Simulation techniques in electromyography

Volume conduction: Extracellular waveform generation in theory and practice

The extracellular waveform manifestations of the intracellular action potential are the quintessential diagnostic foundation of electrodiagnostic medicine, and clinical neurophysiology in general. Volume conduction is the extracellular current flow and associated voltage distributions in an ionic conducting media, such as occurs in the human body. Both surface and intramuscular electrodes, in association with contemporary digital electromyographic systems, permit very sensitive detection and visualization of this extracellular spontaneous, voluntary, and evoked nerve/muscle electrical activity. Waveform configuration, with its associated discharge rate/rhythm, permits the identification of normal and abnormal waveforms, thereby assisting in the diagnosis of nerve and muscle pathology. This monograph utilizes a simple model to explain the various waveforms that may be encountered. There are a limited number of waveforms capable of being generated in excitable tissues which conform to well-known volume conductor concepts. Using these principles, such waveforms can be quickly identified in real time during clinical studies.

Neural decoding from surface high-density EMG signals: influence of anatomy and synchronization on the number of identified motor units

OBJECTIVE

High-density surface electromyography (HD-sEMG) allows the reliable identification of individual motor unit (MU) action potentials. Despite the accuracy in decomposition, there is a large variability in the number of identified MUs across individuals and exerted forces. Here we present a systematic investigation of the anatomical and neural factors that determine this variability.

APPROACH

We investigated factors of influence on HD-sEMG decomposition, such as synchronization of MU discharges, distribution of MU territories, muscle-electrode distance (MED - subcutaneous adipose tissue thickness), maximum anatomical cross-sectional area (ACSA_max), and fiber CSA. For this purpose, we recorded HD-sEMG signals, ultrasound and, magnetic resonance images, and took a muscle biopsy from the biceps brachii muscle from 30 male participants drawn from two groups to ensure variability within the factors - untrained-controls (UT=14) and strength-trained individuals (ST=16). Participants performed isometric ramp contractions with elbow flexors (at 15, 35, 50 and 70% maximum voluntary torque - MVT). We assessed the correlation between the number of accurately detected MUs by HD-sEMG decomposition and each measured parameter, for each target force level. Multiple regression analysis was then applied.

MAIN RESULTS

ST subjects showed lower MED (UT=5.1±1.4 mm; ST=3.8±0.8 mm) and a greater number of identified motor units (UT:21.3±10.2 vs ST:29.2±11.8 MUs/subject across all force levels). The entire cohort showed a negative correlation between MED and the number of identified MUs at low forces (r= -0.6, p=0.002 at 15%MVT). Moreover, the number of identified MUs was positively correlated to the distribution of MU territories (r=0.56, p=0.01) and ACSA_max(r=0.48, p=0.03) at 15%MVT. By accounting for all anatomical parameters, we were able to partly predict the number of decomposed MUs at low but not at high forces.

SIGNIFICANCE

Our results confirmed the influence of subcutaneous tissue on the quality of HD-sEMG signals and demonstrated that MU spatial distribution and ACSA_maxare also relevant parameters of influence for current decomposition algorithms.

Muscle Fiber Diameter and Density Alterations after Stroke Examined by Single-Fiber EMG

This study presents single-fiber electromyography (EMG) analysis for assessment of paretic muscle changes after stroke. Single-fiber action potentials (SFAPs) were recorded from the first dorsal interosseous (FDI) muscle bilaterally in 12 individuals with hemiparetic stroke. The SFAP parameters, including the negative peak duration and the peak-peak amplitude, were measured and further used to estimate muscle fiber diameter through a model based on the quadratic function. The SFAP parameters, fiber density, and muscle fiber diameter derived from the model were compared between the paretic and contralateral muscles. The results show that SFAPs recorded from the paretic muscle had significantly smaller negative peak duration than that from the contralateral muscle. As a result, the derived muscle fiber diameter of the paretic muscle was significantly smaller than that of the contralateral muscle. The fiber density of the paretic muscle was significantly higher than that of the contralateral muscle. These results provide further evidence of remodeled motor units after stroke and suggest that paretic muscle weakness can be due to both complex central and peripheral neuromuscular alterations.

