The spatial integration effect of surface electrode detecting myoelectric signal

Tutorial. Surface EMG detection in space and time: Best practices

This tutorial is aimed to non-engineers using, or planning to use, surface electromyography (sEMG) as an assessment tool in the prevention, monitoring and rehabilitation fields. Its first purpose is to address the issues related to the origin and nature of the signal and to its detection (electrode size, distance, location) by one-dimensional (bipolar and linear arrays) and two-dimensional (grids) electrode systems while avoiding advanced mathematical, physical or physiological issues. Its second purpose is to outline best practices and provide general guidelines for proper signal detection. Issues related to the electrode-skin interface, signal conditioning and interpretation will be discussed in subsequent tutorials.

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

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

A Spatially Focused Method for High Density Electrode-Based Functional Brain Mapping Applications

Mapping the electric field of the brain with electrodes benefits from its superior temporal resolution but is prone to low spatial resolution property comparing with other modalities such as fMRI, which can directly impact the precision of clinical diagnosis. Simulations show that dense arrays with straightforwardly miniaturized electrodes in terms of size and pitch may not improve the spatial resolution but only strengthen the cross coupling between adjacent channels due to volume conduction. We present a new spatially focused method to improve the electrode spatial selectivity and consequently suppress the neural signal coupling from the sources in the vicinity. Compared with existing spatial filtering methods with fixed coefficients, the proposed method is adaptively optimized for the geometric parameters of the recording electrode arrays, including electrode size, pitch and source depth. The effective spatial bandwidth, characterized as Radius of Half Power, can be reduced by about 70% for ECoG and the case of distant sources scenarios. The proposed method has been applied to the analysis of high-frequency oscillations (HFOs) in seizures to study the ictal pathway in the epileptogenic region. The results reveal lucid HFO wavefront propagation in both preictal and ictal stages due to a 75% reduction in the coupling effect. The results also show that a specific power threshold of preictal HFOs is needed in order to initiate an epileptic seizure. This demonstrates that our method indeed facilitates the investigation of complex neurobiological signals preprocessing applications.

Extracting extensor digitorum communis activation patterns using high-density surface electromyography

The extensor digitorum communis muscle plays an important role in hand dexterity during object manipulations. This multi-tendinous muscle is believed to be controlled through separate motoneuron pools, thereby forming different compartments that control individual digits. However, due to the complex anatomical variations across individuals and the flexibility of neural control strategies, the spatial activation patterns of the extensor digitorum communis compartments during individual finger extension have not been fully tracked under different task conditions. The objective of this study was to quantify the global spatial activation patterns of the extensor digitorum communis using high-density (7 × 9) surface electromyogram (EMG) recordings. The muscle activation map (based on the root mean square of the EMG) was constructed when subjects performed individual four finger extensions at the metacarpophalangeal joint, at different effort levels and under different finger constraints (static and dynamic). Our results revealed distinct activation patterns during individual finger extensions, especially between index and middle finger extensions, although the activation between ring and little finger extensions showed strong covariance. The activation map was relatively consistent at different muscle contraction levels and for different finger constraint conditions. We also found that distinct activation patterns were more discernible in the proximal–distal direction than in the radial–ulnar direction. The global spatial activation map utilizing surface grid EMG of the extensor digitorum communis muscle provides information for localizing individual compartments of the extensor muscle during finger extensions. This is of potential value for identifying more selective control input for assistive devices. Such information can also provide a basis for understanding hand impairment in individuals with neural disorders.

Spatial variability in cortex-muscle coherence investigated with magnetoencephalography and high-density surface electromyography

Cortex-muscle coherence (CMC) reflects coupling between magnetoencephalography (MEG) and surface electromyography (sEMG), being strongest during isometric contraction but absent, for unknown reasons, in some individuals. We used a novel nonmagnetic high-density sEMG (HD-sEMG) electrode grid (36 mm × 12 mm; 60 electrodes separated by 3 mm) to study effects of sEMG recording site, electrode derivation, and rectification on the strength of CMC. Monopolar sEMG from right thenar and 306-channel whole-scalp MEG were recorded from 14 subjects during 4-min isometric thumb abduction. CMC was computed for 60 monopolar, 55 bipolar, and 32 Laplacian HD-sEMG derivations, and two derivations were computed to mimic "macroscopic" monopolar and bipolar sEMG (electrode diameter 9 mm; interelectrode distance 21 mm). With unrectified sEMG, 12 subjects showed statistically significant CMC in 91-95% of the HD-sEMG channels, with maximum coherence at ∼25 Hz. CMC was about a fifth stronger for monopolar than bipolar and Laplacian derivations. Monopolar derivations resulted in most uniform CMC distributions across the thenar and in tightest cortical source clusters in the left rolandic hand area. CMC was 19-27% stronger for HD-sEMG than for "macroscopic" monopolar or bipolar derivations. EMG rectification reduced the CMC peak by a quarter, resulted in a more uniformly distributed CMC across the thenar, and provided more tightly clustered cortical sources than unrectifed sEMGs. Moreover, it revealed CMC at ∼12 Hz. We conclude that HD-sEMG, especially with monopolar derivation, can facilitate detection of CMC and that individual muscle anatomy cannot explain the high interindividual CMC variability.

