Simulation analysis of the ability to estimate motor unit propagation velocity non-invasively by different two-channel methods and types of multi-electrodes

Deep phenotyping of post-infectious myalgic encephalomyelitis/chronic fatigue syndrome

Post-infectious myalgic encephalomyelitis/chronic fatigue syndrome (PI-ME/CFS) is a disabling disorder, yet the clinical phenotype is poorly defined, the pathophysiology is unknown, and no disease-modifying treatments are available. We used rigorous criteria to recruit PI-ME/CFS participants with matched controls to conduct deep phenotyping. Among the many physical and cognitive complaints, one defining feature of PI-ME/CFS was an alteration of effort preference, rather than physical or central fatigue, due to dysfunction of integrative brain regions potentially associated with central catechol pathway dysregulation, with consequences on autonomic functioning and physical conditioning. Immune profiling suggested chronic antigenic stimulation with increase in naïve and decrease in switched memory B-cells. Alterations in gene expression profiles of peripheral blood mononuclear cells and metabolic pathways were consistent with cellular phenotypic studies and demonstrated differences according to sex. Together these clinical abnormalities and biomarker differences provide unique insight into the underlying pathophysiology of PI-ME/CFS, which may guide future intervention.

Peculiarities of extracellular potentials produced by deep muscles. Part 2: motor unit potentials

The potential fields generated by single fibres far from the sources are non-propagating. This suggests that there should be differences in the features of surface motor unit (MU) potentials (MUPs) detected from deep and superficial muscles. We explored the features using a simulation approach. We have shown that the non-propagating character and similar shapes among surface MUPs recorded over a wide area above deep muscles with monopolar or longitudinal single differential (LSD) electrodes are natural. Contrary to close distances, at large radial distances single differentiation did not emphasize MUP main phase relative weight. The position of the end plate area could be estimated with LSD detections only for MUs with long (123 mm) almost symmetric fibres. With short fibres, the LSD main phase was masked by the outlined terminal phases. This could be misleading in MUP analysis since the terminal phases reflect standing sources. The highly asymmetric fibres could yield peculiar MUP shapes resembling MUPs of two distinct MUs. We have shown that the relative weight of terminal phases at large fibre-electrode distance decreases under abnormal peripheral conditions. However, the changes in membrane depolarization due to fatigue or pathology could be assessed non-invasively also from deep muscles.

Wavelet based correlation and coherence analysis reveals frequency dependent motor unit conduction velocity of the abductor pollicis brevis muscle

The purpose of this study was to investigate the motorunit conduction velocity (CV) as a function of frequency. A wavelet based correlation and coherence analysis was introduced to measure CV as a function of frequency. Based on the most simple assumption that the power spectra of the motor unit action potential is shifted to higher frequencies with increasing CV, we hypothesized that there would be a monotonic or linear trend of increasing CV with frequency. This trend was only confirmed at higher frequencies. At lower frequencies the trend was often reversed leading to a decrease in CV with increasing frequency. Thus the CV was high at low frequencies, went through a minimum at about 170 Hz and increased at higher frequencies, as expected. The observed CV at low frequencies could not be fully explained by assuming non-propagating signals or variable groups of motor units. We concluded that spectra and CV contain partly independent information about the muscles and that the wavelet based method provides the tools to measure them both simultaneously.

A simulation study for a surface EMG sensor that detects distinguishable motor unit action potentials

An advanced volume conductor model was used to simulate the surface-detected motor unit action potentials (MUAPs) due to current sources located at different depths within the muscle tissue of the biceps brachii. Seven different spatial filters were investigated by linear summation of the monopolarly detected surface MUAPs on a square array of nine electrodes. The criterion of the relative energy-of-difference (EOD) between the MUAPs was used to rank spatial filters for their ability to distinguish two motor units located at different depths. Using the same criterion pair wise combinations of spatial filters were ranked for their ability to generate different MUAP shape representations of the same motor unit. In both analyses, the bi-transversal double-differential (BiTDD) configurations and pair wise combinations involving a BiTDD configuration consistently ranked highest. Varying electrode spacing did not change the results in a relevant way. Based on the EOD calculations, a four-channel detection system using all available electrodes of the array is proposed. The implications of using only six electrodes, effectively reducing contact area of the sensor in half, are discussed.

