Diagnostic yield of noninvasive high spatial resolution electromyography in neuromuscular diseases

Fundamental Concepts of Bipolar and High-Density Surface EMG Understanding and Teaching for Clinical, Occupational, and Sport Applications: Origin, Detection, and Main Errors

Surface electromyography (sEMG) has been the subject of thousands of scientific articles, but many barriers limit its clinical applications. Previous work has indicated that the lack of time, competence, training, and teaching is the main barrier to the clinical application of sEMG. This work follows up and presents a number of analogies, metaphors, and simulations using physical and mathematical models that provide tools for teaching sEMG detection by means of electrode pairs (1D signals) and electrode grids (2D and 3D signals). The basic mechanisms of sEMG generation are summarized and the features of the sensing system (electrode location, size, interelectrode distance, crosstalk, etc.) are illustrated (mostly by animations) with examples that teachers can use. The most common, as well as some potential, applications are illustrated in the areas of signal presentation, gait analysis, the optimal injection of botulinum toxin, neurorehabilitation, ergonomics, obstetrics, occupational medicine, and sport sciences. The work is primarily focused on correct sEMG detection and on crosstalk. Issues related to the clinical transfer of innovations are also discussed, as well as the need for training new clinical and/or technical operators in the field of sEMG.

Two-stage binary classifier for neuromuscular disorders using surface electromyography feature extraction and selection

If surface electromyography (sEMG) can be used to determine neuromuscular disorders, it can diagnose conditions more easily than needle electromyography. In this study, sEMG during maximum voluntary isometric contraction and repetitive exercise was measured, and normal, myopathy, and neuropathy were classified with high accuracy using these signals. First, a two-stage binary classifier model was constructed to classify the patient group and the normal group and categorize the cases assigned to the patient group into myopathy and neuropathy groups. To this end, features related to muscle activity and muscle fatigue were extracted using activity analysis and frequency analysis of the sEMG signal. Since the features for high performance are different for each classifier, the features with statistical differences in the data of each class were selected for each classifier. The selected features and a two-stage binary classifier were distinguished with an accuracy of 86.9%. This shows an accuracy higher than 82.3%, which was found for the two-stage binary classifier without feature selection and 73.9% of the multi-classifier. Through this, the possibility of using sEMG to diagnose neuromuscular disorders was confirmed.

Correlation between Psoas Muscle Index and Degeneration of Spinal Back Muscle in Patients with Back Pain

Sarcopenia is characterized by a decline in systemic muscle mass and physical performance. Disc degeneration also causes back muscle atrophy. Therefore, we aimed to evaluate the influence of systemic muscle mass decline on back muscle atrophy and fatty infiltration compared to disc degeneration. We included 127 patients (65.54 ± 14.93 years) with back pain who underwent lumbar spine magnetic resonance imaging (MRI). Axial T2-weighted MRI data of the L4-5 and L5-S1 levels were used to measure the cross-sectional area (CSA) of the psoas and spinal muscles. The psoas index (cm²/m²) was used as a surrogate for systemic muscle mass. The Pfirrmann grading system was used to evaluate intervertebral disc degeneration. The functional area of the back muscles was calculated by subtracting the fat infiltration area from the CSA; the functional CSA ratio was calculated by dividing the functional CSA by the CSA. Image-processing software (ImageJ; National Institutes of Health, Bethesda, MD, USA) was used for analysis. Psoas index and aging significantly affected CSA and the ratio of functional CSA of the back muscles and multifidi. Disc degeneration did not significantly affect the back muscles beyond aging in patients with back pain. Males showed substantially higher CSA of the back muscles and multifidi than females; however, sex did not affect the functional CSA ratio of these muscles. Systemic muscle mass decline showed a more powerful influence on back muscle atrophy and fatty infiltration than disc degeneration. Therefore, proper evaluation of sarcopenia is needed for patients with chronic back pain and back muscle degeneration.

Surface EMG in Clinical Assessment and Neurorehabilitation: Barriers Limiting Its Use

This article addresses the potential clinical value of techniques based on surface electromyography (sEMG) in rehabilitation medicine with specific focus on neurorehabilitation. Applications in exercise and sport pathophysiology, in movement analysis, in ergonomics and occupational medicine, and in a number of related fields are also considered. The contrast between the extensive scientific literature in these fields and the limited clinical applications is discussed. The "barriers" between research findings and their application are very broad, and are longstanding, cultural, educational, and technical. Cultural barriers relate to the general acceptance and use of the concept of objective measurement in a clinical setting and its role in promoting Evidence Based Medicine. Wide differences between countries exist in appropriate training in the use of such quantitative measurements in general, and in electrical measurements in particular. These differences are manifest in training programs, in degrees granted, and in academic/research career opportunities. Educational barriers are related to the background in mathematics and physics for rehabilitation clinicians, leading to insufficient basic concepts of signal interpretation, as well as to the lack of a common language with rehabilitation engineers. Technical barriers are being overcome progressively, but progress is still impacted by the lack of user-friendly equipment, insufficient market demand, gadget-like devices, relatively high equipment price and a pervasive lack of interest by manufacturers. Despite the recommendations provided by the 20-year old EU project on "Surface EMG for Non-Invasive Assessment of Muscles (SENIAM)," real international standards are still missing and there is minimal international pressure for developing and applying such standards. The need for change in training and teaching is increasingly felt in the academic world, but is much less perceived in the health delivery system and clinical environments. The rapid technological progress in the fields of sensor and measurement technology (including sEMG), assistive devices, and robotic rehabilitation, has not been driven by clinical demands. Our assertion is that the most important and urgent interventions concern enhanced education, more effective technology transfer, and increased academic opportunities for physiotherapists, occupational therapists, and kinesiologists.

Non-invasive assessment of motor unit activation in relation to motor neuron level and lesion location in stroke and spinal muscular atrophy

BACKGROUND

Neuromuscular disorders e.g. spinal muscular atrophy and stroke have a negative impact on functional movement capability. These disorders affect lower and upper motor neurons respectively.

