Simulation of electromyograms showing interference patterns

doi:10.1016/0013-4694(70)90205-1

Electroencephalography and Clinical Neurophysiology

Volume 28, Issue 6, June 1970, Pages 625-632

https://doi.org/10.1016/0013-4694(70)90205-1 Get rights and content

Abstract

The model of the EMG showing an interference pattern in which motor units are discharged independently (which is typical for relatively weak contractions) gives an adequate picture of this type of activity, agreeing with the actual EMG in appearance as well as in some important parameters (the number of maxima, frequency spectrum and autocorrelation function). Some of the interference pattern parameters (mean duration of fluctuation, the possition of the first zero of the autocorrelation function, frequency of the main spectral maximum) are in simple relation with the duration of motor unit action potentials composing this interference pattern.

The study of dependence of integrated electrical activity of the asynchronous model on the number of active motor units N, revealed that after a certain level of activity is reached, the model disagrees with the results of physiological experimentation. The latter shows a more rapid increase in electrical activity with increased number of motor units (force of contraction). If synchronization increasing with increased N is put into the model, it becomes closer to the actual EMG in the range of activity of a great number of motor units.

Simulation has shown that changes in the mean duration of interference pattern fluctuation and the frequency spectrum, observed during synchronization in physiological experiments, are not caused by synchronization but by the fact that this synchronization is not complete in the muscle. Small shifts in the impulses of motor units discharging synchronously account for an increase in mean duration of the interference pattern fluctuation and also for the displacement of the main spectral maximum to the left.

Résumé

Le modèle de l'électromyogramme (EMG) montrant un pattern d'interférence dans lequel les unités motrices se déchargent indépendamment (ce qui est typique de contractions relativement faibles) donne une représentation adéquate de ce type d'activité, conforme à l'EMG réel quant à son apparence en ce qui concerne certains paramètres importants (nombre des maxima, spectre de fréquence et fonction d'autocorrélation). Certains paramètres du pattern d'interférence (durée moyenne de fluctuation, position du premier zéro de la fonction d'autocorrélation, fréquence du maximum principal du spectre) sont en relation simple avec la durée des potentiels d'action de l'unité motrice qui composent ce pattern d'interférence.

L'étude de la dépendance entre l'activité électrique intégrée du modèle asynchrone et le nombre N des unités motrices actives, révèle qu'après qu'un certain niveau d'activité soit atteint, le modèle est en désaccord avec les résultats de l'expérimentation physiologique. Cette dernière montre une augmentation plus rapide de l'activité électrique avec l'accroissement du nombre des unités motrices (force de contraction). Si une synchronisation augmentant avec un nombre N accru est introduite dans le modèle, il devient plus proche de l'EMG réel dans la gamme d'activité d'un grand nombre d'unités motrices.

La simulation montre que des modifications de la durée moyenne de la fluctuation du pattern d'interférence et du spectre de fréquence, observées au cours de la synchronisation dans les expériences physiologiques, ne sont pas dues à la synchronisation, mais au fait que cette synchronisation n'est pas complète dans le muscle. De petites variations dans les impulsions d'unités motrices se déchargeant de façon synchrone sont responsables d'un accroissement de la durée moyenne de la fluctuation du pattern d'interférence et également du déplacement du maximum principal du spectre vers la gauche.

References (24)

F Buchthal et al.
Synchronous activity in normal and atrophic muscle
Electroenceph. clin. Neurophysiol.
(1950)
F.H Norris et al.
Action potentials of single motor units in normal muscle
Electroenceph. clin. Neurophysiol.
(1955)
R.S Person et al.
Cross-correlation of electromyogram showing interference patterns
Electroenceph. clin. Neurophysiol.
(1968)
E.D Adrian
Oliver-Sharpey lectures on the interpretation of the electromyogram
Lancet
(1925)
E.D Adrian
General principles of nervous activity
Brain
(1947)
B Bigland et al.
Motor unit activity in the voluntary contraction of human muscle
J. Physiol. (Lond.)
(1954)
V.S Gurfinkel et al.
Postural control
E Haas
Über die Art der Tätigkeit unserer Muskeln beim Halten verschiedener schwerer Gewichte
Pflügers Arch. ges. Physiol.
(1926)
J Hyde et al.
The dependence of unit discharges on frequency and intensity of stimulation of the motor cortex in the macaque
J. cell. comp. Physiol.
(1954)
K Kogi et al.
Frequency analysis of the surface electromyogram in muscle fatigue
J. Sci. Labour (Tokyo)
(1962)

M.S Libkind

Modelling of interfering bioelectrical activity, Il.

