Motor unit changes in inflammatory myopathy and progressive muscular dystrophy

The aim of present study was to analyse the motor unit (MU) changes in progressive muscle dystrophy (PMD) and in inflammatory myopathy (IM) and to evaluate eventual neurogenic factors in MU reorganisation. The material consisted of 20 patients with (PMD), 20 patients with (IM) and 20 healthy age-matched volunteers. The shape of concentric needle motor unit potentials (cn MUPs), including their duration, amplitude, area, size index and number of phases, the interference pattern and the amplitude and area of macro MUPs were evaluated. The cn emg data satisfied the classical criteria for myopathy in all examined patients, at least in one of the tested muscles. A decreased amplitude and/or area of macro MUPs, compatible with myopathy, were observed in 32 of the 40 patients. In some cases of chronic IM and PDM the long duration polyphasic potentials were recorded. The size index (SI) value of long polyphasic MUPs was usually decreased or normal. This feature indicated that desynchronisation of "myopathic" MUPs results from a reduced number of muscle fibers and their degeneration and regeneration. The results indicated no difference in MU reorganization between PMD and IM and no evidence of neurogenic factors in MU changes.     

Area-to-amplitude ratio of the terminal phase of the belly-tendon detected motor unit potentials could be used to recognize reinnervated motor units

Besides the increased number of fibres, the reinnervated motor units (MUs) are characterised by an increased scattering the end-plates, greater desynchronization in the fibres' activation, greater dispersion in the diameters of the MU fibres and thus in propagation velocities along them. As a result, desynchronization in the moments, at which the excitation waves reach the fibres' ends, increases in reinnervated MUs. The possibility to recognize reinnervated MUs in short (hand) muscles on the basis of changes in duration of the terminal (second) phase of the belly-tendon detected motor unit potentials (MUPs) was examined by numerical experiments. A convolution model that took into account the finite fibre length, was used to calculate MUPs for distances typical of surface detection. It was shown that the ratio between the area of the terminal phase and its amplitude, as a measure of duration of the terminal phase, was sensitive to desynchronisation of the waves of excitation. The ratio was independent of the distance from the MU axis and of the volume conductor properties. Basing on the results obtained, we can conclude that the ratio reflects main functional compensations in reinnervated MUs and could be used for discrimination between reinnervated and normal MUs.     

Surface detected potentials of normal and reinnervated motor units: a simulation study for muscles consisted of short fibres

We aimed to check whether the characteristics used up to now in macro EMG to distinguish between normal and reinnervated motor unit potentials (MUPs), were suitable for surface detected MUPs. MUPs produced by normal and reinnervated MUs were simulated with a fast and precise convolution model. An increased number of fibres in the MU territory enhanced the amplitude, area and RMS of the MUP proportionally irrespective of the MU-electrode distance. An increased scatter of the end-plates and greater desynchronization in the fibres' activation decreased the MUP amplitude and affected the temporal characteristics of the MUP (duration of the negative phase and its area to amplitude ratio). The effects were more pronounced at shorter distances. At larger distances, the effect of the MU-electrode distance on temporal and amplitude characteristics of MUPs was much stronger than that of the parameters changed with reinnervation. We conclude that reinnervated MUs consisting of short fibres can not be distinguished from the normal ones by means of characteristics of MUP used in macro EMG. To discriminate reinnervated MUs non-invasively, the MUP amplitude should be normalized in respect of the MU-electrode distance or other MUP characteristics (independent of MU-electrode distance and sensitive to reinnervation) should be used.     

Depth and intensity of equivalent current dipoles estimated through an inverse analysis of surface electromyograms using the image method

The depth and intensity of equivalent current dipoles that can create the surface potentials of active motor units in human skeletal muscles are estimated through an inverse analysis of surface electromyographic (EMG) potentials in an attempt to measure detailed muscular activity non-invasively. The inverse analysis is conducted by repetition of forward analyses. In the study, the image method is used for forward analysis, because it is the simplest potential calculation method for electric currents in a semi-infinite volume conductor. Using this method, surface EMG potentials are calculated for current sources assumed to be located in a muscle. An inverse analysis is then carried out by searching for the depth and intensity of such current sources that would minimise the sum of squares difference between measured and calculated surface EMG potentials. The inverse analysis is applied to surface EMG potentials measured from the biceps brachii of three healthy subjects. As a result, the individual current sources are estimated to be 2.7±1.6 mm deep and 0.5±0.9 nAm in intensity, whereas the total current intensity for individual motor units is 2.4±2.9 nAm.     

Evaluation of motor unit firing rates by standard concentric needle electromyography.

