Estimation of monopolar signals from sphincter muscles and removal of common mode interference

The detection of surface electromyogram (EMG) by multi-electrode systems is applied in many research studies. The signal is usually recorded by means of spatial filters (linear combination of the potential under at least two electrodes) with vanishing sum of weights. Nevertheless, more information could be extracted from monopolar signals measured with respect to a reference electrode away from the muscle. Under certain conditions, surface EMG signal along a curve parallel to the fibre path has zero mean (property approximately satisfied when EMG is sampled by an array of electrodes that covers the entire support of the signal in space). This property allows estimating monopolar from single differential (SD) signals by pseudoinversion of the matrix relating monopolar to SD signals. The method applies to EMG signals from the external anal sphincter muscle, recorded using a specific cylindrical probe with an array of electrodes located along the circular path of the fibres. The performance of the algorithm for the estimation of monopolar from SD signals is tested on simulated signals. The estimation error of monopolar signals decreases by increasing the number of channels. Using at least 12 electrodes, the estimation error is negligible. The method applies to single fibre action potentials, single motor unit action potentials, and interference signals.The same method can also be applied to reduce common mode interference from SD signals from muscles with rectilinear fibres. In this case, the last SD channel defined as the difference between the potentials of the last and the first electrodes must be recorded, so that the sum of all the SD signals vanishes. The SD signals estimated from the double differential signals by pseudoinvertion are free of common mode.     

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.     

Multielectronic computerized EMG: technical notes on the recording and parallel off-line elaboration

A Multielectrodic EMG analysis program is developing. The purpose is to get as short as possible the main EMG parameters (amplitude, duration, frequency) of most motor units, and to reach an estimation of the anatomical extent of single units. According to the muscle extent a variable number of electrodes are inserted crosswise the fibers. EMG signals are simultaneously recorded on a multichannel AMPEX FR1300 and then off-line processed by a 21MX HP minicomputer connected with a 5Mbytes disc drive. Some technical problems had to be solved:channel amplification adjustment to avoid any difference among preamplifiers calibration and filtering, severe hum filtering of main power that is specially strong in nultielectrodic recording systems, the need of sampling at the same Nyquist time the signals of different channels. The computer is instructed to identify the "sinchronous" units i.e. the motor units recorded from more than one channel. These motor units are detected, counted and deleted from all the channels, except the one where they show the maximum amplitude. The percentage of these sinchronous units depends upon the interelectrodic distance and their anatomical area, thus it can support an evaluation of motor unit anatomical spread.     

Estimation of muscle fiber conduction velocity of doublet discharges

A doublet is defined as two consecutive discharges of a motor unit occurring at short time interval between each other (e.g., <20 ms). In this paper, we propose a method for the estimation of muscle fiber conduction velocity (CV) from two partly overlapping action potentials generated by the same motor units. The method is based on the minimization of the mean square error between time-filtered versions of two surface EMG signals recorded along the direction of muscle fibers. The minimization is performed over the filter parameters that define the two propagation delays. The method was tested on simulated and experimental signals. Simulation results showed that the method is only in some cases superior to the simpler peak approach, due to limitations in the ideal model used for the algorithm development. However, application to experimental signals that mimic doublet motor unit discharges showed a substantial improvement in estimation quality of the new method with respect to the peak method.     

Amplitude-related characteristics of motor unit and M-wave potentials during fatigue. A simulation study using literature data on intracellular potential changes found in vitro.

To realize possible reasons for changes in EMG amplitude characteristics with fatigue, we analyzed motor unit potentials (MUPs) and M-waves under simultaneous variations of the intracellular action potential (IAP) amplitude, duration, and shape as well as of the muscle fiber propagation velocity and desynchronization in activation of individual muscle fibers. Analysis was performed through computer simulation of MUPs and M-waves detected at different distances from active fibers in infinite anisotropic volume conductor. Changes in the IAP spike and negative after-potential were taken from in vitro experiments reported in the literature. It was shown that the amplitudes of MUP and M-wave detected simultaneously at different distances could decrease close to the active fibers, be almost unchanged at middle distances, and increase far from the fibers even under IAP amplitude decreasing. This reflected the distance-dependent effects of changes in the IAP profile along the fiber. Electrode position affected sensitivity of MUP and M-wave durations to changes in the IAP duration and propagation velocity. Thus, the signal area and RMS depended on electrode position and could change with fatigue in a way different from that of signal amplitude. The results can help to avoid misleading interpretation of EMG changes.     

