Modeling the vestibular evoked myogenic potential

Measuring the vestibular evoked myogenic potential (VEMP) promises to become a routine method for assessing vestibular function, although the technique is not yet standardized. To overcome the problem that the VEMP amplitude depends not only on the inhibition triggered by the acoustic stimulation of the vestibular end organs in the inner ear, but also on the tone of the muscle from which the potential is recorded, the VEMP is often normalized by dividing through a measure of the electromyogram (EMG) activity. The underlying idea is that VEMP amplitude and EMG activity are proportional. But this would imply that the muscle tone is irrelevant for a successful VEMP recording, contradicting experimental evidence. Here, an analytical model is presented that allows to resolve the contradiction. The EMG is modeled as the sum of motor unit action potentials (MUAPs). A brief inhibition can be characterized by its equivalent rectangular duration (ERD), irrespective of the actual time course of the inhibition. The VEMP resembles a polarity-inverted MUAP under such circumstances. Its amplitude is proportional to both the ERD and the MUAP rate. The EMG activity, by contrast, is proportional to the square root of the MUAP rate. Thus, the normalized VEMP still depends on the muscle tone. To avoid confounding effects of the muscle tone, the standard deviation of the EMG could be considered. But the inhibition effect on the standard deviation is small so that the measuring time would have to be much longer than usual today.     

Motor unit number estimation as a complementary test to routine electromyography in the diagnosis of amyotrophic lateral sclerosis

Electromyographic (EMG) abnormalities that reveal denervation and reinnervation caused by lower motor neuron degeneration do not reflect the number of motor units that determines muscle strength. Consequently, motor unit activity potential (MUAP) parameters do not reflect muscle dysfunction.The aim of the study was to compare the value of motor unit number estimation (MUNE) and MUAP parameters as indicators of clinical muscle dysfunction in patients with amyotrophic lateral sclerosis (ALS), and to analyze the role of MUNE as a supplement to the EMG criteria for the diagnosis of ALS.In 25 patients with ALS, MUNE by the multipoint incremental method in the abductor digiti minimi (ADM) and quantitative EMG in the first dorsal interosseous (FDI) were obtained. The Medical Research Council (MRC) scale was used to evaluate clinical muscle dysfunction. A strong correlation between the number of motor units evaluated by MUNE and ADM clinical function by the MRC scale was found (P < 0.001). An increased value of surface-detected single motor action potential was associated with a decreased MRC score for ADM (P < 0.1). No relation was found between MUAP parameters in FDI and MRC scores. Our data support the value of the MUNE method for the detection of motor unit loss in ALS, and it could be postulated that MUNE studies may be considered complementary tests for ALS in a future revision of ALS criteria.     

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.     

Determination of feature relevance for the grouping of motor unit action potentials through a generative mixture model

The study of motor unit action potential (MUAP) activity from electromyographic signals is important for neurological investigations aiming to understand the state of the neuromuscular system. In this context, the identification and clustering of MUAPs that exhibit common characteristics, and the assessment of which data features are most relevant for the definition of such cluster structure, are central issues. In this paper, we propose the application of an unsupervised feature relevance determination (FRD) method to the analysis of experimental MUAPs. This method is embedded in a constrained mixture of distributions model that simultaneously performs data clustering and visualization. The experimental results of the analysis of a data set consisting of MUAPs measured from the First Dorsal Interosseous, a hand muscle, indicate that the features corresponding to the hyperpolarization period in the physiological process of generating muscle fibre action potentials are consistently estimated to be the most relevant. Moreover, the MUAP cluster structure of the data is shown to be only partially attributable to inter-subject differences, with the hyperpolarization period providing the best discrimination of the data by subject.     