Motor unit firing rates at slight voluntary contraction were studied by standard concentric needle electromyography. Employing digital signal analysis techniques firing rates of motor units (MU) could be evaluated as long as four or less different MUs were activated in the vicinity of the concentric needle electrode. The extension of the recording area is defined by the recording properties of the electrode and the upper limit of rise-time for all MUPs being evaluated. Distant MUs, generating volume conducted potentials with rise-times greater than 0.8 ms, were excluded. In biceps muscles of 15 healthy controls the firing rate of the MU activated first was evaluated at that moment, when a second MU was recruited and was found to be 12.1 +/- 2.1 Hz (mean +/- S.D., n = 40). The firing rate of the fastest MU out of 2, 3, or 4 simultaneously active MUs was 10.7 +/- 2.5 Hz, 10.9 +/- 2.5 Hz and 10.6 +/- 2.4 Hz respectively. Hence at low innervation level there is no increase of firing rate with rising number of activated MUs. The upper normal limit of MU firing rate (3 sigma interval) is calculated as 17 Hz, irrespective whether 1, 2, 3 or 4 MUs are active within the recording area. Fifteen patients with partially denervated biceps muscles were investigated. Maximal firing rates were increased in 10 patients, all showing moderate or severe paresis (grade 1-3). In 10 patients suffering from myopathies firing rates always were normal. The presented data may serve as an additional criterion in evaluating MU firing rates during standard clinical EMG.     

Influence of motor unit synchronization on amplitude characteristics of surface and intramuscularly recorded EMG signals

The increase in muscle strength without noticeable hypertrophic adaptations is very important in some sports. Motor unit (MU) synchronisation and higher rate of MU activation are proposed as possible mechanisms for such a strength and electromyogram (EMG) increase in the early phase of a training regimen. Root mean square and/or integrated EMG are amplitude measures commonly used to estimate the adaptive changes in efferent neural drive. EMG amplitude characteristics could change also because of alteration in intracellular action potential (IAP) spatial profile. We simulated MUs synchronization under different length of the IAP profile. Different synchronization was simulated by variation of the percent of discharges in a referent MU, to which a variable percent of remaining MUs was synchronized. Population synchrony index estimated the degree of MU synchronization in EMG signals. We demonstrate that the increase in amplitude characteristics due to MU synchronization is stronger in surface than in intramuscularly detected EMG signals. However, the effect of IAP profile lengthening on surface detected EMG signals could be much stronger than that of MU synchronization. Thus, changes in amplitude characteristics of surface detected EMG signals with progressive strength training could hardly be used as an indicator of changes in neural drive without testing possible changes in IAPs.     

Intramuscular EMG signal decomposition

Information regarding motor unit potentials (MUPs) and motor unit fi ring patterns during muscle contractions is useful for physiological investigation and clinical examinations either for the understanding of motor control or for the diagnosis of neuromuscular disorders. In order to obtain such information, composite electromyographic (EMG) signals are decomposed (i.e., resolved into their constituent motor unit potential trains [MUPTs]). The goals of automatic decomposition techniques are to create a MUPT for each motor unit that contributed significant MUPs to the original composite signal. Diagnosis can then be facilitated by decomposing a needle-detected EMG signal, extracting features of MUPTs, and finally analyzing the extracted features (i.e., quantitative electromyography). Herein, the concepts of EMG signals and EMG signal decomposition techniques are explained. The steps involved with the decomposition of an EMG signal and the methods developed for each step, along with their strengths and limitations, are discussed and compared. Finally, methods developed to evaluate decomposition algorithms and assess the validity of the obtained MUPTs are reviewed and evaluated.     

Non-invasive approach of motor unit recording during muscle contractions in humans

Information about the structural and functional characteristics of the motor unit (MU) is highly relevant for the diagnosis of neuromuscular disorders. Electromyography (EMG) is a suitable method for obtaining the information needed. The problem is the separation of the activity of one MU from others which are simultaneously active. Such investigations of single MU activity have commonly used invasive methods, e.g. employing a needle or a wire. Conventional surface-EMG methods have limited resolution and detect, at high contraction levels, multiple MU superimposed one on the other. The separation of the activity of a single MU can be achieved in a non-invasive way when highly specialised acquisition techniques are used. One approach, called high spatial resolution EMG (HSR-EMG), is based on the use of multi-electrode arrays in combination with a two-dimensional Laplace filter. The HSR-EMG permits the completely non-invasive detection of single MU activity even during maximal voluntary contractions. First applications have shown that the method provides a deeper insight into the functional and structural characteristics of the MU. In this paper the application of HSR-EMG to the diagnosis of neuromuscular disorders will be presented, and the latest results will be given of its application in the evaluation of treatment of patients with plexus lesion. Accepted: 6 June 2000     