Technology and instrumentation for detection and conditioning of the surface electromyographic signal: state of the art

The aim of this review is to present the state of the art of the technology of detection and conditioning systems for surface electromyography (sEMG). The first part of the manuscript focuses on the sEMG electrode system technology: the electrode classification, impedance, noise, transfer function, the spatial filtering effect of surface electrode configurations, the effects of electrode geometry, and location on the recorded sEMG signal. Examples of experimental sEMG signals are provided to show the potential value of high-density sEMG electrode grids and multichannel amplifiers that allow to add spatial information to the temporal information content of the sEMG signal. Furthermore, the results of a simple simulation are reported, in order to emphasize the effects of the subcutaneous tissue layers and of the detection volume on the recorded sEMG signal. The second part of the manuscript focuses on the sEMG amplifier technology: the front end amplifier characteristics for signal conditioning, the methods for stimulation artifact reduction, filtering methods, safety requirements, and the methods for analog-to-digital conversion of the sEMG signal.

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

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

Improved surface EMG electrode for measuring genioglossus muscle activity

Activation of the genioglossus (GG) muscles is necessary to maintain the patency of the upper airway. In the condition of obstructive sleep apnea (OSA) this mechanism fails and the possible role of fatigue in its pathogenesis is still not fully understood. In this paper, a new electrode design for recording the genioglossus surface electromyogram (sEMG) is presented. The new design differs from a widely used GG surface electrode in both electrode configuration (unilateral rather than bilateral) and electrode material (Ag-AgCl rather than stainless steel (SS)). The separate effects of these factors were evaluated during force-varying and fatiguing contractions on normal human subjects and using GG sEMG model simulations. Unilateral sEMG was found to have lower amplitude, lower frequency content and a different rate of change of median frequency during fatiguing contractions. It was shown to overcome several disadvantages posed by the bilateral configuration and be more selective. Ag-AgCl has more favorable impedance characteristics and resulted in greater signal amplitudes. It was concluded that the new design is more suitable for detecting GG sEMG and allows more reliable interpretation of changes in sEMG due to physiological mechanisms, thus providing a new methodology for studying GG function and the role of fatigue in OSA.

Efficient parameterization of MUAP signal for identification of MU and volume conductor characteristics using neural networks

The motor unit action potential (MUAPs) shapes depend on the anatomy and the physiology of the contracted muscle. The aim of this work is the identification of some characteristics of the motor unit (MU) and the volume conductor, namely the MU depth, the innervation zone width and the thickness of fat and skin layers based on MUAP signal parameters. The relationship between these characteristics and MUAP parameters are non-linear and complex. Thus, the use of the neural networks approach becomes an efficient tool to put in evidence this relationship. We have used the similarity and the homogeneity of the parameter criterions to choose which parameters are appropriate for the extraction. Two identification systems are presented and compared, a global system and a separate one. In order to evaluate the performance of each system, we have tested them using several simulated MUAP signals corrupted with additive Gaussian noise at different signal to noise ratios (SNR). A new test is introduced in which the electrode radius, the bar electrode dimensions and inclination angles for the detection system, fixed during the training process, are changed.

Differences in the activity of the muscles in the forearm of individuals with a congenital absence of the hand

The spectral content of the myoelectric signals from the muscles of the remnant forearms of three persons with congenital absences (CA) of their forearms was compared with signals from their intact contra-lateral limbs, similar muscles in three persons with acquired losses (AL) and seven persons without absences [no loss (NL)]. The observed bandwidth for the CA subjects was broader with peak energy between 200 and 300 Hz. While the signals from the contra-lateral limbs and the AL and NL subjects was in the 100-150 Hz range. The mean skew of the signals from the AL subjects was 46.3 +/- 6.7 and those with NL of 45.4 +/- 8.7, while the signals from those with CAs had a skew of 11.0 +/- 11. The structure of the muscles of one CA subject was observed ultrasonically. The muscle showed greater disruption than normally developed muscles. It is speculated that the myographic signal reflects the structure of the muscle which has developed in a more disorganized manner as a result of the muscle not being stretched by other muscles across the missing distal joint, even in the muscles that are used regularly to control arm prostheses.