Motor Unit Characteristics after Targeted Muscle Reinnervation

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

Comparative analysis of motor unit action potentials of the medial gastrocnemius muscle in cats and rats

Properties of motor unit action potentials (MUAPs) were compared for medial gastrocnemius (MG) motor units (MUs) in cats and rats. The experiments on functionally isolated MUs were performed under general anaesthesia, under comparable conditions (surgery, stimulating protocol and recording methods) for both species investigated. The proportions of motor units and contractile properties of the sample used in the study were consistent with previous studies performed on the MG muscle in both animal species, so comparisons of action potentials of individual types of MUs were acknowledged as fully reliable. The most prominent differences concerning MUAPs were observed in total duration and peak-to-peak times which for all MU types were about twice longer in cat MUs, in comparison to the rat MUs. The considerable disproportions were observed between the MUAP amplitudes of FF (fast fatigable), FR (fast resistant to fatigue) and S (slow) MUs in each species (the highest amplitudes were measured for FF and the lowest for S MUs), but there were no significant differences between cat and rat when respective types of MUs were compared. The shapes of MUAPs were commonly characterized by biphasic waveforms composed of two or three turns in all types of units, and no interspecies differences were revealed. Several factors influencing MUAP parameters were discussed indicating most of all importance of variable length of cat and rat muscle fibres and ambiguous influence of motor unit size, thickness of muscle fibres and their density around the recording electrode in the MG muscle of both species.     

Computer simulation study of the shape of motor unit action potential

Motor unit action potentials (MUAPs) of brachial biceps were simulated. A simulated MUAP was obtained as a sum of single fibre action potentials (SFAPs) from all the muscle fibres of a motor unit (MU). The influence of the following factors on MUAP shape for different kinds of recording electrode was studied: fibre density, neuromuscular jitter, temporal dispersion and electrode displacements. The simulation confirms that typical MUAPs recorded with needle electrodes from muscles of low fibre density such as brachial biceps are usually triphasic. Increased fibre density produces MUAPs of more complex shape and higher amplitude. Normal neuromuscular jitter is responsible for the variability of shape of subsequent potentials from the same MU as well as for electromyographic shimmer. Pathologic (increased) jitter makes the shapes of subsequent potentials unrecognizable. The influence of temporal dispersion is interconnected with other factors but rather of minor importance. The simulation shows how big changes in MUAP shape can be expected due to electrode displacements during single experiment or during estimation of MU territory.     

Use of surface EMG for studying motor unit recruitment during isometric linear force ramp.

The aim of this work was to demonstrate the rank order of motor unit (MU) recruitment by surface EMG based on a Laplacian detection technique and to document the MU features at their recruitment threshold. Surface EMG signals were recorded on the biceps brachii of 10 healthy subjects during linear force ramps. When achievable, the signals were decomposed into MU action potential (MUAP) trains. MU inter-pulse interval (IPI), conduction velocity (MUCV) and amplitude were estimated on the first 12 MUAPs of each detectable train in order to characterize the MU features at their firing onset. A strong correlation was found between MU recruitment threshold and IPI, MUCV, and amplitude, showing that the size principle can be demonstrated by a fully non-invasive EMG technique. However, signal decomposition was not possible on seven subjects due to the effects of the volume conductor when the skinfold thickness was too large. When requirements for an optimal detection of MUAP trains are met, surface EMG may be used to improve our understanding of MU activity.     

The need for computer-aided electromyography

The limits of quantitative manual electromyography (EMG) are discussed. The role of computers in EMG laboratories is at present to imitate or replace the physician performing the test, extending his memory, to gather valuable information which cannot be obtained in a conventional way or, on the contrary, to delete the redundant information. The difficulties in standardizing the parameters of a single motor unit action potential (MUAP) are mainly related to the complexity of the EMG signal and its variability, particularly in pathological states. A computer-aided quantification of interference pattern is presented. The novel methods of examination applied in computerized EMG laboratories are discussed. The scope and limits of computer-aided EMG should be taken into action potential (MUAP) are mainly related to the complexicity of the EMG be accepted are listed.     