Reproducibility of muscle fibre conduction velocity during linearly increasing force contractions

Muscle fibre conduction velocity (MFCV) is a basic physiological parameter biophysically related to the diameter of muscle fibres and properties of the sarcolemma. The aim of this study was to assess the intersession reproducibility of the relation between voluntary force and estimates of average muscle fibre conduction velocity (MFCV) from multichannel high-density surface electromyographic recordings (HDsEMG). Ten healthy men performed six linearly increasing isometric ankle dorsiflexions on two separate experimental sessions, 4 weeks apart. Each session involved the recordings of voluntary force during maximal isometric (MViF) and submaximal ramp contractions at 35-50-70% of MViF. Concurrently, the HDsEMG activity was detected from the tibialis anterior muscle and MFCV estimates were derived in 250-ms epochs. Absolute and relative reproducibility of MFCV initial value (intercept) and rate of change (regression slope) as a function of force were assessed by within-subject coefficient of correlation (CV_w) and with intraclass correlation coefficient (ICC). MFCV was positively correlated with voluntary force (R² = 0.75 ± 0.12) in all individuals and test conditions (P < 0.001). Average CV_w for MFCV intercept and slope were of 2.6 ± 2.0% and 11.9 ± 3.2% and ICC values of 0.96 and 0.94, respectively. Overall, MFCV regression coefficients showed a high degree of intersession reproducibility in both absolute and relative terms. These results may have important practical implications in the tracking of training-induced neuromuscular changes and/or in the monitoring of the progress of neuromuscular disorders when a full sEMG signal decomposition is problematic or not possible.

Methodology of surface electromyography in gait analysis: review of the literature

Gait analysis is a significant diagnostic procedure for the clinicians who manage musculoskeletal disorders. Surface electromyography (sEMG) combined with kinematic and kinetic data is a useful tool for decision making of the appropriate method needed to treat such patients. sEMG has been used for decades to evaluate neuromuscular responses during a range of activities and develop rehabilitation protocols. The sEMG methodology followed by researchers assessed the issues of noise control, wave frequency, cross talk, low signal reception, muscle co-contraction, electrode placement protocol and procedure as well as EMG signal timing, intensity and normalisation so as to collect accurate, adequate and meaningful data. Further research should be done to provide more information related to the muscle activity recorded by sEMG and the force produced by the corresponding muscle during gait analysis.

A new approach for multi-channel surface EMG signal simulation

Simulation models are necessary for testing the performance of newly developed approaches before they can be applied to interpreting experimental data, especially when biomedical signals such as surface electromyogram (SEMG) signals are involved. A new and easily implementable surface EMG simulation model was developed in this study to simulate multi-channel SEMG signals. A single fiber action potential (SFAP) is represented by the sum of three Gaussian functions. SFAP waveforms can be modified by adjusting the amplitude and bandwidth of the Gaussian functions. SEMG signals were successfully simulated at different detected locations. Effects of the fiber depth, electrode position and conduction velocity of SFAP on motor unit action potential (MUAP) were illustrated. Results demonstrate that the easily implementable SEMG simulation approach developed in this study can be used to effectively simulate SEMG signals.

A method for determination of muscle fiber diameter using single fiber potential (SFP) analysis

We have used computer simulation to study the relationship between the muscle fiber diameter and parameters: peak-to-peak amplitude and duration of the negative peak of the muscle fiber action potential. We found that the negative peak duration is useful in the determination of fiber diameter via the diameter dependence of conduction velocity. We have shown a direct link between the underlying physiology and the measurements characterizing single fiber potential. Using data from simulations, a graphical tool and an analytical method to estimate the muscle fiber diameter from the recorded action potential has been developed. The ability to quantify the fiber diameter can add significantly to the single fiber electromyography examination. It may help study of muscle fiber diameter variability and thus compliment the muscle biopsy studies.

Simulation analysis of interference EMG during fatiguing voluntary contractions. Part I: What do the intramuscular spike amplitude–frequency histograms reflect?

Decline in amplitude of EMG signals and in the rate of counts of intramuscularly recorded spikes during fatigue is often attributed to a progressive reduction of the neural drive only. As a rule, alterations in intracellular action potential (IAP) are not taken into account. To test correctness of the hypothesis, the effect of various discharge frequency patterns as well as changes in IAP shape and muscle fibre propagation velocity (MFPV) on the spike amplitude-frequency histogram of intramuscular interference EMG signals were simulated and analyzed. It was assumed that muscle was composed of four types of motor units (MUs): slow-twitch fatigue resistant, fast-twitch fatigue resistant, fast intermediate, and fast fatigable. MFPV and IAP duration at initial stage before fatigue as well as their changes differed for individual MU types. Fatigability of individual MU types in normal conditions as well as in the case of ischaemic or low oxygen conditions due to restricted blood flow was also taken into account. It was found that spike amplitude-frequency histogram is poorly sensitive to MU firing frequency, while it is highly sensitive to IAP profile lengthening. It is concluded that spike amplitude-frequency analysis can hardly provide a correct measure of MU rate-coding pattern during fatigue.