Estimation of average muscle fiber conduction velocity from simulated surface EMG in pinnate muscles

The aim of this simulation study was to assess the bias in estimating muscle fiber conduction velocity (CV) from surface electromyographic (EMG) signals in muscles with one and two pinnation angles. The volume conductor was a layered medium simulating anisotropic muscle tissue and isotropic homogeneous subcutaneous tissue. The muscle tissue was homogeneous for one pinnation angle and inhomogeneous for bipinnate muscles (two fiber directions). Interference EMG signals were obtained by simulating recruitment thresholds and discharge patterns of a set of 100 and 200 motor units for the pinnate and bipinnate muscle, respectively (15 degrees pinnation angel in both cases). Without subcutaneous layer and muscle fibers with CV 4m/s, average CV estimates from the pinnate (bipinnate) muscle were 4.81+/-0.18 m/s (4.80+/-0.18 m/s) for bipolar, 4.71+/-0.19 m/s (4.71+/-0.12 m/s) for double differential, and 4.78+/-0.16 m/s (4.79+/-0.15m/s) for Laplacian recordings. When subcutaneous layer was added (thickness 1mm) in the same conditions, estimated CV values were 4.93+/-0.25 m/s (5.16+/-0.41 m/s), 4.70+/-0.21 m/s (4.83+/-0.33 m/s), and 4.89+/-0.21 m/s (4.99+/-0.39 m/s), for the three recording systems, respectively. The main factor biasing CV estimates was the propagation of action potentials in the two directions which influenced the recording due to the scatter of the projection of end-plate and tendon locations along the fiber direction, as a consequence of pinnation. The same problem arises in muscles with the line of innervation zone locations not perpendicular to fiber direction. These results indicate an important limitation in reliability of CV estimates from the interference EMG when the innervation zone and tendon locations are not distributed perpendicular to fiber direction.

Simulation of Surface EMG Signals for a Multilayer Volume Conductor With Triangular Model of the Muscle Tissue

This study analytically describes surface electromyogram (sEMG) signals generated by a model of a triangular muscle, i.e., a muscle with fibers arranged in a fan shape. Examples of triangular muscles in the human body are the deltoid, the pectoralis major, the trapezius, the adductor pollicis. A model of triangular muscle is proposed. It is a sector of a cylindrical volume conductor (with the fibers directed along the radial coordinate) bounded at the muscle/fat interface. The muscle conductivity tensor reflects the fan anisotropy. Edge effects have been neglected. A solution of the nonspace invariant problem for a triangular muscle is provided in the Fourier domain. An approximate analytical solution for a two plane layer volume conductor model is obtained by introducing a homogeneous layer (modeling the fat) over the triangular muscle. The results are implemented in a complete sEMG generation model (including the finite length of the fibers), simulating single fiber action potentials. The model is not space invariant due to the changes of the volume conductor along the direction of action potential propagation. Thus the detected potentials at the skin surface change shape as they propagate. This determines problems in the extraction and interpretation of parameters. As a representative example of application of the simulation model, the influence of the inhomogeneity of the volume conductor in conduction velocity (CV) estimation is addressed (for two channels; maximum likelihood and reference point methods). Different fiber depths, electrode placements and small misalignments of the detection system with respect to the fiber have been simulated. The error in CV estimation is large when the depth of the fiber increases, when the detection system is not aligned with the fiber and close to the innervation point and to the tendons.