METHODS

In this study high spatial resolution electromyography was used to record the motor unit activity in 3 groups: healthy subjects, a spinal muscular atrophy group and a stroke group. 7 clinically sensitive parameters were used to analyze the activation patterns of a few motor units.

FINDINGS

In the case of spinal muscular atrophy there was no effect on motor unit activation but on their number. Stroke was characterized by fewer active motor units and a significantly reduced firing rate with low variability.

INTERPRETATION

The results suggest, that for stroke, information from the brain is modified thereby resulting in motor units firing at their natural frequency. Thus, high spatial resolution electromyography and the chosen parameters facilitate non-invasive, objective differentiation and analysis of the activation patterns of motor units in neuromuscular disorders.

Standards of instrumentation of EMG

Standardization of Electromyography (EMG) instrumentation is of particular importance to ensure high quality recordings. This consensus report on "Standards of Instrumentation of EMG" is an update and extension of the earlier IFCN Guidelines published in 1999. First, a panel of experts in different fields from different geographical distributions was invited to submit a section on their particular interest and expertise. Then, the merged document was circulated for comments and edits until a consensus emerged. The first sections in this document cover technical aspects such as instrumentation, EMG hardware and software including amplifiers and filters, digital signal analysis and instrumentation settings. Other sections cover the topics such as temporary storage, trigger and delay line, averaging, electrode types, stimulation techniques for optimal and standardised EMG examinations, and the artefacts electromyographers may face and safety rules they should follow. Finally, storage of data and databases, report generators and external communication are summarized.

Age related neuromuscular changes in sEMG of m. Tibialis Anterior using higher order statistics (Gaussianity & linearity test)

Age-associated changes in the surface electromyogram (sEMG) of Tibialis Anterior (TA) muscle can be attributable to neuromuscular alterations that precede strength loss. We have used our sEMG model of the Tibialis Anterior to interpret the age-related changes and compared with the experimental sEMG. Eighteen young (20-30 years) and 18 older (60-85 years) performed isometric dorsiflexion at 6 different percentage levels of maximum voluntary contractions (MVC), and their sEMG from the TA muscle was recorded. Six different age-related changes in the neuromuscular system were simulated using the sEMG model at the same MVCs as the experiment. The maximal power of the spectrum, Gaussianity and Linearity Test Statistics were computed from the simulated and experimental sEMG. A correlation analysis at α=0.05 was performed between the simulated and experimental age-related change in the sEMG features. The results show the loss in motor units was distinguished by the Gaussianity and Linearity test statistics; while the maximal power of the PSD distinguished between the muscular factors. The simulated condition of 40% loss of motor units with halved the number of fast fibers best correlated with the age-related change observed in the experimental sEMG higher order statistical features. The simulated aging condition found by this study corresponds with the moderate motor unit remodelling and negligible strength loss reported in literature for the cohorts aged 60-70 years.

Age-related motor unit remodeling in the Tibialis Anterior

Limited studies exist on the use of surface electromyogram (EMG) signal features to detect age-related motor unit remodeling in the Tibialis Anterior. Motor unit remodeling leads to declined muscle strength and force steadiness during submaximal contractions which are factors for risk of falls in the elderly. This study investigated the remodeling phenomena in the Tibialis Anterior using sample entropy and higher order statistics. Eighteen young (26.1 ± 2.9 years) and twelve elderly (68.7 ± 9.0 years) participants performed isometric dorsiflexion of the ankle at 20% maximal voluntary contraction (MVC) and their Tibialis Anterior (TA) EMG was recorded. Sample entropy, Gaussianity and Linearity Test statistics were calculated from the recorded EMG for each MVC. Shapiro-Wilk test was used to determine normality, and either a two-tail student t-test or Wilcoxon rank sum test was performed to determine significant difference in the EMG features between the young and old cohorts. Results show age-related motor unit remodeling to be depicted by decreased sample entropy (p <; 0.1), increased non-Gaussianity (p <; 0.05) and lesser degree of linearity in the elderly. This is due to the increased sparsity of the MUAPs as a result of the denervation-reinnervation process, and the decrease in total number of motor units.

"Clustering Index method": a new technique for differentiation between neurogenic and myopathic changes using surface EMG

OBJECTIVE

To establish a non-invasive and quantitative analysis method using single-channel surface EMG (SEMG) for diagnosing neurogenic and myopathic changes.

METHODS

The subjects consisted of 66 healthy controls, 12 patients with neurogenic diseases, and 18 patients with myopathic diseases. The tibialis anterior muscle was examined using a belly to the adjacent bone lead. From each subject, 20-40 signals of 1 s length were collected of various strengths. A new parameter, the "Clustering Index (CI)", was developed to quantify the uneven distribution of the SEMG signal, and was plotted against the SEMG area. The results were expressed as the Z-score of each subject calculated using linear regression from the normative data.

RESULTS

When ±2.5 was used as the cut-off value of the Z-score, the specificity was 95%, whereas the sensitivity was 92% (11/12) and 61% (11/18) for the neurogenic and myopathic patients, respectively. There was no overlap of the Z-score values between the neurogenic and myopathic groups.

CONCLUSIONS

The CI method achieved a reasonably high diagnostic yield in detecting neurogenic or myopathic changes.

SIGNIFICANCE

This is a new simple and quantitative analysis method using SEMG with good reproducibility, and is promising as a non-invasive complement to needle EMG.

Multiscale entropy-based approach to automated surface EMG classification of neuromuscular disorders

We introduce a novel method for an automatic classification of subjects to those with or without neuromuscular disorders. This method is based on multiscale entropy of recorded surface electromyograms (sEMGs) and support vector classification. The method was evaluated on a single-channel experimental sEMGs recorded from biceps brachii muscle of nine healthy subjects, nine subjects with muscular and nine subjects with neuronal disorders, at 10%, 30%, 50%, 70% and 100% of maximal voluntary contraction force. Leave-one-out cross-validation was performed, deploying binary (healthy/patient) and three-class classification (healthy/myopathic/neuropathic). In the case of binary classification, subjects were distinguished with 81.5% accuracy (77.8% sensitivity at 83.3% specificity). At three-class classification, the accuracy decreased to 70.4% (myopathies were recognized with a sensitivity of 55.6% at specificity 88.9%, neuropathies with a sensitivity of 66.7% at specificity 83.3%). The proposed method is suitable for fast and non-invasive discrimination of healthy and neuromuscular patient groups, but it fails to recognize the type of pathology.