Hill muscle model errors during movement are greatest within the physiologically relevant range of motor unit firing rates

This study evaluated the accuracy of Hill-type muscle models during movement. Hill-type models are ubiquitous in biomechanical simulations. They are attractive because of their computational simplicity and close relation to commonly measured experimental variables, but there have been surprisingly few experimental validations of these models during functionally relevant conditions. Our hypothesis was that model errors during movement are largest at the low motor unit firing rates most relevant to normal movement conditions. This hypothesis was evaluated in the cat soleus muscle activated either by electrical stimulation at physiological rates or via the crossed-extension reflex (CXR) thereby obtaining normal patterns of motor unit recruitment and rate modulation. These activation paradigms were applied during continuous movements approximately matched to locomotor length changes. The resulting muscle force was modeled using a common Hill model incorporating independent activation, tetanic length-tension and tetanic force-velocity properties. Errors for this model were greatest for stimulation rates between approximately 10-20Hz. Errors were especially large for muscles activated via the CXR, where most motor units appear to fire within this range. For large muscle excursions, such as those seen during normal locomotion, the errors for naturally activated muscle typically exceeded 50%, supporting our hypothesis and indicating that the Hill model is not appropriate for these conditions. Subsequent analysis suggested that model errors were due to the common Hill model's inability to account for the coupling between muscle activation and force-velocity properties that is most prevalent at the low motor unit firing rates relevant to normal activation.     

Measuring the accuracies of motor unit firing times and action potential waveforms derived from surface electromyographic decomposition

This study included spike trigger averaging (STA) procedures to examine the acceptability of the Precision Decomposition (PD) III derived motor unit action potential (MUAP) trains that met the >90% accuracy criteria from the reconstruct-and-test. MUs met the >90% accuracy criteria from the reconstruct-and-test with STA procedures then applied. Y-intercepts and slopes were calculated for the firing rate- and MUAP amplitude-recruitment threshold relationships. Gaussian noise (1% of the SD of the mean interspike interval) was added to the firing times with the changes in MUAPs quantified. A total of 455 MUs were decomposed with 155 MUs removed as a result of the reconstruct-and-test. Five additional MUs were excluded via the STA criteria. The MUAP waveforms deteriorated with the inclusion of Gaussian noise. There were differences in the derived action potentials amplitudes of higher-threshold MUs between the PD III algorithm and the STA procedure. There was excellent agreement among the slopes and y-intercepts between the relationships that included or excluded MUs that did not meet the STA criteria. There was good agreement between the MUAP amplitude-recruitment threshold relationships derived from the PD III and STA procedure. The addition of the STA procedures did not alter the MU-derived relationships.     

Separation of propagating and non propagating components in surface EMG

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

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

Short term bed-rest reduces conduction velocity of individual motor units in leg muscles

Space permanence simulations such as prolonged bed-rest can mimic some of the physiological modifications in the human body and provide study conditions that are more accessible than during space flight. A short term bed-rest experiment was organized to simulate the effects of weightlessness for studying the adaptation to this condition. Eight healthy young volunteers were studied before and immediately after the 14 day periods of strict bed-rest.Surface EMG signals were detected with linear electrode arrays from vastus medialis, vastus lateralis and tibialis anterior muscle during isometric voluntary contractions at 20% MVC. Motor unit action potentials (MUAPs) of individual motor units were extracted from the interference EMG signals with a partial decomposition algorithm and averaged.MUAP templates generated by the same motor unit could be retrieved before and after bed-rest period. Muscle fiber conduction velocity (CV) was estimated from each averaged MUAP template and from the global EMG signal. Both global and single MU conduction velocity was observed to decrease by about 10% after the bed-rest period (p < 0.05). Amplitude and power spectral parameters did not significantly change after the bed-rest period.It is concluded that a short term bed-rest reduces the CV of individual motor units without a significant effect on muscle force or on other electrophysiological parameters.     