Localization and contractile properties of intrinsic longitudinal motor units of the rat tongue

Tongue dysfunction is a hallmark of many human clinical disorders, yet we lack even a rudimentary understanding of tongue neural control. Here, the location and contractile properties of intrinsic longitudinal motor units (MUs) of the rat tongue body are described to provide a foundation for developing and testing theories of tongue motor control. One hundred and sixty-five MUs were studied by microelectrode penetration and stimulation of individual motor axons coursing in the terminal portion of the lateral (retrusor) branch of the hypoglossal nerve in the rat. Uniaxial MU force was recorded by a transducer attached to the protruded tongue tip, and MU location was estimated by electromyographic (EMG) electrodes implanted into the anterior, middle, and posterior portions of the tongue body. All MUs produced retrusive force. MU twitch force ranged from 2-129 mg (mean = 35 mg) and tetanic force ranged from 9-394 mg (mean = 95 mg). MUs reached maximal twitch force in 8-33 ms (mean = 15 ms) and were resistant to fatigue; following 2 min of stimulation, MUs (n = 11) produced 78-131% of initial force. EMG data were collected for 105 MUs. For 65 of these MUs, the EMG response was confined to a single electrode location: for 26 MUs to the anterior, 21 MUs to the middle, and 18 MUs to the posterior portion of the tongue. Of the remaining MUs, EMG responses were observed in two (38/40) or all three (2/40) tongue regions. These data provide the first contractile measures of identified intrinsic tongue body MUs and the first evidence that intrinsic longitudinal MUs are restricted to a portion of tongue length. Localization of MU territory suggests a role for intrinsic MU in the regional control of the mammalian tongue observed during feeding and speech.     

Motor unit potential characterization using "pattern discovery"

Typically in clinical practice, electromyographers use qualitative auditory and visual analysis of electromyographic (EMG) signals to help infer if a neuromuscular disorder is present and if it is neuropathic or myopathic. Quantitative EMG methods exist that can more accurately measure feature values but require qualitative interpretation of a large number of statistics. Electrophysiological characterization of a neuromuscular system can be improved through the quantitative interpretation of EMG statistics. The aim of the present study was to compare the accuracy of pattern discovery (PD) characterization of motor unit potentials (MUPs) to other classifiers commonly used in the medical field. In addition, a demonstration of PD's transparency is provided. The transparency of PD characterization is a result of observing statistically significant events known as patterns. Using clinical MUP data from normal subjects and patients with known neuropathic disorders, PD achieved an error rate of 30.3% versus 29.8% for a Na?ve Bayes classifier, 30.1% for a Decision Tree and 29% for discriminant analysis. Similar results were found for simulated EMG data. PD characterization succeeded in interpreting the information extracted from MUPs and transforming it into knowledge that is consistent with the literature and that can be valuable for the capture and transparent expression of clinically useful knowledge.     

Comparison of F-waves of motor unit action potentials activated during voluntary contraction

The system for classifying F-waves was developed to study the properties of F-wave and to compare single motor unit (MU) F-waves with motor unit action potentials (MUAPs) activated during voluntary contraction. The F-waves evoked by submaximal stimulation as well as the EMG signals during voluntary contraction at 6 levels of 10-100% of maximum voluntary contraction (MVC) were measured in the tibialis anterior muscles of 3 healthy volunteers. Nine channel F-wave waveforms in a selected electrode array were classified using a template-matching method. After the detection procedure of MUAPs in voluntary EMG signals, the MUAPs were also classified by the same method. Most of the F-waves (88.4%) were composed of a single MUAP. The numbers of MU classified from single MU F-waves in 3 subjects were 12, 12 and 15, and the numbers of MU classified from the voluntary EMG signals at 6 contraction levels were 20, 27 and 24, respectively. A total of 26 single MU F-waves were identified with the MUs extracted from the data during voluntary contractions. The results suggest that the F-waves are composed of a population of the MUs, which are recruited at a wide range of contraction levels. The classification procedures of F-waves and voluntary EMG signals have made it possible to recognize the same MU in both signals and to analysis the firing thresholds of F-waves.     