The behavior of action potential conduction velocity on isokinetic knee extension tests

The present study investigates the behavior of action potential conduction velocity (CV) on each repetition of an isokinetic test set and on each set as a whole. A total of seven healthy men (27.7 ± 2.8 yrs, 1.74 ± 0.06 m, and 79.6 ± 11.0 Kg) performed 3 (three) sets of 10 (ten) maximal concentric repetitions of dominant knee extension at 60°/s on an isokinetic dynamometer, with 1 minute of rest interval between the sets. The surface electromyographic (SEMG) signals were recorded from the vastus lateralis muscle during the exercises. CV was estimated with a spectral matching method which requires the SEMG acquisition technique based on a flexible linear array of electrodes (here used with 8 electrodes and 5 mm inter-electrode distance). With the view to minimize the factors other than fatigue that also influence the CV behavior, only the extension phase of the isokinetic exercise repetition was considered for measurements. Results showed that CV usually increases during a single repetition whereas it has a decreasing tendency along the isokinetic set seen as a whole.

Multichannel SEMG in clinical gait analysis: a review and state-of-the-art

BACKGROUND

Application of surface electromyography (SEMG) to the clinical evaluation of neuromuscular disorders can provide relevant "diagnostic" contributions in terms of nosological classification, localization of focal impairments, detection of pathophysiological mechanisms, and functional assessment.

METHODS

The present review article elaborates on: (i) the technical aspects of the myoelectric signals acquisition within a protocol of clinical gait analysis (multichannel recording, surface vs. deep probes, electrode placing, encumbrance effects), (ii) the sequence of procedures for the subsequent data processing (filtering, averaging, normalization, repeatability control), and (iii) a set of feasible strategies for the final extraction of clinically useful information.

FINDINGS

Relevant examples of SEMG application to functional diagnosis are provided.

INTERPRETATION

Emphasis is given to the key role of SEMG along with kinematic and kinetic analysis, for non-invasive assessment of relevant pathophysiological mechanisms potentially hindering the gait function, such as changes in passive muscle-tendon properties (peripheral non-neural component), paresis, spasticity, and loss of selectivity of motor output in functionally antagonist muscles.

American Association of Neuromuscular & Electrodiagnostic Medicine evidenced-based review: use of surface electromyography in the diagnosis and study of neuromuscular disorders

Surface electromyography (sEMG) measures myoelectrical signals recorded from sensors placed on the skin surface. The non-invasive nature of sEMG makes it a potentially useful technology for studying diseases of muscle and nerve. Reviews published by the American Association of Neuromuscular and Electrodiagnostic Medicine (AANEM) and the Therapeutics and Technology Assessment Subcommittee of the American Academy of Neurology (AAN), covering 1964-1994 and 1952-1998, respectively, concluded that sEMG adds no clinical utility over conventional needle EMG (nEMG) for the diagnosis of neuromuscular disease. The AANEM sEMG task force reevaluated the diagnostic utility and added value of this technology for the study of neuromuscular disease based on a contemporary review of relevant literature published between January 1994 and February 2006. The present review concludes that sEMG may be useful to detect the presence of neuromuscular disease (level C rating, class III data), but there are insufficient data to support its utility for distinguishing between neuropathic and myopathic conditions or for the diagnosis of specific neuromuscular diseases. sEMG may be useful for additional study of fatigue associated with post-poliomyelitis syndrome and electromechanical function in myotonic dystrophy (level C rating, class III data).

Spherical classification of wavelet transformed EMG intensity patterns

Electromyograms of different muscles can be submitted to a wavelet-transform and arranged in a Multi-Muscle Pattern (MMP). The MMP represents the intensity of the EMG signals of a number of muscles simultaneously in time/frequency space. As previously shown, the MMPs can be represented by points in an Euclidian vector space that was called pattern space. The variability of the MMPs is represented by the distribution of the scattered points in pattern space. The purpose of this study was to investigate the distribution of the points and use the properties of the distribution to classify MMPs. The first task was to test whether the points representing a group of MMPs were located between the inner and outer boundary of a sphere-like domain in whitened pattern space as theoretically predicted. The mean of these points and thus of the MMPs is represented by a point at the center of the sphere. The hypothesis was that the spheres representing points of the MMPs of barefoot and shod runners were sufficiently separated and distinguishable in pattern space to allow classification of the runners according to their shod condition. The results confirmed the hypothesis and revealed that the recognition rate was over 80%. One can conclude and generalize that the points representing MMPs recorded for a certain condition reside between the inner and outer boundary of the sphere. The classification based on the spherical feature represents a much better discrimination than one based on the distance from the mean.

Changes in intracellular action potential profile affect parameters used in turns/amplitude analysis

The influence of changes in the intracellular action potential (IAP) spatial profile on motor unit potentials (MUPs), number of turns per second (NTs), and mean turn amplitude were simulated and analyzed. We show why measurement of NTs was "the best indicator of neurogenic affection" and why the lower diagnostic yield of turns/amplitude analysis in myopathy could be due to changes in IAP shape caused by elevated free calcium concentration. The results explain the complications observed when interference electromyographic signals obtained during high levels of isometric contractions were analyzed. We show that, in contrast to earlier assumptions, the effect of increased IAP spike duration on NTs was stronger than that of a decrease in muscle fiber propagation velocity (MFPV). The decrease in the NTs could occur without a drop-out of MUs and/or a decrease in their firing rates, and without a change in MFPV and synchronous firing.

