Effect of electrode dimensions on motor unit potentials

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.

Specificity of surface EMG recordings for gastrocnemius during upright standing

The relatively large pick-up volume of surface electrodes has for long motivated the concern that muscles other than that of interest may contribute to surface electromyograms (EMGs). Recent findings suggest however the pick-up volume of surface electrodes may be smaller than previously appreciated, possibly leading to the detection of surface EMGs insensitive to muscle activity. Here we combined surface and intramuscular recordings to investigate how comparably action potentials from gastrocnemius and soleus are represented in surface EMGs detected with different inter-electrode distances. We computed the firing instants of motor units identified from intramuscular EMGs detected from gastrocnemius and soleus while five participants stood upright. We used these instants to trigger and average surface EMGs detected from multiple skin regions along gastrocnemius. Results from 66 motor units (whereof 31 from gastrocnemius) revealed the surface-recorded amplitude of soleus action potentials was 6% of that of gastrocnemius and did not decrease for inter-electrode distances smaller than 4 cm. Gastrocnemius action potentials were more likely detected for greater inter-electrode distances and their amplitude increased steeply up to 5 cm inter-electrode distance. These results suggest that reducing inter-electrode distance excessively may result in the detection of surface EMGs insensitive to gastrocnemius activity without substantial attenuation of soleus crosstalk.

Analysis of deep brain stimulation electrode characteristics for neural recording

OBJECTIVE

Closed-loop deep brain stimulation (DBS) systems have the potential to optimize treatment of movement disorders by enabling automatic adjustment of stimulation parameters based on a feedback signal. Evoked compound action potentials (ECAPs) and local field potentials (LFPs) recorded from the DBS electrode may serve as suitable closed-loop control signals. The objective of this study was to understand better the factors that influence ECAP and LFP recording, including the physical presence of the electrode, the geometrical dimensions of the electrode, and changes in the composition of the peri-electrode space across recording conditions.

APPROACH

Coupled volume conductor-neuron models were used to calculate single-unit activity as well as ECAP responses and LFP activity from a population of model thalamic neurons.

MAIN RESULTS

Comparing ECAPs and LFPs measured with and without the presence of the highly conductive recording contacts, we found that the presence of these contacts had a negligible effect on the magnitude of single-unit recordings, ECAPs (7% RMS difference between waveforms), and LFPs (5% change in signal magnitude). Spatial averaging across the contact surface decreased the ECAP magnitude in a phase-dependent manner (74% RMS difference), resulting from a differential effect of the contact on the contribution from nearby or distant elements, and decreased the LFP magnitude (25% change). Reductions in the electrode diameter or recording contact length increased signal energy and increased spatial sensitivity of single neuron recordings. Moreover, smaller diameter electrodes (500 µm) were more selective for recording from local cells over passing axons, with the opposite true for larger diameters (1500 µm). Changes in electrode dimensions had phase-dependent effects on ECAP characteristics, and generally had small effects on the LFP magnitude. ECAP signal energy and LFP magnitude decreased with tighter contact spacing (100 µm), compared to the original dimensions (1500 µm), with the opposite effect on the ECAP at longer contact-to-contact distances (2000 µm). Finally, acute edema reduced the single neuron and population ECAP signal energy, as well as LFP magnitude, and glial encapsulation had the opposite effect, after accounting for loss of cells in the peri-electrode space.

SIGNIFICANCE

This study determined recording conditions and electrode designs that influence ECAP and LFP recording fidelity.

The extraction of neural information from the surface EMG for the control of upper-limb prostheses: emerging avenues and challenges

Despite not recording directly from neural cells, the surface electromyogram (EMG) signal contains information on the neural drive to muscles, i.e., the spike trains of motor neurons. Using this property, myoelectric control consists of the recording of EMG signals for extracting control signals to command external devices, such as hand prostheses. In commercial control systems, the intensity of muscle activity is extracted from the EMG and used for single degrees of freedom activation (direct control). Over the past 60 years, academic research has progressed to more sophisticated approaches but, surprisingly, none of these academic achievements has been implemented in commercial systems so far. We provide an overview of both commercial and academic myoelectric control systems and we analyze their performance with respect to the characteristics of the ideal myocontroller. Classic and relatively novel academic methods are described, including techniques for simultaneous and proportional control of multiple degrees of freedom and the use of individual motor neuron spike trains for direct control. The conclusion is that the gap between industry and academia is due to the relatively small functional improvement in daily situations that academic systems offer, despite the promising laboratory results, at the expense of a substantial reduction in robustness. None of the systems so far proposed in the literature fulfills all the important criteria needed for widespread acceptance by the patients, i.e. intuitive, closed-loop, adaptive, and robust real-time ( 200 ms delay) control, minimal number of recording electrodes with low sensitivity to repositioning, minimal training, limited complexity and low consumption. Nonetheless, in recent years, important efforts have been invested in matching these criteria, with relevant steps forwards.