Modelling the passive and nerve activated response of the rectus femoris muscle to a flexion loading: a finite element framework

A muscle modelling framework is presented which relates the mechanical response of the rectus femoris muscle (at the organ level) to tissue level properties, with the capability of linking to the cellular level as part of the IUPS Physiome Project. This paper will outline our current approach to muscle modelling incorporating micro-structural passive and active properties including fibre orientations and nerve innervation. The technique is based on finite deformation (using FE analysis) coupled to electrical nerve initiated muscle activation, and we present the influence of active tension through an eccentric contraction at specific flexion angles. Finally we discuss the future goals of incorporating cell mechanics and validating at the organ level to provide a complete diagnostic tool with the ability to relate mechanisms of failure across spatial scales.

A simulation model of the surface EMG signal for analysis of muscle activity during the gait cycle

This work describes a model able to synthetize the surface EMG (electromyography) signal acquired from tibialis anterior and gastrocnemious medialis muscles during walking of asymptomatic adult subjects. The model assumes a muscle structure where the volume conductor is represented by multiple layers of anisotropic media. This model originates from analysis of the single fiber action potential characterized by the conduction velocity. The surface EMG of voluntary contraction is calculated by gathering motor unit action potentials estimated by the summation of all activities of muscle fibers assumed to have a uniformly parallel distribution. The parameters related to the gait cycle, such as onset and cessation timings of muscle activation, amplitude of muscle contraction, periods and sequences of motor units' recruitment, are included in the model presented. In addition, the relative positions of the electrodes during gait can also be specified in order to adapt the simulation to the different acquisition settings.

Physiologically based simulation of clinical EMG signals

An algorithm that generates electromyographic (EMG) signals consistent with those acquired in a clinical setting is described. Signals are generated using a model constructed to closely resemble the physiology and morphology of skeletal muscle, combined with line source models of commonly used needle electrodes positioned in a way consistent with clinical studies. The validity of the simulation routines is demonstrated by comparing values of statistics calculated from simulated signals with those from clinical EMG studies of normal subjects. The simulated EMG signals may be used to explore the relationships between muscle structure and activation and clinically acquired EMG signals. The effects of motor unit (MU) morphology, activation, and neuromuscular junction activity on acquired signals can be analyzed at the fiber, MU and muscle level. Relationships between quantitative features of EMG signals and muscle structure and activation are discussed.

Novel Ideas for Fast Muscle Action Potential Simulations Using the Line Source Model

Using a signal processing approach, we analyze the line source model for muscle action potential (AP) modeling. We show that the original model presents a tradeoff between violating the Nyquist criterion on one hand and using a discretization frequency that is unnecessarily high with respect to the bandwidth of the generated AP on the other. Here, we present an improved line source model that, compared to the original, allows a lower discretization frequency while retaining the accuracy by simply introducing a continuous-time anti-aliasing filter. Moreover, a transfer function form of the transmembrane current is presented that promote the use of sophisticated signal processing methods on these type of signals. Both continuous-time and discrete-time models are presented. We also address and analyze the implications of the finite length of the muscle fibers. Including this in the model is straightforward, owing to the convolutional form of the line source model, and is manifested by a simple transformation of the associated weighting function. AP modeling is discussed for the three different electrode models: the concentric needle electrode, the single fiber electrode, and the macro electrode. The presented model is suitable for modeling large motor units, where both accuracy and computational efficiency are important factors. To simplify the selection of the discretization interval, we derive what we call the cumulative cutoff frequency that provides an estimate of the required Nyquist frequency.

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.