Estimation of Motor Unit Conduction Velocity From Surface EMG Recordings by Signal-Based Selection of the Spatial Filters

Muscle fiber conduction velocity (CV) can be estimated by the application of a pair of spatial filters to surface electromagnetic (EMG) signals and compensation of the spatial filter transfer function with equivalent temporal filters. This method integrates the selection of the spatial filters for signal detection to the estimation of CV. Using this approach, in this paper, we propose a novel technique for signal-based selection of the spatial filter pair that minimizes the effect of nonpropagating signal components (end-of-fiber effects) on CV estimates (optimal filters). The technique is applicable to signals with one propagating and one nonpropagating component, such as single motor unit action potentials. It is shown that the determination of the optimal filters also allows the identification of the propagating and nonpropagating signal components. The new method was applied to simulated and experimental EMG signals. Simulated signals were generated by a cylindrical, layered volume conductor model. Experimental signals were recorded from the abductor pollicis brevis with a linear array of 16 electrodes. In the simulations, the proposed approach provided CV estimates with lower bias due to nonpropagating signal components than previously proposed methods based on the entire signal waveform. In the experimental signals, the technique separated propagating and nonpropagating signal components with an average reconstruction error of 2.9 +/- 0.9% of the signal energy. The technique may find application in single motor unit studies for decreasing the variability and bias of CV estimates due to the presence and different weights of the nonpropagating components.

Estimate of M-wave changes in human biceps brachii during continuous stimulation

The purpose of the present study was to validate the capability of new fatigue indexes (in the time and frequency domain) applied to experimental recordings and thus, to test some assumptions made in previous simulations. The indexes were applied to M-waves detected non-invasively from human m.biceps brachii during repetitive slightly above threshold stimulations. It was found that distance between the motor point and middle of the end-plate region could be relatively large. Under identical conditions (signals detected by monopolar electrodes and high-pass filtered at 1 Hz), the relative changes of the indexes obtained in electrophysiological experiments and simulations were similar. Changes of the intracellular action potential profile during fatigue used in the simulations were consequently supposed to be close to the actual ones for the muscle analyzed. When the high-pass cut-off frequency was higher than 1 Hz, the sensitivity of the index in the time domain was higher, while that in the frequency domain was lower. If the normalizing spectral moment was of higher order, the sensitivity of the spectral index could be even 150-times greater than that of the fatigue indexes traditionally used. Thus, the spectral index promises high capability to assess fatigue during functional electrical stimulation.

Experimental muscle pain changes motor control strategies in dynamic contractions

This study investigated the effect of muscle pain on muscle activation strategies during dynamic exercises. Ten healthy volunteers performed cyclic elbow flexion/extension movements at maximum speed for 2 min after injection of (1) hypertonic (painful) saline in the biceps brachii, (2) hypertonic saline in both biceps brachii and triceps brachii, and (3) isotonic (nonpainful) saline in the biceps brachii muscle. Surface electromyographic (EMG) signals were collected from the upper trapezius, biceps brachii, triceps brachii, and brachioradialis muscles (to estimate EMG amplitude) and with an electrode arrays from biceps brachii (to estimate muscle fiber conduction velocity [CV]). In all conditions, the acceleration of the movement decreased throughout the exercise, and kinematic parameters were not altered by pain. With respect to the control condition, pain induced a decrease of the biceps brachii (mean +/- SE, -23+/-4%) and brachioradialis (-10+/-0.4%) integrated EMG (IEMG) in the beginning of the exercise, and an increase (45+/-3.5%) of the upper trapezius IEMG at all time points during the exercise. The biceps brachii IEMG decreased over time during the nonpainful exercises (-11+/-0.6%) while it remained constant in the painful condition. Biceps brachii CV decreased during painful conditions (-12.8+/-2.2%) while it remained constant during the nonpainful condition. In conclusion, muscle pain changes the motor control strategy to sustain the required dynamic task both in the relative contribution between synergistic muscles and in the motor unit activation within the painful muscle. Such a changed motor strategy may be highly relevant in models of occupational musculoskeletal pain conditions.