一种新型算法在组织光学参数测量系统中的应用

无创测量确定生物组织的光学特性参数在医学诊断和治疗领域中有着广泛的应用前景.目前确定组织参数的方法多建立在单层模型条件下,而实际的许多生物组织均具有分层结构,比如在肌肉、颅骨等.因此在多层模型条件下反演计算组织参数具有更大的实际意义.近年许多研究者针对以上问题提出了各种解决方法,如最小二乘法、神经网络方法等,但这些方法都存在需要时间过长或者误差较大的缺点.本文在组织参数测量领域引入数据挖掘办法--支持向量机(support vector machines,SVM),对双层模型中四个待定组织光学参数的确定进行了研究.结果 表明,利用SVM方法确定组织光学参数具有很好的准确性和实时性.     

Adaptive certainty-based classification for decomposition of EMG signals

An adaptive certainty-based supervised classification approach for electromyographic (EMG) signal decomposition is presented and evaluated. Similarity criterion used for grouping motor unit potentials (MUPs) is based on a combination of MUP shapes and two modes of use of motor unit (MU) firing pattern information: passive and active. Performance of the developed classifier was evaluated using synthetic signals of known properties and real signals and compared with the performance of the certainty classifier (CC). Across the sets of simulated and real EMG signals used for comparison, the adaptive certainty classifier (ACC) had both better average performance and lower performance variability. For simulated signals of varying intensity, the ACC had an average correct classification rate (CC _r ) of 83.7% with a mean absolute deviation (MAD) of 5.8% compared to 78.3 and 8.7%, respectively, for the CC. For simulated signals with varying amounts of shape and/or firing pattern variability, the ACC had a CC _r of 79.7% with a MAD of 4.7% compared to 76.6 and 6.9%, respectively, for the CC. For real signals, the ACC had a CC _r of 70.0% with a MAD of 6.3% compared to 64.9 and 6.4%, respectively, for the CC. The test results demonstrate that the ACC can manage both MUP shape variability as well as MU firing pattern variability. The ACC adapts to EMG signal characteristics to create dynamic data driven classification criteria so that the number of MUP assignments made reflects the signal complexity and the number of erroneous assignments is kept sufficiently low. The ability of the ACC to adjust to specific signal characteristics suggests that it can be successfully applied to a wide variety of EMG signals.     

Non-invasive assessment of single motor unit mechanomyographic response and twitch force by spike-triggered averaging

A method for non-invasive assessment of single motor unit (MU) properties from electromyographic (EMG), mechanomyographic (MMG) and force signals is proposed. The method is based on the detection and classification of single MU action potentials from interference multichannel surface EMG signals and on the spike-triggered average of the MMG (detected by an accelerometer) and force signals. The first dorsal interosseous (FDI) and abductor digiti minimi (ADM) muscles were investigated at contraction levels of 2% and 5% of the maximum voluntary contraction (MVC) force. A third contraction was performed by selective activation of a single MU with surface MU action potential visual feedback provided to the subject. At 5% MVC, the mean (±standard error) single MU MMG peak-to-peak value was 11.0±1.8 mm s⁻² (N=17) and 32.3±6.5 mm s⁻² (N=20) for the FDI and AMD muscles, respectively. The peak of the twitch force was, at the same contraction livel, 7.41±1.34 mN and 14.42±2.92 mN, for the FDI and ADM muscles, respectively. The peak-to-peak value of the MMG was significantly different for the same MU at different contraction levels, indicating a non-linear summation of the single MU contributions. For the FDI muscle, the MMG peak-to-peak value of individual MUs was 21.5±7.8 mm s⁻², when such MUs were activated with visual feedback provided to the subject, whereas, for the same MUs, it was 11.8±3.8 mm s⁻², when the subject maintained a constant force level of 2% MVC. The method proposed allows the non-invasive assessment of single MU membrane and contractile properties during voluntary contractions.     

Effect of electrode dimensions on motor unit potentials

Different effects of longitudinal and transversal electrode dimensions on nerve or muscle single fibre action potentials detected monopolarly, were reported in the literature. The results were contradictory. We studied motor unit potentials (MUPs) detected at a large distance (typical of surface recording) on the basis of a mathematical model without source simplification. The MUPs were calculated as a single convolution of the first temporal derivative of a realistic intracellular action potential and MU impulse response. The spatial averaging of the MUPs by rectangular plate electrodes was performed through analytical integration of the MU impulse response over the electrode area. The effects of longitudinal dimension of the electrode were stronger than those of a transversal one. The effects were distance dependent. The longitudinal dimension of the electrode influenced the main phases (that reflected the excitation origin and propagation) more than the terminal phases (that reflected the excitation extinction at the muscle fibers' ends). This was due to differences in the character of the potential fields (quadrupole or dipole) during generation of individual MUP phases. It was shown that the relative weight of the individual MUP phases could be stressed or suppressed by a proper choice of electrode dimensions, position and orientation.     

