Repeatability of electrically evoked EMG signals in the human vastus medialis muscle.

The repeatability of spectral and amplitude parameters and conduction velocity estimates of M-waves was tested on the vastus medialis muscle of 9 normal subjects. Isometric contractions sustained for 30 s were elicited by stimulation of the main muscle motor point and repeated on 5 different days. The initial value and two indicators of myoelectric manifestations of muscle fatigue were computed for each variable. The test-retest Pearson correlation coefficient, the paired Wilcoxon test, and the intraclass correlation coefficient (ICC) showed that parameters of spectral variables are more repeatable than those of amplitude variables and conduction velocity. The ICC ranged from 86.4% for the initial value of median frequency to 21.6% for the initial value of the average rectified value. Fatigue indices showed ICCs in the range of 20-64%. It is concluded that: (a) initial values and fatigue indices based on spectral variables are more repeatable than those based on amplitude variables; (b) the repeatability of conduction velocity estimates is not yet sufficient for clinical application; (c) M-wave shape, rather than amplitude or width, is a characteristic of individual muscles; and (d) electrode location is critical.

Surface EMG signal processing during isometric contractions.

This paper provides an overview of techniques suitable for the estimation, interpretation and understanding of time variations that affect the surface electromyographic (EMG) signal during sustained voluntary or electrically elicited contractions. These variations concern amplitude variables, spectral variables and muscle fiber conduction velocity, are interdependent and are referred to as the 'fatigue plot'. The fatigue plot provides information suitable for the classification of muscle behavior. In addition, the information obtainable by means of linear electrode arrays is discussed, and applications of mathematical models for the interpretation of array signals are presented. The model approach provides additional ways for the classification of muscle behavior.

Estimation of shape characteristics of surface muscle signal spectra from time domain data.

Myoelectric manifestations of muscle fatigue have been described by monitoring the first-order moment (mean frequency) of the power spectral density function during voluntary or electrically elicited sustained contractions. Higher order central moments provide additional information about the width, skewness, and kurtosis of the spectrum and its shape changes, thereby providing a description of slow nonstationarities more accurate than that allowed by the mean frequency alone. In 1986, B. Saltzberg introduced a method of representing the moments of the power spectral density function of band limited signals, without computing the Fourier transform, as weighted sums of samples of the autocorrelation function. If we allow for oversampling of the signal (and therefore of its autocorrelation function), more efficient weighted sums can be found which give Saltzberg's formula as a limiting case. The faster rate of decay of the weights implies a faster convergence of the estimates and the need to compute fewer samples of the autocorrelation function. The algorithm is particularly suitable for: 1) analysis of evoked potentials (M-waves), because it does not need zero padding to increase resolution and operates on any number of samples, and 2) on-line implementation by dedicated microprocessors performing simultaneous spectral moment analysis on a number of parallel channels.

Advances in processing of surface myoelectric signals: Part 1.

During sustained voluntary or electrically elicited muscle contractions the surface myoelectric signal is nonstationary and it undergoes progressive changes reflecting the modifications of the motor unit action potentials and their propagation velocity. In particular, during sustained electrical stimulation, the evoked signals show progressive amplitude, time scaling and shape modification. The quantitative evaluation of these changes is important for non-invasive muscle characterisation and may be performed in either the time or frequency domain using parametric and nonparametric spectral analysis as well as alternative methodologies. The paper introduces the detection techniques, reviews and compares the methods of spectral estimation based on FFT and autoregressive models, and discusses their applications and limitations in extracting information from the surface myoelectric signal with particular regard to myoelectric manifestations of localised muscle fatigue during sustained contractions.

Advances in processing of surface myoelectric signals: Part 2.

The paper focuses on the analysis of myoelectric evoked potentials and their progressive scaling, as well as morphological changes using orthogonal basis functions with essentially finite time support; and the compression of the information content using principal component analysis. The application of the Hermite-Rodriguez and the associated Hermite functions is discussed as a means to provide compact information about the shape of the M-wave or of the power spectral density function of either voluntary or electrically elicited myoelectric signals; a means to estimate scaling factors; and a means to describe and classify nonstationarities. The principal component analysis shows the possibility of a compression ratio of at least 10:1 in the storage of M-wave sequences. The paper also describes three methods for the estimation of delay between similar signals, and therefore for estimation of conduction velocity. They are based on normalised integrals. Fourier transform matching and matching in the time domain. In particular conditions they provide different results for the same pair of signals. The concept of delay and the performance of these methods are reviewed and discussed. The paper is not exhaustive. It has the main objective of making the reader aware of the wealth of methods available for nonstationary myoelectric signal analysis and conduction velocity estimation, and of the need to use them with knowledge of their respective advantages, disadvantages, peculiarities and limitations.

Repeatability of electrically-evoked myoelectric signals in the human tibialis anterior muscle.