An application of a muscle model to study electromyographic signals

A simulation program for research and teaching electromyography (EMG) has been developed. It has a great number of parameters that may be optionally changed in simulations of normal and diseased muscle. The simulator is user-friendly and fast and can actually be run without much help from the manual. It is easy to introduce new motor units (MU), to change MU and individual muscle fibre parameters, to insert an EMG electrode and to change its position. The model allows simulation of the most common pathological situations. The resulting signals are displayed in a conventional form. The generated EMG signals obtained with the three electrodes that have been used so far are reasonably similar to the signals obtained in real recordings. A few shortcomings in simulating, e.g. end plate zone and abnormal volume conduction characteristics do not seem to influence the principal results. The simulator can, therefore, be used in teaching and even for research.

A model of the muscle action potential for describing the leading edge, terminal wave, and slow afterwave

The leading edge, terminal wave, and slow afterwave of the motor-unit action potential (MUAP) are produced by changes in the strength of electrical sources in the muscle fibers rather than by movement of sources. The latencies and shapes of these features are, therefore, determined primarily by the motor-unit (MU) architecture and the intracellular action potential (IAP), rather than by the volume-conduction characteristics of the limb. We present a simple model to explain these relationships. The MUAP is modeled as the convolution of a source function related to the IAP and a weighting function related to the MU architecture. The IAP waveform is modeled as the sum of a spike and a slow repolarization phase. The MU architecture is modeled by assuming that the individual fibers lie along a single equivalent axis but that their action potentials have dispersed initiation and termination times. The model is illustrated by simulating experimentally recorded MUAPs and compound muscle action potentials.

EMG-interference pattern analysis

The EMG interference pattern, built up of single motor unit action potentials, may be analyzed subjectively, or objectively by computer aided, quantitative methods, like counting of zero-crossings, counting of spikes, amplitude measurements, integration of the area under the curve, decomposition techniques, power spectrum analysis and turn/amplitude analysis. Since the shape of the interference pattern of healthy muscles is dependent on age, sex, force, muscle, temperature, fatigue, fitness level, recording site and surrounding tissue, electrode type, sensitivity, filters, sampling frequency and threshold level, all methods of analyzing the IP have to be standardized. Quantitative methods of analyzing the EMG interference pattern may be used for monitoring botulinum toxin therapy of dystonia and spasticity, quantifying spontaneous activity, assessment of chronic muscle pain, neuro-urological and proctological function, and diagnosing neuromuscular disorders. For diagnostic purposes, the methods favored are those that use needle electrodes and do not require measurement or monitoring of muscle force. The most well-evaluated methods are those using turn/amplitude analysis, like the cloud methods and the peak-ratio analysis. Peak-ratio analysis has the advantage that reference limits are easy to obtain and that its utility is well established and confirmed by several investigations. Overall, automatic methods of EMG interference pattern analysis are powerful tools for diagnostic and non-diagnostic purposes.

EMG signal decomposition: how can it be accomplished and used?

Electromyographic (EMG) signals are composed of the superposition of the activity of individual motor units. Techniques exist for the decomposition of an EMG signal into its constituent components. Following is a review and explanation of the techniques that have been used to decompose EMG signals. Before describing the decomposition techniques, the fundamental composition of EMG signals is explained and after, potential sources of information from and various uses of decomposed EMG signals are described.

Calculation of spatially filtered signals produced by a motor unit comprising muscle fibres with non-uniform propagation

Simulation of actual muscle potentials is necessary to understand processes that underlie changes in electromyographic signals. The work reported aims to analyse existing methods and suggest new ways of calculating precisely the signals (MUS) detected by a multielectrode from motor units (MUs) consisting of homogeneous or inhomogeneous (functionally and geometrically) fibres. Simulation (based on cable equations) of intracellular action potential (IAP) in a muscle fibre with a moderate geometrical inhomogeneity demonstrates that considerable changes in propagation velocity (more than 3.5 times) are accompanied by insignificant changes in the IAP amplitude (< 5%) and IAP shape in the temporal domain. MUS can therefore be considered as the output signal of a timeshift-invariant system whose input signal is the first temporal derivative of the IAP. As a result, calculation of MUS is reduced to a single convolution in the case of muscle composed of both homogeneous and inhomogeneous fibres. The suggested approach is valid for simulation of recordings obtained with points or rectangular plates leading off surfaces from muscles consisting of fibres that are parallel or inclined to the skin surface. The MUS terminal phases are prolonged because of fibre inhomogeneities. The presence of geometrical inhomogeneities results in additional positive-negative phases in MUS.