Estimation of the muscle fibre semi-length under varying joint positions on the basis of non-invasively extracted motor unit action potentials

Changes in muscle fibre length and surface electrode position with respect to the muscle fibres affect the amplitude and frequency characteristics of surface electromyography (SEMG) in different ways. Knowledge of changes in muscle fibre length would help towards a better interpretation of the signals. The possibility of estimating the length through SEMG during voluntary contractions was checked in this study. The fibres' semi-length was estimated from the product of the conduction velocity and conduction time during which the wave of excitation propagated from the end-plate region to the ends of the fibres. Short (10 s), moderate (30% of maximum voluntary contraction) isometric contractions were performed by 10 subjects at different elbow joint angles (80-140 degrees in steps of 20 degrees ). Monopolar signals were detected non-invasively, using a two-dimensional electrode array. High spatial resolution EMG and a decomposition technique were utilised to extract single motor unit activities for triggered averaging and to estimate conduction velocity. A significant increase with joint angle was found in conduction time and estimated fibre semi-length. Changes in conduction velocity with joint angle were found to be not significant. The methodology described allows the relative changes in fibres' semi-length to be estimated from SEMG data.

Sensitivity of surface EMG-based conduction velocity estimates to local tissue in-homogeneities – influence of the number of channels and inter-channel distance

The aim of this simulation study was to investigate the influence of local tissue in-homogeneities on the estimates of muscle fiber conduction velocity (CV) from surface EMG signals. A recently developed analytical surface EMG model was used to generate simulated surface EMG signals from a planar layered volume conductor, comprised of the muscle tissue and fat layer, with spheres (1 mm radius) in the fat layer of conductivity different from the surrounding tissue. CV was estimated with a maximum likelihood multi-channel approach, varying the number of channels and the inter-channel distance used for the estimate. The action potentials detected along the muscle fiber direction changed shape due to the presence of the in-homogeneities, thus affecting CV estimates. CV estimates were influenced by the location of the in-homogeneities with respect to the fiber and detection electrodes. The maximum percent variation of CV estimates due to the presence of in-homogeneities decreased with increasing number of channels and inter-channel distance: 19.6% (2 channels), 12.1% (3 channels), 6.4% (4 channels), for 5 mm inter-channel distance, and 12.0% (2 channels), 5.2% (3 channels), 2.4% (4 channels), for 10 mm inter-channel distance (for double differential detection). The results were in agreement and explained previous experimental findings. It was concluded that multi-channel methods for CV estimation significantly reduce the sensitivity of CV estimates to tissue in-homogeneities.

Surface electromyogram signal modelling

The paper reviews the fundamental components of stochastic and motor-unit-based models of the surface electromyogram (SEMG). Stochastic models used in ergonomics and kinesiology consider the SEMG to be a stochastic process whose amplitude is related to the level of muscle activation and whose power spectral density reflects muscle conduction velocity. Motor-unit-based models for describing the spatio-temporal distribution of individual motor-unit action potentials throughout the limb are quite robust, making it possible to extract precise information about motor-unit architecture from SEMG signals recorded by multi-electrode arrays. Motor-unit-based models have not yet been proven as successful, however, for extracting information about recruitment and firing rates throughout the full range of contraction. The relationship between SEMG and force during natural dynamic movements is much too complex to model in terms of single motor units.

Methods for estimating muscle fibre conduction velocity from surface electromyographic signals

The review focuses on the methods currently available for estimating muscle fibre conduction velocity (CV) from surface electromyographic (EMG) signals. The basic concepts behind the issue of estimating CV from EMG signals are discussed. As the action potentials detected at the skin surface along the muscle fibres are, in practice, not equal in shape, the estimation of the delay of propagation (and thus of CV) is not a trivial task. Indeed, a strictly unique definition of delay does not apply in these cases. Methods for estimating CV can thus be seen as corresponding to specific definitions of the delay of propagation between signals of unequal shape. The most commonly used methods for CV estimation are then reviewed. Together with classic methods, recent approaches are presented. The techniques are described with common notations to underline their relationships and to highlight when an approach is a generalisation of a previous one or when it is based on new concepts. The review identifies the difficulties of CV estimation and underlines the issues that should be considered by the investigator when selecting a particular method and detection system for assessing muscle fibre CV. The many open issues in CV estimation are also presented.