Calculation of depth dose and dose per monitor unit for irregularly shaped electron fields: an addendum.

Electron beam output (dose/MU) is generally specified at the depth of maximum dose (zmax). The location of this point depends on beam energy, field size and field shape. Useful relationships have been developed to estimate zmax as a function of field size and beam energy. The formalism uses a pencil beam theory applied to circular fields.     

Detection volume of simulated electrode systems for recording sphincter muscle electromyogram

BACKGROUND: Recording surface electromyogram (EMG) signals from sphincter muscles has become of increasing interest due to potential applications in diagnosis or investigation of the mechanisms of incontinence. Recently developed probes allow high-resolution detection of EMG signal from the external anal sphincter. One of the main issues in the interpretation of experimental signals is the detection volume of the recording electrodes. METHODS: An analytical model of generation of EMG from the anal sphincter was applied to simulate single fiber action potentials varying the fiber length, conductivity and thickness of the mucosa, shape of the electrodes, and detection system (monopolar, bipolar, and double differential). RESULTS: The new probe is more selective than classical probes with big electrodes and large interelectrode distance. The decay of the recorded surface EMG action potentials with distance of the fiber was faster for increasing depth than axial distance (this is due to the geometry of the volume conductor, as indicated by comparison with simulations with a planar volume conductor). Point electrodes led to smaller detection volumes than rectangular electrodes, and the double differential system was the most selective recording configuration. The relative decrease of the detected potential generated by more distant fibers was lower for increasing thickness and conductivity of the mucosa. End-of-fiber components are enhanced by the circular geometry of sphincter muscles with respect to the case of a planar volume conductor. CONCLUSIONS: The detection volume of EMG recording systems from sphincter muscles extends more in the axial than in the depth direction and is affected by many parameters that cannot be estimated in practical situations, thus introducing a rather large variability in the muscle portion investigated among subjects. More selective information can be obtained using the recently developed multi-channel probe with respect to classical probes. Selectivity is increased with small electrodes and double differential recordings.     

A morphological analysis of the macro motor unit potential

The technique of macro EMG is used to investigate the motor unit architecture in a number of pathological conditions. Amplitude and area are the most commonly used criteria, but these parameters alone are not sufficient to assess the complexity of the macro MUP morphology. In an attempt to examine the morphology of the macro MUP in more detail, additional measures were investigated including, (i) average power, (ii) duration, and (iii) number of phases. Macro MUP duration was defined as the time parameter that contains a particular fraction (90%) of the total power of the potential. The above mentioned parameters were evaluated for normal subjects and for patients suffering with motor neuron disease (MND), spinal muscular atrophy (SMA), and Becker's muscular dystrophy (BMD). It is shown that high amplitude and average power macro MUPs give shorter macro MUP duration than macro MUPs with normal amplitude. In contrast, in low amplitude macro MUPs there is a tendency towards a higher duration measure, as compared with the duration of the normal amplitude macro MUPs. Also, t–test results for the duration measure gave a significant difference between the NOR–MND, and no significant difference between the NOR–BMD and NOR–SMA groups at P<0.05. Significant difference between the NOR and the three disease groups investigated was obtained for the parameters log amplitude, log area, and log average power. The number of phases was not significantly different between the NOR and the rest of the groups. In conclusion, the average power and duration parameters can possibly be used as additional discriminators to detect abnormalities of the macro motor unit potential in both needle and surface EMG but further investigation is necessary.     

Evidence of Potential Averaging over the Finite Surface of a Bioelectric Surface Electrode

Most bioelectric signals are not only functions of time but also exhibit a variation in spatial distribution. Surface EMG signals are often “summarized” by a large electrode. The effect of such an electrode is interpreted as averaging the potential at the surface of the skin beneath the electrode. We first introduce an electrical equivalent model to delineate this principle of averaging. Next, in a realistic finite element model of EMG generation, two outcome variables are evaluated to assess the validity of the averaging principle. One is the change in voltage distribution in the volume conductor after electrode application. The other is the change in voltage across the high impedance double layer between tissue and electrode. We found that the principle of averaging is valid, once the impedance of the double layer is sufficiently high. The simulations also revealed that skin conductivity plays a role. High-density surface EMG provided experimental evidence consistent with the simulation results. A grid with 120 small electrodes was placed over the thenar muscles of the hand. Electrical nerve stimulation assured a reproducible compound muscle response. The averaged grid response was compared with a single electrode matching the surface of the high-density electrodes. The experimental results showed relatively small errors indicating that averaging of the surface potential by the electrode is a valid principle under most practical conditions.