Biofizika

(1968)

M.S Libkind

Modelling of interfering bioelectrical activity, III

Biofizika

(1969)

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This work studies the dynamic relationship between the electrical activity produced in skeletal muscles and recorded using electromyogram(EMG), and torque at the healthy human ankle during isometric contractions. Subjects were instructed to voluntarily modulate their ankle torque by tracking a pseudo-random visual command signal. Impulse response functions (IRF) estimated between the EMG and torque records had an unphysiological anticipatory component suggesting that the estimated IRF was biased because the data were recorded in closed-loop. Applying a closed-loop identification algorithm that modeled the EMG-torque relation as a nonparametric impulse response function, and the noise as an autoregressive-moving-average process gave unbiased results. The EMG-torque IRF had second-order, low-pass, dynamics, whose properties varied with the mean torque.
Methodological aspects of SEMG recordings for force estimation - A tutorial and review
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Citation Excerpt :
Because the traveling waves of the MUPs (see Section 2.1) are bi-phasic or tri-phasic in nature (they contain positive and negative phases), these phases may add in this summation (constructive) or they may cancel (destructive) (McGill, 2004). This phenomenon, usually referred to as phase cancellation has been recognized early on (Adrian, 1925; Libkind, 1968; Moore, 1967; Person and Libkind, 1970), but its consequences are often overlooked. Due to irregularity of MU firing (Matthews, 1996) and despite a low level of synchronization of firing between MUs (Yao et al., 2000), constructive and destructive superimpositions occur randomly.
Insight into the magnitude of muscle forces is important in biomechanics research, for example because muscle forces are the main determinants of joint loading. Unfortunately muscle forces cannot be calculated directly and can only be measured using invasive procedures. Therefore, estimates of muscle force based on surface EMG measurements are frequently used. This review discusses the problems associated with surface EMG in muscle force estimation and the solutions that novel methodological developments provide to this problem. First, some basic aspects of muscle activity and EMG are reviewed and related to EMG amplitude estimation. The main methodological issues in EMG amplitude estimation are precision and representativeness. Lack of precision arises directly from the stochastic nature of the EMG signal as the summation of a series of randomly occurring polyphasic motor unit potentials and the resulting random constructive and destructive (phase cancellation) superimpositions. Representativeness is an issue due the structural and functional heterogeneity of muscles. Novel methods, i.e. multi-channel monopolar EMG and high-pass filtering or whitening of conventional bipolar EMG allow substantially less variable estimates of the EMG amplitude and yield better estimates of muscle force by (1) reducing effects of phase cancellation, and (2) adequate representation of the heterogeneous activity of motor units within a muscle. With such methods, highly accurate predictions of force, even of the minute force fluctuations that occur during an isometric and isotonic contraction have been achieved. For dynamic contractions, EMG-based force estimates are confounded by the effects of muscle length and contraction velocity on force producing capacity. These contractions require EMG amplitude estimates to be combined with modeling of muscle contraction dynamics to achieve valid force predictions.
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2008, Computers in Biology and Medicine
A new method based on probability density functions (inverse Gaussian distributions) to simulate surface electromyograms (sEMGs) was developed for the specific use of the ‘ $T_{P}$ technique’, which discriminates sEMG activity patterns. First, four prototypes with different activity patterns were generated from inverse Gaussian distributions by changing their geometrical parameters, which were derived from actual recorded sEMGs. Then, four simulated sEMGs were produced on the basis of the prototypes. The validity of the simulation method in relation to the $T_{P}$ technique was statistically examined and verified. The new simulation method will be useful.
Epoch length to accurately estimate the amplitude of interference EMG is likely the result of unavoidable amplitude cancellation