Influence of muscle fibre shortening on estimates of conduction velocity and spectral frequencies from surface electromyographic signals

The study of surface electromyographic (EMG) signals under dynamic contractions is becoming increasingly important. However, knowledge of the methodological issues that may affect such analysis is still limited. The aim of the study was to analyse the effect of fibre shortening on estimates of conduction velocity (CV) and mean power spectral frequency (MNF) from surface EMG signals. Single fibre action potentials were simulated, as detected by commonly used spatial filters, for different fibre lengths. No physiological modifications were included with changes in fibre length, and thus only geometrical artifacts related to fibre shortening were investigated. The simulation results showed that the dependence of CV and MNF on fibre shortening is affected by the fibre location, electrode position and the spatial filter applied. With shortening of up to 50% for a fibre of 50 mm semi-length, the variations in CV and MNF estimates with shortening in bipolar recordings were 0.5% (CV) and 0.7% (MNF) for superficial fibres, and 3.6% and 5.1% for deeper fibres. Using the longitudinal double differential filter, under the same conditions, the percent variation was 0% and 0.2%, and 24.7% and 15.8%, respectively. The main conclusions were, first, muscle fibre shortening can significantly affect estimates of CV and MNF, especially for short fibre lengths. However, for long (semi-length >50 mm) and superficial fibres, this effect is limited for shortenings of up to 50% of the initial fibre length. Secondly, CV and MNF are almost equally affected by changes in muscle length; and, thirdly, sensitivity to fibre shortening depends on the spatial filter applied for signal detection.

The cross-correlation and phase-difference methods are not equivalent under noninvasive estimation of the motor unit propagation velocity

Noninvasive estimation of motor unit propagation velocity (MUPV) was reduced to that of the time delay between signals detected by two surface EMG electrodes placed along the muscle fibres. When the cross-correlation function between the signals was used, the problem with temporal resolution arose. Estimation of the time delay in the frequency domain was proposed to overcome this problem. To check whether the cross-correlation and phase-difference methods give the same estimates, the results obtained by both methods were compared through simulation. A different sensitivity of the two methods to the effects of the excitation origin and extinction was found. Besides, the quality of the estimate depended on the electrode arrangement. The longitudinal double difference electrodes were preferable with the phase-difference method, while the MUPV estimates obtained by the cross-correlation technique were more correct when the longitudinal single difference or bipolar transversal double difference electrodes were used. In addition, the estimates obtained by the phase-difference method were more sensitive to the longitudinal scattering of motor end-plates and ends of the fibres, to the fibre lengths and to the negative after-potential magnitude. Such sensitivity could make MUPV estimates incorrect even under a relatively small distance between the motor unit axis and electrode.

Estimation of average muscle fiber conduction velocity from two-dimensional surface EMG recordings

We propose a novel method for the estimation of muscle fiber conduction velocity (CV) from surface EMG recordings. The approach is based on the analysis of signals detected along a number of linear electrode arrays parallel to the fiber direction, thus collected by a bi-dimensional (2-D) array (matrix) of electrodes. The information provided by the 2-D array is used to derive a maximum likelihood estimator which can be applied to any number of signals and which may account for missing channels in the matrix. An iterative technique in the frequency domain for the estimation of the propagation delay is proposed to reduce the computational time and avoid the limit of resolution due to signal sampling. The method proposed is applied to signals collected from the biceps brachii muscle of eight healthy subjects during isometric, constant force contractions at 50% of the maximal voluntary contraction torque. It is shown that CV estimation standard deviation and sensitivity to electrode displacements significantly decrease by the application of the method proposed with respect to classic CV estimation techniques. The method promises to be a useful tool when average CV is estimated for muscle assessment and diagnostic purposes.