A model for the generation of synthetic intramuscular EMG signals to test decomposition algorithms

As more and more intramuscular electromyogram (EMG) decomposition programs are being developed, there is a growing need for evaluating and comparing their performances. One way to achieve this goal is to generate synthetic EMG signals having known features. Features of interest are: the number of channels acquired (number of detection surfaces), the number of detected motor unit action potential (MUAP) trains, their time-varying firing rates, the degree of shape similarity among MUAPs belonging to the same motor unit (MU) or to different MUs, the degree of MUAP superposition, the MU activation intervals, the amount and type of additive noise. A model is proposed to generate one or more channels of intramuscular EMG starting from a library of real MUAPs represented in a 16-dimensional space using their Associated Hermite expansion. The MUAP shapes, regularity of repetition rate, degree of superposition, activation intervals, etc. may be time variable and are described quantitatively by a number of parameters which define a stochastic process (the model) with known statistical features. The desired amount of noise may be added to the synthetic signal which may then be processed by the decomposition algorithm under test to evaluate its capability of recovering the signal features.

Surface EMG models: properties and applications

After a general introduction on the kind of models and the use of models in the natural sciences, the main body of this paper reviews potential properties of structure based surface EMG (sEMG) models. The specific peculiarities of the categories (i) source description, (ii) motor unit structure, (iii) volume conduction, (iv) recording configurations and (v) recruitment and firing behaviour are discussed. For a specific goal, not all aspects conceivable have to be part of a model description. Therefore, finally an attempt is made to integrate the 'question level' and the 'model property level' in a matrix providing direction to the development and application of sEMG models with different characteristics and varying complexity. From this overview it appears that the least complex are models describing how the morphological muscle features are reflected in multi-channel EMG measurements. The most challenging questions in terms of model complexity are related to supporting the diagnosis of neuromuscular disorders.

Motor unit sound in needle electromyography: assessing normal and neuropathic units

Motor unit action potentials (MUPs) recorded by a monopolar needle electrode in normal and neuropathic muscles were computer-simulated. Five experienced electromyographers acted as examiners and assessed the firing sounds of these MUPs without seeing them on a display monitor. They judged whether the sounds were crisp or close enough to accept for the evaluation of MUP parameters and whether, when judged acceptable, they were neuropathic-polyphasic. The examiners recognized motor unit (MU) sound as crisp or polyphasic when the MUP obtained was 0.15-0.2 mm from the edge of the MU territory. When the intensity of the sound decreased, they were unable to perceive it as crisp. When the intensity exceeded the saturation level of loudspeaker output, the sound was perceived as polyphasic, but the wave form of the MUP was not. When the frequency of the neuropathic MUP was lowered, the examiners were unable to determine whether the MUP was polyphasic. MUPs recognized as acceptable for evaluation can be distinguished by listening to MU sounds. The audio amplifier gain must be appropriately adjusted for each MUP amplitude in order to assess whether an individual MU sound is crisp or polyphasic before MUP parameters are measured on a display monitor.

A model of EMG generation

Simulation models are unavoidable in experimental research when the point is to develop new processing algorithms to be applied on real signals in order to extract specific parameter values. Such algorithms have generally to be optimized by comparing true parameter values to those deduced from the algorithm. Only a simulation model can allow the user to access and control the actual process parameter values. This constraint is especially true when dealing with biomedical signals like surface electromyogram (SEMG). This work is an attempt to produce an efficient SEMG simulation model as a help for assessing algorithms related to SEMG features description. It takes into account the most important parameters which could influence these characteristics. This model includes all transformations from intracellular potential to surface recordings as well as a fast implementation of the extracellular potential computation. In addition, this model allows multiple graphically-programmable electrode-set configurations and SEMG simulation in both voluntary and elicited contractions.

The size index as a motor unit identifier in electromyography examined by numerical calculation

A computer simulation was performed to investigate the size index as a motor unit identifier in electromyography. The size index calculated from the amplitude and area of the simulated motor unit action potential (MUP) was plotted against the distance between the needle electrode and current source to show how the index changes as a function of the distance. The index of the MUP also was plotted against the number of muscle fibers belonging to a single motor unit, the size of the motor unit territory, and the diameter of the muscle fibers in order to establish the major determinants of the index. The index was relatively constant for the distance less than 2 mm between the needle electrode and closest edge of the current source. It changed logarithmically with the number of muscle fibers and with the diameter of the fibers.