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Researchers and clinicians routinely rely on interference electromyograms (EMGs) to estimate muscle forces and command signals in the neuromuscular system (e.g., amplitude, timing, and frequency content). The amplitude cancellation intrinsic to interference EMG, however, raises important questions about how to optimize these estimates. For example, what should the length of the epoch (time window) be to average an EMG signal to reliably estimate muscle forces and command signals? Shorter epochs are most practical, and significant reductions in epoch have been reported with high-pass filtering and whitening. Given that this processing attenuates power at frequencies of interest (<250 Hz), however, it is unclear how it improves the extraction of physiologically relevant information. We examined the influence of amplitude cancellation and high-pass filtering on the epoch necessary to accurately estimate the “true” average EMG amplitude calculated from a 28 s EMG trace (EMG_ref) during simulated constant isometric conditions. Monte Carlo iterations of a motor-unit model simulating 28 s of surface EMG produced 245 simulations under two conditions: with and without amplitude cancellation. For each simulation, we calculated the epoch necessary to generate average full-wave rectified EMG amplitudes that settled within 5% of EMGref. For the no-cancellation EMG, the necessary epochs were short (e.g., <100 ms). For the more realistic interference EMG (i.e., cancellation condition), epochs shortened dramatically after using high-pass filter cutoffs above 250 Hz, producing epochs short enough to be practical (i.e., <500 ms). We conclude that the need to use long epochs to accurately estimate EMG amplitude is likely the result of unavoidable amplitude cancellation, which helps to clarify why high-pass filtering (>250 Hz) improves EMG estimates.
Surface EMG models: Properties and applications
2000, Journal of Electromyography and Kinesiology
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.
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This article introduces the area of scientific study of human movement. It is primarily intended for readers who wish to form a judgement on the usefulness of scientific movement analysis techniques in the treatment process of patients with abnormal movement patterns. With a focus on the analysis of human locomotion, the paper outlines the historical development of a biomechanical approach towards the understanding of human movement patterns. This approach alone proves to be inadequate in supplying reliable information on neuromuscular control of movement. It follows that electromyographic techniques are essential for this purpose. Scientific literature reveals relevant practical usability of such information. This is the rationale for a review of the historical, physiological, technical and methodological background of electromyographic analysis of movement. The field of management and rehabilitation of motor disability is identified as one important application area. On the basis of relevant literature, the present paper asserts that scientific analysis of human movement patterns can materially affect patient treatment. It provides evidence that patient management and rehabilitation processes in central neurological disorders can be improved through electromyographic techniques. In particular, this evidence supports the use of electromyography for surgical planning in children with cerebral palsy. The paper concludes with a view on future directions in research, development and applications of scientific analysis of human movement.

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¹: It is deeply regretted that Dr. Libkind met with a fatal accident after this paper was sumbmitted for publication.

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Simulation of electromyograms showing interference patternsSimulation d'électromyogrammes montrant des patterns d'interférence

Abstract

Résumé

Electroenceph. clin. Neurophysiol.

Electroenceph. clin. Neurophysiol.

Electroenceph. clin. Neurophysiol.

Oliver-Sharpey lectures on the interpretation of the electromyogram

Lancet

General principles of nervous activity

Brain

Motor unit activity in the voluntary contraction of human muscle

J. Physiol. (Lond.)

Postural control

Über die Art der Tätigkeit unserer Muskeln beim Halten verschiedener schwerer Gewichte

Pflügers Arch. ges. Physiol.

The dependence of unit discharges on frequency and intensity of stimulation of the motor cortex in the macaque

J. cell. comp. Physiol.

Frequency analysis of the surface electromyogram in muscle fatigue

J. Sci. Labour (Tokyo)

Modelling of interfering bioelectrical activity, Il.

Biofizika

Modelling of interfering bioelectrical activity, III

Biofizika