Effect of aging on properties of motor unit action potentials in the rat medial gastrocnemius muscle

The purpose of this study was to investigate whether age-related changes in motor unit (MU) contractile properties are reflected in parameters of motor unit action potentials (MUAPs). MUs of the medial gastrocnemius muscle were functionally isolated in anaesthetized Wistar rats. A control group of young animals (5–10 mo) was compared to two groups of old rats (24–25 mo and 28–30 mo). The basic contractile properties of MUs as well as the amplitude, total duration, peak-to-peak time, and number of turns within MUAPs were measured. Effects of aging were mainly observed for fast fatigable MUs (a prolongation of MUAPs and increased number of turns). The MUAP amplitude did not change significantly with aging in either MU type, but it correlated to the twitch or tetanic forces, which tended to increase with age, especially for slow MUs. We concluded that the prolongation of MUAPs and the greater incidence of signal turns was probably a result of a decrease in muscle fiber conduction velocity and/or an increase in their dispersion, and enlargement of MU territories – presumably caused by axonal sprouting of surviving motoneurons. The latter might also be responsible for the observed age-related tendency for a increase in MUAP amplitudes in slow MUs.     

A teleological explanation of Weber's law and the motor unit size law

It is shown that the Weber-Fechner law. which relates the response of a sensory biosystem to the intensity of the input stimulus, can be derived from a teleological principle of minimum transentropy (maximal noise reduction) provided the relative mean fluctuation (coefficient of variation) of the input intensity can be assumed to be (approximately) constant for all feasible mean input intensities. A law is then deduced from experimental results which quantifies the relationship existing between the relative amount of activated muscle mass and the “size” (which term is clearly defined) of a newly recruited motor unit. This law is found to be formally equivalent to the Weber-Fechner law when applied to motor unit recruitment. It is then shown that, in general, the ratio of the force increment upon recruitment, to the present force output does not obey Weber's law. Finally, it is proved that the “motor unit size law” as derived in this paper implies a fixed sequential order in the recruitment of motor units and that it may be viewed as the realization, by the mammalian neuromuscular system, of a general principle of maximum grading sensitivity.     

Myoelectric manifestations of fatigue at low contraction levels in subjects with and without chronic pain.

The aim of the present study was to investigate differences in myoelectric responses to fatigue development between cases with chronic neck-shoulder pain (n=10) and healthy controls (n=10) during a low force level sustained contraction. Subjects performed a 15-min isometric shoulder elevation at a force level of 40 N (sustained contraction), preceded and followed by a step contraction, consisting of five force levels from 20 to 100 N. EMG recordings were made with a two-dimensional electrode array on the upper trapezius of the dominant side. Root-mean-square (RMS(G)), median power frequency (FMED(G)), conduction velocity (CV), number of motor unit action potentials per second (MUAP Rate) and MUAP shape properties were estimated. Changes over time and differences between the groups were statistically evaluated with a linear mixed model. During the sustained contraction, cases showed less increase in RMS(G) than controls (controls: 58.5%, cases: 33.0%). FMED(G) and CV decreased in controls (FMED(G): -6.3%, CV: -5.3%) and stayed constant (FMED(G)) or slightly increased (CV, 3.15%) in cases. Overall, cases showed a less pronounced myoelectric response to the fatiguing task than controls, which may be related to additional recruitment of higher-threshold MUs. A possible explanation might be that cases were already (chronically) fatigued before the experiment started.     

Automatic detection of motor unit innervation zones of the external anal sphincter by multichannel surface EMG

A method to detect automatically the location of innervation zones (IZs) from 16-channel surface EMG (sEMG) recordings from the external anal sphincter (EAS) muscle is presented in order to guide episiotomy during child delivery. The new algorithm (2DCorr) is applied to individual motor unit action potential (MUAP) templates and is based on bidimensional cross correlation between the interpolated image of each MUAP template and two images obtained by flipping upside-down (around a horizontal axis) and left–right (around a vertical axis) the original one. The method was tested on 640 simulated MUAP templates of the sphincter muscle and compared with previously developed algorithms (Radon Transform, RT; Template Match, TM). Experimental signals were detected from the EAS of 150 subjects using an intra-anal probe with 16 equally spaced circumferential electrodes. The results of the three algorithms were compared with the actual IZ location (simulated signal) and with IZ location provided by visual analysis (VA) (experimental signals). For simulated signals, the inter quartile error range (IQR) between the estimated and the actual locations of the IZ was 0.20, 0.23, 0.42, and 2.32 interelectrode distances (IED) for the VA, 2DCorr, RT and TM methods respectively.     