Influence of amplitude cancellation on the accuracy of determining the onset of muscle activity from the surface electromyogram

The purpose of the study was to quantify the influence of amplitude cancellation on the accuracy of detecting the onset of muscle activity based on an analysis of simulated surface electromyographic (EMG) signals. EMG activity of a generic lower limb muscle was simulated during the stance phase of human gait. Surface EMG signals were generated with and without amplitude cancellation by summing simulated motor unit potentials either before (cancellation EMG) or after (no-cancellation EMG) the potentials had been rectified. The two sets of EMG signals were compared at forces of 30% and 80% of maximum voluntary contraction (MVC) and with various low-pass filter cut-off frequencies. Onset time was determined both visually and by an algorithm that identified when the mean amplitude of the signal within a sliding window exceeded a specified standard deviation (SD) above the baseline mean. Onset error was greater for the no-cancellation conditions when determined automatically and by visual inspection. However, the differences in onset error between the two cancellation conditions appear to be clinically insignificant. Therefore, amplitude cancellation does not appear to limit the ability to detect the onset of muscle activity from the surface EMG.     

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.     

Estimation of muscle fiber conduction velocity from two-dimensional surface EMG recordings in dynamic tasks

The aims of this study are (1) to demonstrate that multi-channel surface electromyographic (EMG) signals can be detected with negligible artifacts during fast dynamic movements with an adhesive two-dimensional (2D) grid of 64 electrodes and (2) to propose a new method for the estimation of muscle fiber conduction velocity from short epochs of 2D EMG recordings during dynamic tasks. Surface EMG signals were collected from the biceps brachii muscle of four subjects with a grid of 13 × 5 electrodes during horizontal elbow flexion/extension movements (range 120–170°) at the maximum speed, repeated cyclically for 2 min. Action potentials propagating between the innervation zone and tendon regions could be detected during the dynamic task. A maximum likelihood method for conduction velocity estimation from the 2D grid using short time intervals was developed and applied to the experimental signals. The accuracy of conduction velocity estimation, assessed from the standard deviation of the residual of the regression line with respect to time, decreased from (range) 0.20–0.33 m/s using one column to 0.02–0.15 m/s when combining five columns of the electrode grid. This novel method for estimation of muscle fiber conduction velocity from 2D EMG recordings provides an estimate which is global in space and local in time, thus representative of the entire muscle yet able to track fast changes over the execution of a task, as is required for assessing muscle properties during fast movements.     

Recent progress in the diagnostic use of surface EMG for neurological diseases.

The different techniques to measure and analyze surface EMG are summarized with an emphasis on the clinician's point of view. The application of surface EMG in neurological disease is hampered by many inherent problems, especially the difficulties in extracting features of single motor units. However, the evolution of surface EMG from single bipolar recordings via a linear array of multiple electrodes to densely packed, multi-channel electrode arrays could in principle solve this problem. The added value of using multiple channels (up to 128) with an interelectrode distance of a few millimetres to obtain more spatial information is emphasized. At least for some muscles it is now possible to extract information from the surface EMG, conventionally thought to belong to the domain of needle EMG (for example the "electrical size" of motor units). The use of analysis techniques such as the estimation of muscle fiber conduction velocity has already proven to be of diagnostic value in several myopathies characterized by a disturbed membrane function and in metabolic myopathies with abnormal fatigue profiles. Future research should be directed at the development of analysis techniques enabling the extraction of more relevant motor unit variables from surface EMG signals.     

Pulse charge and not waveform affects M-wave properties during progressive motor unit activation

The aim of this study was to investigate changes in experimentally recorded M-waves with progressive motor unit (MU) activation induced by transcutaneous electrical stimulation with different pulse waveforms. In 10 subjects, surface electromyographic signals were detected with a linear electrode array during electrically elicited contractions of the biceps brachii muscle. Three different monophasic waveforms of 304-μs duration were applied to the stimulation electrode on the main muscle motor point: triangular, square, and sinusoidal. For each waveform, increasing stimulation current intensities were applied in 10 s (frequency: 20 Hz). It was found that: (a) the degree of MU activation, as indicated by M-wave average rectified value, was a function of the injected charge and not of the stimulation waveform, and (b) MUs tended to be recruited in order of increasing conduction velocity with increasing charge of transcutaneous stimulation. Moreover, the subjects reported lower discomfort during the contractions elicited by the triangular waveform with respect to the others. Since subject tolerance to the stimulation protocol must be considered as important as MU recruitment in determining the effectiveness of neuromuscular electrical stimulation (NMES), we suggest that both charge and waveform of the stimulation pulses should be considered relevant parameters for optimizing NMES protocols.     