Concentric needle recording characteristics related to depth of tissue penetration

This study investigates the influence of tissue penetration depth as it relates to a concentric needle electrode, particularly delineating regions where the cannula potential predominates over the core potential. The regions of cannula predominance is studied by means of a standard and 20 times enlarged physical model of an electromyographic concentric needle electrode in a homogeneous volume conductor by delineating the zero isopotential which partitions where the core potential predominates versus where the cannula potential predominates. Clinical studies in muscle tissue are used to test and confirm results from the enlarged physical model. At shallow electrode insertions equivalent to 4 mm, the concentric needle model records a net negative potential, which is a region where the cannula predominates, from a distant positive dipole at the same depth compared with a net positive potential for penetration depths exceeding 4 mm. The clinical portion of this study verifies the bipolar nature of the concentric needle electrode in detecting motor unit action potentials (MUAPs) with primarily an initial positive onset irrespective of recording depth. Refinements to the conceptualization of the nature and detection of MUAPs are discussed which are consistent with all the findings of the clinical and model study.

Volume conduction models for surface EMG; confrontation with measurements

Volume conduction models are used to describe and explain recorded motor unit potentials (MUPs). So far it has remained unclear which factors have to be taken into account in a volume conduction model. In the present study, five different models are confronted with measured MUP distributions over the skin surface above the m. biceps brachii generated by MUs at different depths and recorded by small surface electrodes. All model simulations include fibres of finite length. The models differ in the size of the volume conductor (finite/infinite), the number of different layers (1, 2 or 3) and the conductivities of these layers (representing muscle, subcutaneous fat and skin). All measured and simulated MUPs contain a mainly negative propagating wave followed by a positive wave simultaneously present at all electrode positions. The magnitude of the different MUP components relative to each other and as a function of motor unit (MU) and electrode position differ between the models studied and the measurements. All simulated MUPs changed faster with observation distance than the measured MUPs. The three-layer model, in which muscle tissue was surrounded by a subcutaneous fat layer and by a layer of skin resulted in MUPs closest to the measured MUPs.

Concentric and single fiber electrode spatial recording characteristics

A better appreciation of the specific spatial recording characteristics of the single fiber and concentric needle electrode can result in more accurate physiologic and theoretical interpretations of single fiber and quantitative motor unit action potential analysis. We demonstrate by physical modeling that the 90% and 99% amplitude sensitivity envelopes are not simple hemispherical shapes. The 90% sensitivity concentric electrode volume does not extend beyond the insulated portion of the 15 degree beveled surface between the core and cannula and extends only 280 microm perpendicularly from the center of the core's surface. The 99% envelope extends approximately 830 microm perpendicularly from the core's center. This is a much smaller volume of sensitivity than exists for a similarly modeled monopolar electrode. The 90% and 99% envelopes extend to 110 and 320 microm perpendicularly from the exposed single fiber core. Both the single fiber and concentric needle volumes of sensitivity have specific asymmetries described.

Concentric needle electrode duration measurement and uptake area

Motor unit action potentials (MUAPs) were recorded with a standard concentric needle electrode inserted into the right biceps brachii muscle with different angular orientations of the beveled recording surface to the muscle fibers. Contrary to the predictions from computer simulations, the MUAP duration remained constant during needle rotation. This finding is used to reexamine the previous assumptions regarding the concentric needle's spatial uptake recording territory and the implications with respect to MUAP duration measurements.

Concentric/monopolar needle electrode modeling: spatial recording territory and physiologic implications

Scaled 20:1 physical models of monopolar and standard concentric needle electrodes are investigated with a constant current bipolar generator to determine the amplitude versus radial distance characteristics of these two electrodes. Each model is examined at three scaled and simulated tissue penetration depths (4, 10 and 20 mm) with measurements documented from 20 to 9000 microns radially in front and behind the models. The monopolar compared to concentric electrode has a smaller response to a standardized stimuli but a flatter response curve at distances of less than 1500 microns. The cannula of the concentric needle also has a flatter response than that of its core. When compared to a remote reference such as that at scaled depths of tissue penetration approximating 4 mm or less the cannula-to-remote reference potential exceeds the amplitude of the core-to-remote reference, recording a net negative potential at 6500 microns in front and 3500 microns behind the core. This study offers an explanation for the clinically observed larger magnitude potentials detected with monopolar compared to concentric electrodes resulting from a larger recording cross-sectional area with more fibers contributing to the potential even though the magnitude of potential at any one location is comparatively smaller in magnitude than that for the concentric electrode. Additionally, the physiologic duration of a motor unit is anticipated to be considerably longer than presently measured clinically with automated methods because of the electrodes' ability to detect such small signals from a large region of the volume conductor.

