thresholding or its extended version in the Teager Kaiser Energy domain.     

The application of independent component analysis to the multi-channel surface electromyographic signals for separation of motor unit action potential trains: part I-measuring techniques.

The purpose of this study is to examine whether or not the application of independent component analysis (ICA) is useful for separation of motor unit action potential trains (MUAPTs) from the multi-channel surface EMG (sEMG) signals. In this study, the eight-channel sEMG signals were recorded from tibialis anterior muscles during isometric dorsi-flexions at 5%, 10%, 15% and 20% maximal voluntary contraction. Recording MUAP waveforms with little time delay mounted between the channels were obtained by vertical sEMG channel arrangements to muscle fibers. The independent components estimated by FastICA were compared with the sEMG signals and the principal components calculated by principal component analysis (PCA). From our results, it was shown that FastICA could separate groups of similar MUAP waveforms of the sEMG signals separated into each independent component while PCA could not sufficiently separate the groups into the principal components. A greater reduction of interferences between different MUAP waveforms was demonstrated by the use of FastICA. Therefore, it is suggested that FastICA could provide much better discrimination of the properties of MUAPTs for sEMG signal decomposition, i.e. waveforms, discharge intervals, etc., than not only PCA but also the original sEMG signals.