Clinical applications of high-density surface EMG: A systematic review

High density-surface EMG (HD-sEMG) is a non-invasive technique to measure electrical muscle activity with multiple (more than two) closely spaced electrodes overlying a restricted area of the skin. Besides temporal activity HD-sEMG also allows spatial EMG activity to be recorded, thus expanding the possibilities to detect new muscle characteristics. Especially muscle fiber conduction velocity (MFCV) measurements and the evaluation of single motor unit (MU) characteristics come into view. This systematic review of the literature evaluates the clinical applications of HD-sEMG. Although beyond the scope of the present review, the search yielded a large number of "non-clinical" papers demonstrating that a considerable amount of work has been done and that significant technical progress has been made concerning the feasibility and optimization of HD-sEMG techniques. Twenty-nine clinical studies and four reviews of clinical applications of HD-sEMG were considered. The clinical studies concerned muscle fatigue, motor neuron diseases (MND), neuropathies, myopathies (mainly in patients with channelopathies), spontaneous muscle activity and MU firing rates. In principle, HD-sEMG allows pathological changes at the MU level to be detected, especially changes in neurogenic disorders and channelopathies. We additionally discuss several bioengineering aspects and future clinical applications of the technique and provide recommendations for further development and implementation of HD-sEMG as a clinical diagnostic tool.

The role of different EMG methods in evaluating myopathy

For the diagnosis of myopathy, EMG may have an important role along with blood tests, muscle biopsies and genetic testing. This review evaluates different EMG methods in the diagnosis of myopathy. These include manual analysis of individual motor unit potentials and multi-motor unit potential analysis sampled at weak effort. At high effort, turns-amplitude analyses such as the cloud analysis and the peak ratio analysis have a high diagnostic yield. The EMG can seldom be used to differentiate between different types of myopathy. In the channelopathies, myotonia, exercise test and cooling of the muscle are helpful. Macro-EMG, single-fibre EMG and muscle fibre conduction velocity analysis have a limited role in myopathy, but provide information about the changes seen. Analysis of the firing rate of motor units, power spectrum analysis, as well as multichannel surface EMG may have diagnostic potential in the future. EMG is of great importance in the diagnosing of patients with myopathy, preferably a needle electrode and quantitative analyses should be used. A combination of a method at weak effort as well as a method at stronger effort seems optimal.

Signal-dependent wavelets for electromyogram classification

In the study, an efficient method to perform supervised classification of surface electromyogram (EMG) signals is proposed. The method is based on the choice of a relevant representation space and its optimisation with respect to a training set. As EMG signals are the summation of compact-support waveforms (the motor unit action potentials), a natural tool for their representation is the discrete dyadic wavelet transform. The feature space was thus built from the marginals of a discrete wavelet decomposition. The mother wavelet was designed to minimise the probability of classification error estimated on the learning set (supervised classification). As a representative example, the method was applied to simulate surface EMG signals generated by motor units with different degrees of short-term synchronisation. The proposed approach was able to distinguish surface EMG signals with degrees of synchronisation that differed by 10%, with a misclassification rate of 8%. The performance of a spectral-based classification (error rate approximately 33%) and of the classification with Daubechies wavelet (21%) was significantly poorer than with the proposed wavelet optimisation. The method can be used for a number of different application fields of surface EMG classification, as the feature space is adapted to the characteristics of the signal that discriminate between classes.

Électromyographie de surface et fonction musculaire en pathologie

Surface electromyography (SEMG) had been and is still widely used in kinesiology and fatigue studies. Its use in routine clinical neurophysiology remains limited. Patients are requiring non-invasive EMG, which could also benefit to physicians and health care system looking for tools to evaluate muscle function in neuromuscular diseases as well as for therapeutic trials. This is the aim of our clinical studies. We apply SEMG envelope signal analysis acquired from maximal voluntary contractions, and the related compound muscle action potential (CMAP). These unspecific parameters cannot be used for neuromuscular diseases diagnosis, objective under study by many research teams. In nerve lesions follow-up studies, our SEMG procedure is related to motor clinical progression. We are currently evaluating it in chronic neuromuscular diseases. The respective contribution in neuromuscular disorders of the different neurophysiology techniques has still to be confirmed, and compared to force measurement by manual or quantitative testing, dynamometry, other suggested techniques (spectroscopy, imaging) as well as functional scales.

Topographical Characteristics of Motor Units of the Lower Facial Musculature Revealed by Means of High-Density Surface EMG

The objective of this study was to systematically characterize motor units (MUs) of the musculature of the lower face. MU endplate positions and principal muscle fiber orientations relative to facial landmarks were identified. This was done by the analysis of motor unit action potentials (MUAPs) in the surface electromyogram. Thirteen specially trained, healthy subjects performed selective contractions of the depressor anguli oris, depressor labii inferioris, mentalis, and orbicularis oris inferior muscles. Signals were recorded using recently developed, 0.3-mm thin and flexible high-density surface electromyography (sEMG) grids (120 channels). For each subject and each muscle and for different low contraction levels, representative MUAPs ("MU fingerprints") were extracted from the raw sEMG data according to their spatiotemporal amplitude characteristics. We then topographically characterized the lower facial MUs' endplate zones and main muscle fiber orientations on the individual faces of the subjects. These topographical MU parameters were spatially warped to correct for the different sizes and shapes of the faces of individual subjects. This electrophysiological study revealed a distribution of the lower facial MU endplates in more or less restricted, distinct clusters on the muscle often with eccentric locations. The results add substantially to the basic neurophysiologic and anatomical knowledge of the complex facial muscle system. They can also be used to establish objective guidelines for placement of conventional (surface or needle) EMG electrodes as well as for clinical investigations on neuromuscular diseases affecting the facial musculature. The localized endplate positions may also indicate optimal locations for botulinum toxin injection in the face.