Detection of motor unit action potentials with surface electrodes: influence of electrode size and spacing

A model of the motor unit action potential was developed to investigate the amplitude and frequency spectrum contributions of motor units, located at various depths within muscle, to the surface detected electromyographic (EMG) signal. A dipole representation of the transmembrane current in a three-dimensional muscle volume was used to estimate detected individual muscle fiber action potentials. The effects of anisotropic muscle conductance, innervation zone location, propagation velocity, fiber length, electrode area, and electrode configuration were included in the fiber action potential model. A motor unit action potential was assumed to be the sum of the individual muscle fiber action potentials. A computational procedure, based on the notion of isopotential layers, was developed which substantially reduced the calculation time required to estimate motor unit action potentials. The simulations indicated that: 1) only those motor units with muscle fibers located within 10–12 mm of the electrodes would contribute significant signal energy to the surface EMG, 2) variation in surface area of electrodes has little effect on the detection depth of motor unit action potentials, 3) increased interelectrode spacing moderately increases detection depth, and 4) the frequency content of action potentials decreases steeply with increased electrode-motor unit territory distance.     

Motor unit number estimation and quantitative needle electromyography in stroke patients

ObjectiveTo evaluate the effect of upper motor neuron damage upon motor units’ function by means of two separate and supplementary electrophysiological methods.MethodsThe abductor digiti minimi muscle of the non-paretic and the paretic side was studied in forty-six stroke patients with (a) motor unit number estimation (MUNE) – adapted multiple point stimulation method and (b) computerized quantitative needle electromyography (EMG) assessing the configuration of voluntary recruited motor unit potentials. Main outcome comparisons were focused on differences between non-paretic and paretic side.ResultsOn the affected hands mean MUNE value was significantly lower and mean area of the surface recorded single motor unit potentials was significantly larger than the corresponding ones on the non-paretic hands. EMG findings did not reveal remarkable differences between the two sides. Neither severity nor chronicity of stroke was related to MUNE or EMG parameters.DiscussionMUNE results, which suggested reduced motor unit numbers in stroke patients, in conjunction with the normal EMG features in these same muscles has given rise to different interpretations. In a clinical setting, reinnervation type changes in the EMG similar to that occurring in neuronopathies or axonal neuropathies should not be expected in muscles with central neurogenic lesion.     

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.     

A method based on wavelets to analyse overlapped and dependant M-Waves

Implanted stimulation restores hand movement in patients with complete spinal cord injuries. However, assessing the response by surface evoked EMG recordings is challenging because the forearm muscles are small and overlapping. Moreover, M-waves are dependent because they are induced by a single stimulation paradigm. We hypothesized that the M-waves of each muscle has a specific time–frequency signature and we have developed a method to reconstruct the recruitment curves using the energy of this specific time–frequency signature. Orthogonal wavelets are used to analyze individual M-waves. As the selection of the wavelet family and the determination of the time–frequency signature were not trivial, the impact of these choices was evaluated. First, we were able to discriminate the 2 relevant M-waves related to the studied muscles thanks to their specific time–frequency representations. Second, the Meyer family, compared to the Daubechies 2 and 4 families, is the most robust choice against the uncertainty of the time–frequency region definition. Finally, the results are consistent with the semi-quantitative evaluation performed with the MRC scoring. The Meyer wavelet transform combined with the definition of a specific area of interest for each individual muscle allows us to quantitatively and objectively evaluate the evoked EMG in a robust manner.     

Comparison of algorithms for estimation of EMG variables during voluntary isometric contractions.

Many algorithms have been described in the literature for estimating amplitude, frequency variables and conduction velocity of the surface EMG signal detected during voluntary contractions. They have been used in different application areas for the non invasive assessment of muscle functions. Although many studies have focused on the comparison of different methods for information extraction from surface EMG signals, they have been carried out under different conditions and a complete comparison is not available. It is the purpose of this paper to briefly review the most frequently used algorithms for EMG variable estimation, compare them using computer generated as well as real signals and outline the advantages and drawbacks of each. In particular the paper focuses on the issue of EMG amplitude estimation with and without pre-whitening of the signal, mean and median frequency estimation with periodogram and autoregressive based algorithms both in stationary and non-stationary conditions, delay estimation for the calculation of muscle fiber conduction velocity.     

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.     

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.     

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.     

A Wavelet-Based Method to Predict Muscle Forces From Surface Electromyography Signals in Weightlifting

The purpose of this study was to develop a wavelet-based method to predict muscle forces from surface electromyography (EMG) signals in vivo.The weightlifting motor task was implemented as the case study.EMG signals of biceps brachii,triceps brachii and deltoid muscles were recorded when the subject carried out a standard weightlifting motor task.The wavelet-based algorithm was used to process raw EMG signals and extract features which could be input to the Hill-type muscle force models to predict muscle forces.At the same time,the musculoskeletal model of subject's weightlifting motor task was built and simulated using the Computed Muscle Control (CMC) method via a motion capture experiment.The results of CMC were compared with the muscle force predictions by the proposed method.The correlation coefficient between two results was 0.99(p＜0.01).However,the proposed method was easier and more efficiency than the CMC method.It has potential to be used clinically to predict muscle forces in vivo.