Surface EMG analysis on normal subjects based on isometric voluntary contraction

The objective of this study was to compute reference SEMG values for normal subjects of 13 parameters extracted in the time, frequency and bispectrum domain, from the Biceps Brachii (BB) muscle generated under isometric voluntary contraction (IVC). SEMG signals were recorded from 94 subjects for 5s at 10, 30, 50, 70 and 100% of maximum voluntary contraction (MVC). The Wilcoxon signed rank test was applied to detect significant differences or not at p<0.05 between force levels for each of the 13 parameters. The main findings of this study can be summarized as follows: (i) The time domain parameters turns per second and number of zero crossings per second increase significantly with force level. (ii) The power spectrum median frequency parameter decreases significantly with force level, whereas maximum power and total power increase significantly with force level. (iii) The bispectrum parameter, maximum amplitude, increases significantly with force level with the exception the transition from 30% to 50% MVC. Although, the tests for Gaussianity and linearity show no significant difference with force level, the SEMG signal exhibits a more Gaussian distribution with increase of force up to 70% MVC. The SEMG linearity test, which is a measure of how constant the bicoherence index is in the bi-frequency domain, shows that the signal's bicoherence index is less constant (hence, the signal is less linear) at 70% of MVC compared to 10, 30, 50 and 100% MVC. (iv) The time domain parameters have good correlation between them as well as, between each one of them and maximum and total power. The median frequency has a good (negative) correlation with the bispectrum peak amplitude. (v) No significant differences exist between values based on gender or age. The findings of this study can further be used for the assessment of subjects suffering with neuromuscular disorders, or in the rehabilitation laboratory for monitoring the elderly or the disabled, or in the occupational medicine laboratory.

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

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

Surface electromyogram signal modelling

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

Advances in surface electromyographic signal simulation with analytical and numerical descriptions of the volume conductor

Surface electromyographic (EMG) signal modelling is important for signal interpretation, testing of processing algorithms, detection system design and didactic purposes. Various surface EMG signal models have been proposed in the literature. This study focuses on the proposal of a method for modelling surface EMG signals, using either analytical or numerical descriptions of the volume conductor for space-invariant systems, and on the development of advanced models of the volume conductor by numerical approaches, accurately describing the volume conductor geometry and the conductivity, as mainly done in the past, but also the conductivity tensor of the muscle tissue. For volume conductors that are space-invariant in the direction of source propagation, the surface potentials generated by any source can be computed by one-dimensional convolutions, once the volume conductor transfer function has been derived (analytically or numerically). Conversely, more complex volume conductors require a complete numerical approach. In a numerical approach, the conductivity tensor of the muscle tissue should be matched with the fibre orientation. In some cases (e.g. multi-pinnate muscles), accurate description of the conductivity tensor can be very complex. A method for relating the conductivity tensor of the muscle tissue, to be used in a numerical approach, to the curve describing the muscle fibres is presented and applied to investigate representatively a bi-pinnate muscle with rectilinear and curvilinear fibres. The study thus proposes an approach for surface EMG signal simulation in space invariant systems, as well as new models of the volume conductor using numerical methods.

Concentric-ring electrode systems for noninvasive detection of single motor unit activity

New recording techniques for detecting surface electromyographic (EMG) signals based on concentric-ring electrodes are proposed in this paper. A theoretical study of the two-dimensional (2-D) spatial transfer function of these recording systems is developed both in case of rings with a physical dimension and in case of line rings. Design criteria for the proposed systems are presented in relation to spatial selectivity. It is shown that, given the radii of the rings, the weights of the spatial filter can be selected in order to improve the rejection of low spatial frequencies, thus increasing spatial selectivity. The theoretical transfer functions of concentric systems are obtained and compared with those of other detection systems. Signals detected with the ring electrodes and with traditional one-dimensional and 2-D systems are compared. The concentric-ring systems show higher spatial selectivity with respect to the traditional detection systems and reduce the problem of electrode location since they are invariant to rotations. The results shown are very promising for the noninvasive detection of single motor unit (MU) activities and decomposition of the surface EMG signal into the constituent MU action potential trains.