Clinical applications of surface electromyography in neuromuscular disorders

Surface electromyography (SEMG) is still rarely used in clinical settings for the detection and analysis of myoelectric signals. The electromyographic signal detected on the skin surface includes information from a greater proportion of the muscle of interest than conventional clinical EMG, acquired using needle electrodes. SEMG is therefore more representative than the localised, and thus very selective needle EMG signals currently used. However, both reliability and interpretation of surface EMG need to be questioned. This review looks at the studies concerned with the characterisation of neuromuscular pathologies using EMG parameters. After introducing principles and limitations of surface EMG, an overview of the main results obtained in clinical settings is presented and discussed. There is a particular focus on high spatial resolution surface EMG as it is currently the best compromise between the selectivity of needle EMG and the representative nature of classical SEMG. Several perspectives are proposed that underline the fact that surface EMG is an evolving discipline and should be worthy of a place in routine clinical examinations.

Repeatability of surface EMG parameters at various isometric contraction levels and during fatigue using bipolar and Laplacian electrode configurations

The objective of this work was to assess the repeatability of two surface electromyographic (sEMG) recording techniques, the classical bipolar configuration and a Laplacian configuration to document their ability to provide reliable information during follow-up studies. The signals were recorded on 10 healthy subjects during voluntary isometric contractions of the biceps brachii muscle at different constant contraction levels. Slopes, area ratios (at 60% of the maximal voluntary contraction (MVC)) and initial values (at 20%, 40%, 60%, 80% and 100% MVC) of the root mean square (RMS), the mean power frequency (MPF) and the muscle fibre conduction velocity (CV) were estimated. Experimental sessions were repeated on three different days with both electrode sets to evaluate the repeatability of sEMG parameter estimates. Classical results were observed, such as an increase in the RMS and the CV with the contraction level. Only initial values of RMS and MPF were shown to be dependent on electrode type. These two parameters presented intra-class correlation coefficient values higher than .80 for high contraction levels. On the whole, the repeatability of the measures was good; however it was better for all sEMG parameter estimates with bipolar electrodes than Laplacian electrodes. Because a bipolar configuration is less selective than a Laplacian one, it provides a global view of muscular activity, which is more repeatable, hence more suitable for follow-up studies.

Assessment of Average Muscle Fiber Conduction Velocity From Surface EMG Signals During Fatiguing Dynamic Contractions

In this paper, we propose techniques of surface electromyographic (EMG) signal detection and processing for the assessment of muscle fiber conduction velocity (CV) during dynamic contractions involving fast movements. The main objectives of the study are: 1) to present multielectrode EMG detection systems specifically designed for dynamic conditions (in particular, for CV estimation); 2) to propose a novel multichannel CV estimation method for application to short EMG signal bursts; and 3) to validate on experimental signals different choices of the processing parameters. Linear adhesive arrays of electrodes are presented for multichannel surface EMG detection during movement. A new multichannel CV estimation algorithm is proposed. The algorithm provides maximum likelihood estimation of CV from a set of surface EMG signals with a window limiting the time interval in which the mean square error (mse) between aligned signals is minimized. The minimization of the windowed mse function is performed in the frequency domain, without limitation in time resolution and with an iterative computationally efficient procedure. The method proposed is applied to signals detected from the vastus laterialis and vastus medialis muscles during cycling at 60 cycles/min. Ten subjects were investigated during a 4-min cycling task. The method provided reliable assessment of muscle fatigue for these subjects during dynamic contractions.

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

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

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

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

A thin, flexible multielectrode grid for high-density surface EMG

Although the value of high-density surface electromyography (sEMG) has already been proven in fundamental research and for specific diagnostic questions, there is as yet no broad clinical application. This is partly due to limitations of construction principles and application techniques of conventional electrode array systems. We developed a thin, highly flexible, two-dimensional multielectrode sEMG grid, which is manufactured by using flexprint techniques. The material used as electrode carrier (Polyimid, 50 microm thick) allows grids to be cut out in any required shape or size. One universal grid version can therefore be used for many applications, thereby reducing costs. The reusable electrode grid is attached to the skin by using specially prepared double-sided adhesive tape, which allows the selective application of conductive cream only directly below the detection surfaces. To explore the practical possibilities, this technique was applied in single motor unit analysis of the facial musculature. The high mechanical flexibility allowed the electrode grid to follow the skin surface even in areas with very uneven contours, resulting in good electrical connections in the whole recording area. The silverchloride surfaces of the electrodes and their low electrode-to-skin impedances guaranteed high baseline stability and a low signal noise level. The electrode-to-skin attachment proved to withstand saliva and great tensile forces due to mimic contractions. The inexpensive, universally adaptable and minimally obstructive sensor allows the principal advantages of high-density sEMG to be extended to all skeletal muscles accessible from the skin surface and may lay the foundation for more broad clinical application of this noninvasive, two-dimensional sEMG technique.

Reproducibility of muscle-fiber conduction velocity estimates using multichannel surface EMG techniques

The aim of this study was to assess the reproducibility of muscle-fiber conduction velocity (MFCV) estimates obtained from multichannel surface electromyographic (EMG) recordings. Surface EMG signals were collected with a matrix of 61 electrodes during isometric, submaximal (50% of the maximal voluntary contraction torque) contractions of the biceps brachii muscle. Conduction velocity was estimated using multichannel maximum likelihood techniques. Reproducibility of MFCV estimates was assessed varying the number of signals (two to seven) used for the estimate and the distance between detection points (5-30 mm). Intraclass correlation coefficient (ICC) of both initial MFCV values and their rates of change with fatigue increased when increasing number of signals and distance between detection points. ICC of initial MFCV was negative using two signals for MFCV estimate, and it increased to approximately 75% with six to seven signals. Thus, reproducibility of MFCV estimates may be improved significantly using advanced multichannel estimation methods with respect to classic two-channel techniques.