Motor unit action potentials recorded with concentric electrodes: physiologic implications

Computer simulations of concentric needle electrode recording characteristics assume a hemisphere spatial recording territory for the electrode's core with the cannula shielding electrical activity arising from those muscle fibers located behind the cannula with respect to the electrode's core. It is also believed that the motor unit action potential's (MUAP) duration is generated by the number of muscle fibers within the electrode's hemispherical recording territory. This presumption suggests that rotating the needle will necessarily alter the number of muscle fibers within the hemispherical recording territory and hence lead to an alteration in MUAP duration. Comparisons were performed for different needle orientations with documentation of no statistically significant alteration in MUAP duration. Additionally, referential recording montages with the concentric needle electrode revealed that the electrode's core records MUAPs with durations comparable to those detected by the cannula. These findings strongly suggest that the recording territory of the concentric needle electrode, with respect to MUAP duration, is not a hemisphere but a sphere encompassing most if not all of the MUAP's muscle fibers in a manner similar to that of a monopolar needle. These findings have significant implications regarding presently used MUAP simulation techniques and require a reconceptualization of how the concentric needle electrode records electrical activity within a volume conductor.

Spatio-temporal representation of multichannel EMG firing patterns and its clinical applications

Analyzing motor unit (MU) activity is essential for studying the neurological dysfunction of upper motor neuron disorders (UMND). This study employs multichannel surface electromyographic (EMG) signals, as recorded from the upper arm during elbow flexion and extension, to analyze the temporal changes and spatial distribution of the dominant firing rate. To estimate the dominant firing rate, the autoregressive (AR) spectrum analysis method is utilized to detect the peaks and poles of the AR model, of the surface EMG spectrum below 40 Hz. The temporal changes in firing rates are also observed by using the spectrogram representation of low-frequency EMG spectra. The EMG spectrogram facilitates examination of the time-varying characteristics of firing rates and recruitment of MUs from surface EMG signal. The low-frequency spectra of multichannel EMG are then represented in a polar form to visualize the spatial distribution of firing patterns across muscles. Via spatio-temporal representation techniques, this study provides a viable approach of observing both the spatial and temporal patterns of MU activities in normal subjects and patients with UMND, including cerebrovascular disease and Parkinson's disease.

Analysis of the electromyographic interference pattern

The electromyographic interference pattern (EMG-IP) contains information about the number, firing rate, and recruitment characteristics of motor units, and information regarding the waveforms of the recruited motor units. Muscle and nerve diseases produce characteristic changes in the IP that can be distinguished by IP analysis. This analysis complements analysis of the motor unit potentials. The electromyographer usually assesses the IP signals subjectively by their appearance on the oscilloscope screen and by their sound on the audio monitor. Techniques have been developed to automate IP analysis with and without force monitoring. These techniques give objective information, quantitate the degree of abnormality, and permit electromyographers-in-training to compare their subjective analysis of the IP with more objective findings.

Muscle electric activity. II: On the feasibility of model-based estimation of experimental conditions in electromyography

From regular one-channel registrations of single muscle fiber action potential no measures on the recording configuration can be derived. When multichannel recordings are made, experimental parameters such as the distance between muscle fiber and needle electrode can be estimated. With the help of a volume conductor model, the single fiber activity at each of the electrodes can be predicted as a function of the recording conditions. Within known physical and physiological constraints such a model approach can be inverted (the inverse model) and used to estimate basic experimental conditions. From eight simultaneous single fiber action potential recordings we estimated (a) the distance between fiber and needle, (b) the axial position of the needle with respect to the muscle fiber, (c) a factor related to the muscle tissue anisotropy, and (d) a factor combining the muscle fiber diameter and the effective muscle tissue conductivity. With the help of a model describing the influence of the needle shaft it is made plausible that the needle inhomogeneity influences the results of the proposed procedure.