Motor unit number estimation--a Bayesian approach

All muscle contractions are dependent on the functioning of motor units. In diseases such as amyotrophic lateral sclerosis (ALS), progressive loss of motor units leads to gradual paralysis. A major difficulty in the search for a treatment for these diseases has been the lack of a reliable measure of disease progression. One possible measure would be an estimate of the number of surviving motor units. Despite over 30 years of motor unit number estimation (MUNE), all proposed methods have been met with practical and theoretical objections. Our aim is to develop a method of MUNE that overcomes these objections. We record the compound muscle action potential (CMAP) from a selected muscle in response to a graded electrical stimulation applied to the nerve. As the stimulus increases, the threshold of each motor unit is exceeded, and the size of the CMAP increases until a maximum response is obtained. However, the threshold potential required to excite an axon is not a precise value but fluctuates over a small range leading to probabilistic activation of motor units in response to a given stimulus. When the threshold ranges of motor units overlap, there may be alternation where the number of motor units that fire in response to the stimulus is variable. This means that increments in the value of the CMAP correspond to the firing of different combinations of motor units. At a fixed stimulus, variability in the CMAP, measured as variance, can be used to conduct MUNE using the "statistical" or the "Poisson" method. However, this method relies on the assumptions that the numbers of motor units that are firing probabilistically have the Poisson distribution and that all single motor unit action potentials (MUAP) have a fixed and identical size. These assumptions are not necessarily correct. We propose to develop a Bayesian statistical methodology to analyze electrophysiological data to provide an estimate of motor unit numbers. Our method of MUNE incorporates the variability of the threshold, the variability between and within single MUAPs, and baseline variability. Our model not only gives the most probable number of motor units but also provides information about both the population of units and individual units. We use Markov chain Monte Carlo to obtain information about the characteristics of individual motor units and about the population of motor units and the Bayesian information criterion for MUNE. We test our method of MUNE on three subjects. Our method provides a reproducible estimate for a patient with stable but severe ALS. In a serial study, we demonstrate a decline in the number of motor unit numbers with a patient with rapidly advancing disease. Finally, with our last patient, we show that our method has the capacity to estimate a larger number of motor units.     

Motor unit tracking with high-density surface EMG

Following (tracking) individual motor units over time can provide important new insights, both into the relationships among various motor unit (MU) morphological and functional properties and into how these properties are influenced by neuromuscular disorders or interventions. The present study aimed to determine whether high-density surface EMG (HD-sEMG) recordings, which use an array of surface electrodes over a muscle, can increase the yield of MU tracking studies in terms of the number of MUs that can be tracked. For that purpose, four HD-sEMG recording sessions were performed on the thenar muscles of ten healthy subjects. Decomposition of the recorded composite responses yielded a study total of 2849 motor unit action potentials (MUAPs). MUAPs that were found in both of the first two sessions, performed on the same day, were defined as trackable MUAPs. Our results show that 22 (median value; range, 13–34) MUAPs per nerve were trackable, which represented approximately 5% of the total MU population. Of these trackable MUAPs, 16 (11–26) could also be found in one or both of the third and fourth sessions, which were performed between 1 and 13 weeks after the initial studies. Nine (4–18) MUAPs were found in all four sessions. Many of the characteristic MUAP shapes matched well between sessions, even when these sessions were several weeks apart. However, some MUAPs seem very sensitive to changes in arm position or in the muscle’s morphology (e.g., to changes in muscle fiber length due to variable degrees of thumb flexion or extension), particularly those from larger and/or superficial MUs. Standardization is, therefore, essential to detect even small MUAP changes, as may occur with pathology or interventions. If this is accomplished, MU tracking with HD-sEMG may prove to be a powerful tool for a promising type of neurophysiological investigation.     

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

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