Comparison of spatial filter selectivity in surface myoelectric signal detection: Influence of the volume conductor model

Spatial filters are used for increasing selectivity in surface EMG signal detection. The study investigated the importance of the description of the volume conductor to the inference of conclusions on comparing filter selectivity from simulation analyses. A cylindrical multi-layer description of the volume conductor was used for the simulation analysis. Different anatomies were analysed with this model, and results on filter selectivity were compared. The longitudinal single (LSD), double (LDD) and normal double differential (Laplacian, NDD) filters were investigated. Largely different conclusions could be drawn when comparing filter selectivity resulting from simulations with different volume conductor models. A filter that performed best with a particular anatomy could be the poorest with another anatomy. With a bone-muscle model and superficial fibres, the ratio between peak-to-peak values of the propagating and non-propagating signal components was approximately 220% for LDD and LSD and lower than for NDD (approximately 290%). With a bone-muscle-fat-skin model, LSD performed significantly worse (150%) than both LDD and NDD, which showed similar performances (approximately 300%). Similarly, if the lateral distance of the recording was increased by 10 degrees, the signal amplitude was reduced to 2% with LSD and LDD and to 4% with NDD. With another anatomy, LSD and LDD reduced signal amplitude to 20-25%, and NDD reduced it to 4%. Similar considerations could be drawn for other selectivity indexes. Thus, modelling should be used carefully to infer conclusions on spatial selectivity and to indicate particular choices of spatial filters.

A novel approach for estimating muscle fiber conduction velocity by spatial and temporal filtering of surface emg signals

We describe a new method for the estimation of muscle fiber conduction velocity (CV) from surface electromyography (EMG) signals. The method is based on the detection of two surface EMG signals with different spatial filters and on the compensation of the spatial filtering operations by two temporal filters (with CV as unknown parameter) applied to the signals. The transfer functions of the two spatial filters may have different magnitudes and phases, thus the detected signals have not necessarily the same shape. The two signals are first spatially and then temporally filtered and are ideally equal when the CV value selected as a parameter in the temporal filters corresponds to the velocity of propagation of the detected action potentials. This approach is the generalization of the classic spectral matching technique. A theoretical derivation of the method is provided together with its fast implementation by an iterative method based on the Newton's method. Moreover, the lowest CV estimate among those obtained by a number of filter pairs is selected to reduce the CV bias due to nonpropagating signal components. Simulation results indicate that the method described is less sensitive than the classic spectral matching approach to the presence of nonpropagating signals and that the two methods have similar standard deviation of estimation in the presence of additive, white, Gaussian noise. Finally, experimental signals have been collected from the biceps brachii muscle of ten healthy male subjects with an adhesive linear array of eight electrodes. The CV estimates depended on the electrode location with positive bias for the estimates from electrodes close to the innervation or tendon regions, as expected. The proposed method led to significantly lower bias than the spectral matching method in the experimental conditions, confirming the simulation results.

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

Ability to estimate motor unit propagation velocity correctly using different two-channel methods for delay estimation and different non-invasive spatial filters was analysed by simulation. It was established that longitudinal double difference electrodes could be not a better choice than simple bipolar parallel electrodes. Spatial filtration with a new multi-electrode (performing difference between signals detected by two transversal double difference electrodes positioned along the muscle fibres) promises to give the best estimate. Delay estimation between reference points is more preferable than that based on the cross-correlation technique, which is considerably sensitive to the fundamental properties of the muscle fibre extracellular fields. Preliminary averaging and approximation of the appropriate parts of the signals around chosen reference points could reduce the larger noise sensitivity and the effects of local tissue inhomogeneities as well as eliminate the sampling problem. A correct estimate of the propagation velocity could be impossible, even in the case of not very deep motor units (15 or 10 mm, depending on the spatial filter used) with relatively long (about 120 mm) muscle fibres. In the case of fibres with asymmetrical location of the end-plates in respect to the fibre ends, the propagation velocity estimates could be additionally biased above the longer semilength of the motor unit fibres.

Multichannel surface EMG: basic aspects and clinical utility

The generation of the surface electromyogram (sEMG) is described with regard to the properties of the single muscle fiber action potential as source, the physical aspects of volume conduction and recording configuration, and the properties and firing pattern of motor units (MUs). The spatial aspect of the motor unit action potential (MUP) is emphasized in relation to the results of high-density, multichannel sEMG measurements. The endplate zone, depth, size, and position of MUs can be estimated. The use of muscle fiber conduction velocity measurements in channelopathies and the changes in pathological fatigue are described. Using the unique patterns of spatial spread of MUPs over the skin (MU fingerprint), MU classification and the determination of firing moments is done noninvasively. Clinical applications of high-density sEMG measurements are reviewed. Emerging possibilities provided by MUP size and fingerprint measurements in neuromuscular disease and motor control are discussed. We conclude that multichannel sEMG adds unique, and sometimes indispensable, spatial information to our knowledge of the motor unit.

Single motor unit analysis from spatially filtered surface electromyogram signals. Part I: spatial selectivity

The aim of the study was to compare experimentally, on the basis of single motor unit (MU) activities, the selectivity of different spatial filters commonly used to detect surface electromyogram (EMG) signals. Surface EMG signals were recorded from the biceps brachii and the upper trapezius muscle of five subjects using a two-dimensional (2D) electrode array consisting of 16 pin electrodes. The subjects performed isometric contractions at different elbow angles and shoulder abduction and flexion. The same monopolar surface EMG signals were filtered using longitudinal single and double differential, transverse single and double differential and normal double differential filters. From the single MU action potentials, extracted by automatic EMG decomposition, indexes of transverse (perpendicular with respect to the fibre direction) and longitudinal (along the fibre direction) selectivity were computed. The number of detected MUs was 46 for the upper trapezius, with the arms held in the sagittal plane, and 52 when the arms were held in the frontal plane; 85 MUs were identified from the biceps brachii contractions. The results showed that transverse selectivity was significantly higher for the 2D and transverse one-dimensional (1D) filters with respect to the 1D longitudinal filters, whereas longitudinal selectivity was higher (i.e. MU action potentials were shorter) for the 2D filter and the longitudinal double differential filter. In particular, the relative attenuation of potential amplitude moving 5 mm from the source was, on average (for the two muscles), 16.5% for the least selective filter in the transverse direction (longitudinal single differential) and 35.7% for the most selective one in the same direction (transverse double differential). The MU action potential duration was, on average, 13.8 ms for the most selective filter in the longitudinal direction (longitudinal double differential) and 18.7 ms for the least selective one (transverse double differential). The normal double differential filter resulted in spatial selectivity indexes that ware not statistically different in the two directions from those of the best filters in each direction.