Long-lasting supernormal conduction velocity after sustained maximal isometric contraction in human muscle

Local muscle fatigue (1 min maximal voluntary contraction) and recovery were studied by means of surface and invasive EMG on elbow flexors to record the changes in muscle fiber conduction velocity (MFCV), median power frequency (MPF), integrated EMG (IEMG), and force. The main finding was a long-lasting "supernormal" MFCV during recovery, for at least 1 hour. After a normalization phase, the MFCV and MPF continued to increase reaching a steady state at supernormal values after 10-12 min. Mean MFCV increase at 20% MVC after 15-min recovery was 0.58 m.s-1 (12%). Postfatigue IEMG values were increased at all contraction levels. In combination with near normal force levels, this resulted in a decrease in "neuromuscular efficiency" (force/IEMG). We suggest that this IEMG increase is mainly a result of the MFCV increase. The MFCV changes in fastest and slowest fibers found with the invasive method indicate a relatively equal effect on type I and II fiber types. A possible explanation of the supernormal MFCV is muscle fiber swelling, in combination with altered membrane properties.

Investigation on parametric analysis of dynamic EMG signals by a muscle-structured simulation model

In the analysis of electromyographic (EMG) signals during dynamic movement, we have proposed an estimation algorithm for the time-varying parameters of an autoregressive model. The parameters correspond to less biased time-varying reflection coefficients. We determined the less biased estimation using a locally quasi-stationary model and named these parameters "k parameters." We estimated k parameters up to the fifth order for the surface EMG signals of a masseter muscle during rapid open-close movement of the lower jaw, a ballistic contraction, and fatigue. According to the results, the time courses of the k parameters displayed remarkable properties. In order to study the behavior of k parameters physiologically, we produced a muscle-structured simulation model based on anatomical and physiological data. The simulation results suggested that the behavior of the third parameter is related to the number of active motor units (MU's) at the shallow layer of a muscle. The detailed recruitment mechanism in terms of the MU's types has not yet been solved. Although further study is required, the parametric analysis using k parameters offers a new perspective for evaluation of muscle dynamics during several movements.

Examination of the choice of models for computing the extracellular potential of a single fibre in a restricted volume conductor

The paper compares the rigorous and the conventional approximate line source solution of Laplace's equation used to evaluate the potential of a single cylindrical fibre. Particular attention is given to the solutions for a radially restricted circular cylindrical volume conductor. The effect of the extent of the volume conductor b on the difference between the potentials evaluated according to the different models is examined. For values of b larger than 10 times the fibre radius, the relative difference is less than 1 per cent and the values of b around 2 times the fibre radii, the error reaches as much as 17 per cent.

Finite limb dimensions and finite muscle length in a model for the generation of electromyographic signals

A volume conductor model is presented in which the aspects of finite volume conductor dimensions and finite muscle fiber length are combined. The effects of these aspects on single muscle fiber action potentials (SFAPs) and on motor unit action potentials (MUAPs) are shown and verified with surface recorded motor unit action potentials. It is demonstrated that the influence of the fiber length being finite is enhanced significantly by the finite limb dimensions of the volume conductor model, for single fiber action potentials as well as for motor unit action potentials. The model described is found to be capable of generating surface MUAPs which show a very good resemblance with measured surface MUAPs. Recorded MUAPs illustrate clearly the effects caused by finite muscle fiber length. The effect of finite limb dimensions in simulated intramuscular MUAPs was evidently less dominant than in simulated surface MUAPs.

On the relation between axial resistance and conductivity in linear cable models

In the classical core conductor model the intra- and extracellular media of an infinitely long nerve or muscle fiber in a volume conductor are represented by parallel axial resistances. Thus, volume conductor properties are neglected. In this paper a study is presented that relates the conductivity of the intra- or extracellular medium of the fiber to the axial resistance used in the core conductor model. Expressions for the axial resistances that are dependent on the spatial frequency of the membrane current source density are derived from a volume conductor approach.

Simulation of myopathic motor unit action potentials

Normal motor units (MUs) were simulated and their architecture altered to simulate the changes produced by myopathy. The concentric needle electromyographic recordings of motor unit action potentials (MUAPs) from the MUs were then also simulated. These simulated MUAPs showed features that are seen in myopathy: normal amplitude and slightly reduced area, MUAPs with simple waveform and reduced duration, and complex MUAPs with normal or increased duration. The MUAP waveforms were complex because of increased variability of fiber diameter and not because of loss of muscle fibers. The MUAP duration increased when the variability of fiber diameter increased. Finally, MUAPs similar to those seen in neurogenic diseases were produced from MUs in which the only abnormality was increased variability of fiber diameter.