Experimental and modelling investigation of surface EMG spike analysis

A pattern classification method based on five measures extracted from the surface electromyographic (sEMG) signal is used to provide a unique characterization of the interference pattern for different motor unit behaviours. This study investigated the sensitivity of the five sEMG measures during the force gradation process. Tissue and electrode filtering effects were further evaluated using a sEMG model. Subjects (N=8) performed isometric elbow flexion contractions from 0 to 100% MVC. The sEMG signals from the biceps brachii were recorded simultaneously with force. The basic building block of the sEMG model was the detection of single fibre action potentials (SFAPs) through a homogeneous, equivalent isotropic, infinite volume conduction medium. The SFAPs were summed to generate single motor unit action potentials. The physiologic properties from a well-known muscle model and motor unit recruitment and firing rate schemes were combined to generate synthetic sEMG signals. The following pattern classification measures were calculated: mean spike amplitude, mean spike frequency, mean spike slope, mean spike duration, and the mean number of peaks per spike. Root-mean-square amplitude and mean power frequency were also calculated. Taken together, the experimental data and modelling analysis showed that below 50% MVC, the pattern classification measures were more sensitive to changes in force than traditional time and frequency measures. However, there are additional limitations associated with electrode distance from the source that must be explored further. Future experimental work should ensure that the inter-electrode distance is no greater than 1cm to mitigate the effects of tissue filtering.

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.

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

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

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.

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.

Deconvolution estimation of motor unit conduction velocity distribution

A conduction velocity distribution (CVD) estimator that incorporates volume conductor modeling of the muscle voluntary response is introduced in this paper. The CVD estimates are obtained from two correlation functions, an autocorrelation and a cross, computed from myoelectric signal recorded at the skin surface. The performance of the proposed estimator is evaluated for simulated and experimental data. The study includes assessment of the estimator bias and standard deviation, as well as its sensitivity to errors in the model parameters. Simulations show its good performance in terms of estimator bias. A filtering technique also helps reduce its variance. However, the inaccuracy introduced in the estimation of model parameters considerably deteriorates the estimator performance.

Neither high-pass filtering nor mathematical differentiation of the EMG signals can considerably reduce cross-talk

Using mathematical simulation of motor unit potentials (MUPs), detected by a point and rectangular plate electrode, we have shown that the muscle tissue does not act like a low-pass frequency filter on MUPs. Depending on the electrode type and its longitudinal position, the relative weight of the terminal phases (reflecting the excitation extinction) in MUPs and thus of high frequencies in the MUP power spectrum, increase with the MU depth. Therefore, high-pass filtering or differentiating signals detected neither monopolarly nor bipolarly could eliminate the cross-talk produced by high frequency components of MUPs from deep MUs. Such methods could be effective against the main components but not against the MUP leading edge and terminal phases. To reduce the cross-talk, position of the detecting electrodes should correspond to anatomy of muscles producing the cross-talk. Monopolar electrode should be located above the ends of the muscles. Cross-talk of the muscles located beyond the muscle of interest could be higher than that produced above the end-plate of deep muscles. On the contrary, under detection by a longitudinal bipolar electrode, the cross-talk is much smaller above the end-plate region or beyond deep muscles. The cross-talk is the greatest above the ends of the deep muscles.

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.

The effects of four time-varying factors on the mean frequency of a myoelectric signal

Daily activities involve dynamic muscle contractions that yield nonstationary myoelectric signals (MESs). The purpose of this work was to determine the individual effects of four time-varying factors (the number and firing rate of active motor units, muscle force and joint angle) on the mean frequency of a MES. Previous theoretical and experimental work revealed that although changes in the number and firing rate of active motor units contribute to the nonstationarities of the signal, they do not significantly affect the mean frequency. In the experimental work, 12 subjects performed 25 static contractions, one for each force (20, 30, 40, 50 and 60% of maximum voluntary contraction) and elbow joint angle (50, 70, 90, 110 and 130 degrees extension) combination. A MES was recorded from the surface of the biceps brachii during each contraction. The results indicated that muscle force only weakly affects the mean frequency. Also shown was that alteration in muscle geometry resulting from changes in elbow joint angle does significantly affect the mean frequency. Knowing this is important for the assessment of muscle fatigue during dynamic contractions.

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.

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.

Calculation of extracellular potentials produced by an inclined muscle fibre at a rectangular plate electrode

Generally the anatomy of muscles is rather complex, and the fibres have various inclination angles within the muscles. We suggest a fast and reliable way to calculate extracellular potentials produced at a point or rectangular plate electrode by a muscle fibre of finite length with an arbitrary inclination. A muscle fibre was considered to be a linear timeshift-invariant system of potential generation. Then, similar to the fibre without inclination, the extracellular potential produced by an inclined fibre was represented as the output signal of the system; it was calculated as the convolution of the input signal and impulse response. Irrespective of the inclination, the input signal of the system was the first temporal derivative of the intracellular action potential. The impulse response of the system differed for the fibres with inclination. This required a new method of analytical integration over the rectangular electrode area. The approach provides a chance to simulate and analyze motor unit potentials or F-, H- or M-responses produced by muscles of complicated anatomy (circum-pennate or complex pennate type) at electrodes of actual size and location in normals and patients with neuro-muscular disorders.