Single motor unit analysis from spatially filtered surface electromyogram signals. Part 2: conduction velocity estimation

The aim of the study was to compare experimentally conduction velocity (CV) estimates obtained with different estimation methods based on surface electromyogram (EMG) signals detected using five spatial filters. The filters investigated were the longitudinal single and double differential, transverse single and double differential, and normal double differential. The same surface EMG signals detected as described in Part 1 were used in this work. CV was estimated with four commonly used delay estimation techniques, i.e. from the distance between the peak values of two waveforms (with and without polynomial interpolation around the peak), and by the maximum likelihood estimate (MLE) based on two or more surface EMG channels. The average standard deviation of CV estimation (for all the MUs and the two muscles together) was 0.61 m s(-1) and 0.79 m s(-1) for the peak method, with and without interpolation, respectively, and 0.50 m s(-1) and 0.31 m s(-1) for the MLE method, from two and more surface EMG channels, respectively. Moreover, the mean of CV estimates varied by as much as 1 m s(-1) depending on the spatial filter used and the method adopted for CV estimation. Considering the dependence on the spatial filter only, the average (over all estimation methods) CV estimates obtained with the five spatial filters were 4.32 m s(-1) (normal double differential), 4.23 m s(-1) (longitudinal double differential), 4.61 m s(-1) (transverse double differential), 4.64 m s(-1) (transverse single differential) and 4.03 m s(-1) (longitudinal single differential). It was concluded that the comparison of single MU CV values obtained in different studies is critical if different spatial filters and processing techniques are used for their estimation. Higher estimates of CV were attributed to a smaller reduction in non-travelling signal components and thus were assumed to be positively biased.

Selectivity of spatial filters for surface EMG detection from the tibialis anterior muscle

Many spatial filters have been proposed for surface electromyographic (EMG) signal detection. Although theoretical and modeling predictions on spatial selectivity are available, there are no extensive experimental validations of these techniques based on single motor unit (MU) activity detection. The aim of this study was to compare spatial selectivity of one- and two-dimensional (1-D and 2-D) spatial filters for EMG signal detection. Intramuscular and surface EMG signals were recorded from the tibialis anterior muscle of ten subjects. The simultaneous use of intramuscular wire and surface recordings (with the spike triggered averaging technique) allowed investigation of the activity of single MUs at the skin surface. The surface EMG signals were recorded with a grid of point electrodes (3 x 3 electrodes) and a ring electrode system at 15 locations over the muscle, with the wires detecting signals from the same intramuscular location. For most subjects, it was possible to classify, from the intramuscular recordings, the activity of the same MUs for all the contractions. The surface EMG signals were averaged with the intramuscularly detected MU action potentials as triggers. In this way, eight spatial filters--longitudinal and transversal, single and double differential (LSD, TSD, LDD, TDD), Laplacian (NDD), inverse binomial filter of the second order (IB2), inverse rectangle filter (IR), and differential ring system (C1)--could be compared on the basis of their spatial selectivity. The distance from the source (transversal with respect to the muscle fiber orientation) after which the surface detected potential did not exceed +/- 5% of the maximal peak-to-peak amplitude (detection distance) was statistically smaller for the 2-D systems and TDD than for the other filters. The MU action potential duration was significantly shorter with LDD and with the 2-D systems than with the other filters. The 2-D filters investigated (including C1) showed very similar performance and were, thus, considered equivalent from the point of view of spatial selectivity.

The linear electrode array: a useful tool with many applications

In this review we describe the basic principles of operation of linear electrode arrays for the detection of surface EMG signals, together with their most relevant current applications. A linear array of electrodes is a system which detects surface EMG signals in a number of points located along a line. A spatial filter is usually placed in each point for signal detection, so that the recording of EMG signals with linear arrays corresponds to the sampling in one spatial direction of a spatially filtered version of the potential distribution over the skin. Linear arrays provide indications on motor unit (MU) anatomical properties, such as the locations of the innervation zones and tendons, and the fiber length. Such systems allow the investigation of the properties of the volume conductor and its effect on surface detected signals. Moreover, linear arrays allow to estimate muscle fiber conduction velocity with a very low standard deviation of estimation (of the order of 0.1-0.2 m/s), thus providing reliable indications on muscle fiber membrane properties and their changes in time (for example with fatigue or during treatment). Conduction velocity can be estimated from a signal epoch (global estimate) or at the single MU level. In the latter case, MU action potentials are identified from the interference EMG signals and conduction velocity is estimated for each detected potential. In this way it is possible, in certain conditions, to investigate single MU control and conduction properties with a completely non-invasive approach. Linear arrays provide valuable information on the neuromuscular system properties and appear to be promising tools for applied studies and clinical research.

A new surface electromyography analysis method to determine spread of muscle fiber conduction velocities

Muscle fiber conduction velocity (MFCV) estimation from surface signals is widely used to study muscle function, e.g., in neuromuscular disease and in fatigue studies. However, most analysis methods do not yield information about the velocity distribution of the various motor unit action potentials. We have developed a new method-the interpeak latency method (IPL)-to calculate both the mean MFCV and the spread of conduction velocities in vivo, from bipolar surface electromyogram (sEMG) during isometric contractions. sEMG was analyzed in the biceps brachii muscle in 15 young male volunteers. The motor unit action potential peaks are automatically detected with a computer program. Associated peaks are used to calculate a mean MFCV and the SD. The SD is taken as a measure of the MFCV spread. The main finding is that the IPL method can derive a measure of MFCV spread at different contraction levels. In conclusion, the IPL method provides accurate values for the MFCV and additionally gives information about the scatter of conduction velocities.