A novel approach for precise simulation of the EMG signal detected by surface electrodes

We propose a new electromyogram generation and detection model. The volume conductor is described as a nonhomogeneous (layered) and anisotropic medium constituted by muscle, fat and skin tissues. The surface potential detected in space domain is obtained from the application of a two-dimensional spatial filter to the input current density source. The effects of electrode configuration, electrode size and inclination of the fibers with respect to the detection system are included in the transfer function of the filter. Computation of the signal in space domain is performed by applying the Radon transform; this permits to draw considerations about spectral dips and clear misunderstandings in previous theoretical derivations. The effects of generation and extinction of the action potentials at the fiber end plate and at the tendons are included by modeling the source current, without any approximation of its shape, as a function of space and time and by using again the Radon transform. The approach, based on the separation of the temporal and spatial properties of the muscle fiber action potential and of the volume conductor, includes the capacitive tissue properties.

Selectivity and sensitivity of intramuscular and transcutaneous electromyography electrodes

We evaluated the differences in selectivity and sensitivity of intramuscular fine-wire electrodes and transcutaneous electrodes in detecting dynamic electromyography (EMG) signals from extensor digitorum (EDC) and extensor carpi radialis (ECR) muscles during isolated EDC and ECR contractions in two able-bodied subjects. Intramuscular fine-wire electrodes differentiated EDC and ECR EMG activities better than transcutaneous electrodes, and intramuscular fine-wire electrodes recorded higher amplitude signals than transcutaneous electrodes. Data suggest that intramuscular fine-wire electrodes are more selective and sensitive than transcutaneous electrodes in detecting EMG signals from adjacent forearm muscles.

Surface EMG models: properties and applications

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

Modeling of surface myoelectric signals--Part I: Model implementation

The relationships between the parameters of active motor units (MU's) and the features of surface electromyography (EMG) signals have been investigated using a mathematical model that represents the surface EMG as a summation of contributions from the single muscle fibers. Each MU has parallel fibers uniformly scattered within a cylindrical volume of specified radius embedded in an anisotropic medium. Two action potentials, each modeled as a current tripole, are generated at the neuromuscular junction, propagate in opposite directions and extinguish at the fiber-tendon endings. The neuromuscular junctions and fiber-tendon endings are uniformly scattered within regions of specified width. Muscle fiber conduction velocity and average fiber length to the right and left of the center of the innervation zone are also specified. The signal produced by MU's with different geometries and conduction velocities are superimposed. Monopolar, single differential and double differential signals are computed from electrodes placed in equally spaced locations on the surface of the muscle and are displayed as functions of any of the model's parameters. Spectral and amplitude variables and conduction velocity are estimated from the surface signals and displayed as functions of any of the model's parameters. The influence of fiber-end effects, electrode misalignment, tissue anisotropy, MU's location and geometry are discussed. Part II of this paper will focus on the simulation and interpretation of experimental signals.

Using evoked EMG as a synthetic force sensor of isometric electrically stimulated muscle

A method for the estimation of the force generated by electrically stimulated muscle during isometric contraction is developed here. It is based upon measurements of the evoked electromyogram (EMG) [EEMG] signal. Muscle stimulation is provided to the quadriceps muscle of a paralyzed human subject using percutaneous intramuscular electrodes, and EEMG signals are collected using surface electrodes. Through the use of novel signal acquisition and processing techniques, as well as a mathematical model that reflects both the excitation and activation phenomena involved in isometric muscle force generation, accurate prediction of stimulated muscle forces is obtained for large time horizons. This approach yields synthetic muscle force estimates for both unfatigued and fatigued states of the stimulated muscle. In addition, a method is developed that accomplishes automatic recalibration of the model to account for day-to-day changes in pickup electrode mounting as well as other factors contributing to EEMG gain variations. It is demonstrated that the use of the measured EEMG as the input to a predictive model of muscle torque generation is superior to the use of the electrical stimulation signal as the model input. This is because the measured EEMG signal captures all of the neural excitation, whereas stimulation-to-torque models only reflect that portion of the neural excitation that results directly from stimulation. The time-varying properties of the excitation process cannot be captured by existing stimulation-to-torque models, but they are tracked by the EEMG-to-torque models that are developed here. This work represents a promising approach to the real-time estimation of stimulated muscle force in functional neuromuscular stimulation applications.

Uterine electromyography: a critical review

On the basis of a literature review, this work summarizes uterine animal and human electromyographic information obtained at cellular, myometrial, and abdominal levels during gestation and parturition. We show that both internal and external electromyograms occur in phase with intrauterine pressure increase and exhibit similar spectra, including a slow wave (0.01 < frequency < 0.03 Hz) probably because of mechanical artifacts and a fast wave whose frequency content can be subdivided into a low-frequency band always present in every contraction and a high-frequency band related to efficient parturition contractions. Application of classic spectral techniques to electromyogram envelopes has identified group propagation but not pacemaker areas. However, no time delay or classic propagation has been demonstrated by applying the same spectral techniques to the electromyogram itself, probably because of the nonlinearity and three-dimensional nature of the propagating process.