Motor unit conduction velocity distribution estimation: assessment of two short-term processing methods

Muscle fibre conduction velocity (MFCV) can be used as an index of the structural and/or functional modifications that can occur during fatigue or pathological processes. Current evaluation of MFCV from surface electromyography (SEMG) classically produces an average value. However, a single mean value is not sufficient when modifications affect only a small part of the conduction velocity distribution. In such a case, an estimation of the whole motor unit conduction velocity distribution (MUCV) would be advantageous. The aim of this study was the evaluation of the quality of two short-term methods based on cross-correlation (CC) and peak-to-peak (PP) estimation. A comprehensive simulation program was used to generate signals with known MUCV distributions. The Dmax statistic of Kolmogorov-Smirnov was used as an error criterion to quantify the estimation error and to optimise the MUCV distribution computation algorithms. The minimum error was observed for an analysing window of 10ms for PP and 15ms for CC. Dmax was significantly lower for PP (0.195+/-0.054) than for CC (0.343+/-0.073). Various simulations showed the strong effect of the variance of the true distribution on the features of the estimated ones. Clinical data measured on the abductor pollicis brevis were studied. MUCV was estimated on a healthy subject (3.63+/-0.87ms(-1)), a patient suffering from a myopathy (2.73+/-0.51ms(-1)) and one suffering from a neuropathy (4.38+/-0.23ms(-1)). The results demonstrate the overall superiority of a peak-to-peak approach.

Effect of parameters altering with muscle fibre functional state on power spectra of spatially filtered extracellular potentials

We aimed to analyse the effect of parameters altered with muscle fibre functional state on power spectra (PS) and spectral characteristics of the signals detected from skeletal muscle fibres of finite length by bipolar or one-dimensional multi-electrodes oriented in parallel to the muscle fibres. The PS were calculated as the product of the power spectrum of the input signal (the first temporal derivative of the intracellular action potential (IAP)) and spatially filtered impulse response. A multi-electrode with an even number of poles, located above the end-plate or fibre end, reduces the effect of alterations in the propagation velocity and increases that of the IAP duration and after-potentials. Detection of the signals far from the end-plate and fibre ends reduces the effect of the IAP spike duration and increases that of the propagation velocity. Increasing the number of poles reduces the effect of after-potentials. A proper multi-electrode arrangement and position could help to separate and assess the relative alteration of individual parameters.

Surface electromyography using electrode arrays: a study of motor neuron disease

The use of electromyography (EMG) is limited, particularly in the investigation of children, by the invasive nature of needle electrodes. Surface electrode techniques are an attractive alternative but the detected signals are greatly influenced by volume conductor effects, thus making their interpretation problematic. Using finite element analysis we investigated the relationship between surface potential distribution and motor unit depth, incorporating anisotropic conductivity to model muscle tissue and a range of subcutaneous fat thicknesses. The modeling results were used to analyze data recorded with a 16-channel surface electrode array, from 10 normals subjects and 12 patients with motor neuron disease. Differences in the motor units between the two groups were statistically significant (P < 0.01) and are consistent with reinnervation and increased motor unit territory in the patient group. This noninvasive technique shows promise as a more acceptable alternative to the use of conventional needle electrodes for neurophysiological investigations.

The utility of interference pattern analysis

The interference pattern of the electrical activity of muscle can be quantified by amplitude measurements, different spike counting methods, and power spectrum analyses. Interference pattern analysis (IPA) methods are used to describe the degree of activation of different muscles, muscle fatigue, occupational work, muscles in chronic pain syndromes, disused muscle, and dystonic muscle treated with botulinum toxin. In patients with neuromuscular disorders, the turns/amplitude analysis is useful for diagnosis. High diagnostic yields can be obtained without force measurements, for example, by using the amplitude as an indicator of force (the peak ratio method) or plotting the amplitude against the turns (cloud analysis). The diagnostic possibilities of the power spectrum analysis and the motor unit firing rate obtained by decomposition techniques are still unclear.

Multielectrode surface EMG for noninvasive estimation of motor unit size

To noninvasively estimate the motor unit size, we present a novel surface electromyographic (EMG) measurement system consisting of a surface multielectrode with four-pin electrodes and a pair of surface-disk electrodes. Surface motor unit action potentials (MUAPs) were recorded with the multielectrode, in the so-called multielectrode surface EMG (MSEMG), which was spatially filtered to localize the sensing area and reduce the noise. In addition, a modified decomposition algorithm, considering the geometrical configuration of the multielectrode, was designed to identify the individual MUAPs in the measured MSEMG. The identified MUAP was subsequently used as the triggering source for the EMG signals recorded by the surface-disk electrodes. From a pool of 34 subjects with neuromuscular diseases and 14 normal subjects, the median amplitudes of surface-disk EMG after spike-triggered averaging, called MSEMG-MUAP, correlated well (r = 0.82, P < 0.0001) with those of macro EMG. Moreover, the MSEMG-MUAP recording during a ramp force contraction exhibited the common size principle phenomenon during motor unit recruitment. The results of this study demonstrate that the MSEMG-MUAP measurement is a feasible approach for estimating the motor unit size from the skin surface.

Estimation of the relationship between the noninvasively detected activity of single motor units and their characteristic pathological changes by modelling

Neuromuscular disorders are often related to specific changes in the structure of single motor units (MUs). One approach for the detection of these changes is high-spatial-resolution EMG (HSR-EMG), which allows non-invasive recording of the activity of a single MU. Early investigations with patients suffering from various neuromuscular disorders have shown that there is a distinct difference between the HSR-EMG signals of healthy volunteers, patients with muscular disorders, and patients with neuronal disorders. In this study, the relationship between typical HSR-EMG patterns and characteristic pathological changes in the structure of the MUs is considered. Therefore, a muscle model has been developed which is adapted to the physiological properties of the m. abductor pollicis brevis. The effects of the loss of single muscle fibres (muscular disorders) and the loss of entire MUs (neuronal disorders) on the HSR-EMG pattern have been simulated. These simulations show the same HSR-EMG patterns as seen in patients and healthy volunteers. As a consequence, it can be assumed that the muscle model is an appropriate tool for the simulation of HSR-EMG signals. Furthermore, the simulation results support the hypothesis that the typical changes in the HSR-EMG pattern found in patients with neuromuscular disorders can be attributed to the characteristic changes in the structure of the MUs.