The reproducibility of surface myoelectric signal measurements is of paramount importance for clinical applications of electromyography (EMG) techniques. The repeatability of electrically-evoked myoelectric signal shape (M-wave) as well as spectral and amplitude parameters, conduction velocity and elicited torque was tested, in isometric conditions, on the tibialis anterior muscle of 10 normal subjects. Contractions were elicited by stimulation of the main muscle motor point and repeated after removal and replacement of the stimulation and detection electrodes in the same carefully marked locations. This protocol was repeated five times on each subject on five different days. The test-retest Pearson correlation coefficient, the paired t test and analysis of variance (ANOVA) were used to quantify repeatability and estimate the fraction of variance due to repeated trials within experiments, repeated experiments within subjects and inter-subject variability. Results indicate that parameters of spectral variables are more repeatable than those of amplitude variables. Elicited torque and conduction velocity show the lowest repeatability. The intra-class correlation coefficient ranged from 87.9% for the initial value of median frequency to 11.5% for the initial value of conduction velocity. Fatigue indices based on the time course of the myoelectric signal variables showed even lower values of this coefficient. It is concluded that: (a) initial values and fatigue indices based on spectral variables are more repeatable than those based on amplitude variables; (b) the repeatability of conduction velocity and torque is very poor; (c) M-wave shape, rather than amplitude or width, seems to be a characteristic of individual muscles; and (d) electrode location is a critical issue in the study of M-waves elicited by stimulation of a muscle motor point. The methodology for estimation of muscle fibre conduction velocity must be refined and the characterization of evoked responses must be improved to allow widespread clinical applications.

Hermite expansions of compact support waveforms: applications to myoelectric signals.

Nonstationary signals with finite time support are frequently encountered in electrophysiology and other fields of biomedical research. It is often desirable to have a compact description of their shape and of their time evolution. For this purpose, Fourier analysis is not necessarily the best tool. The Hermite-Rodriguez and Associated Hermite basis functions are applied in this work. Both are based on the product of Hermite polynomials and Gaussian functions. Their general properties relevant to biomedical signal processing are reviewed. Preliminary applications are described concerning the analysis and description of: a) test signals such as a square pulse and a single cycle of a sinewave, b) electrically evoked myoelectric signals, and c) power spectra of either voluntary or evoked signals. It is shown that expansions with only five to ten terms provide an excellent description of the computer simulated and real signals. It is shown that these two families of Hermite functions are well suited for the analysis of nonstationary biological evoked potentials with compact time support. An application to the estimation of scaling factors of electrically evoked myoelectric signals is described. The Hermite functions show advantages with respect to the more traditional spectral analysis, especially in the case of signal truncation due to stimulation with interpulse intervals smaller than the duration of the evoked response. Finally, the Hermite approach is found to be suitable for classification of spectral shapes and compression of spectral information of either voluntary or evoked signals. The approach is very promising for neuromuscular diagnosis and assessment because of its capability for information compression and waveform classification.

Effect of ankle joint position on electrically evoked surface myoelectric signals of the tibialis anterior muscle.

The relationship between surface myoelectric signal variables and ankle joint angle is studied in the tibialis anterior muscle of ten normal subjects during electrical stimulation of the main muscle motor point in isometric conditions. Rectangular current pulses of 0.1 ms width and 20Hz repetition rate were applied for 10s with a monopolar technique using a stimulation/detection system providing stimulation artifact suppression. Electrically evoked responses (M-waves) were detected with a four-bar electrode placed on the skin below the lowest motor point near the tendon end of the muscle. Average rectified value, root mean square value, mean and median spectral frequency, conduction velocity, and latency of the surface signal were computed for ankle angles of 15 degrees dorsal flexion (-15 degrees), 0 degrees, 15 degrees, 30 degrees and 45 degrees of plantar flexion. All variables were considerably affected by the joint angle. Spectral variables and latency showed a statistically significant decrement as angle increased from -15 degrees to 45 degrees whereas conduction velocity and amplitude variables had a less regular behavior. The evoked response showed a latency decrement and a change of shape (mostly a widening of the second phase), as ankle joint angle increased from -15 degrees to 45 degrees. In most subjects conduction velocity appeared to be over estimated at -15 degrees and 45 degrees, a fact attributed to the small distance between the electrodes and either the tendon or the innervation zone at these two angles.(ABSTRACT TRUNCATED AT 250 WORDS)

Age related changes in surface myoelectric signals.

The initial values and the time course of muscle fiber conduction velocity and of surface myoelectric signal spectral variables were studied during voluntary or electrically elicited contractions of the tibialis anterior muscle of 15 healthy elderly human subjects. Age ranged from 65 to 84 years. Isometric voluntary contractions were performed at 20% MVC (Maximal Voluntary Contraction) and 80% MVC for 20 s. Tetanic electrical stimulation was then applied to the main muscle motor point for 20 s with surface electrodes. Two stimulation rates (20 Hz and 40 Hz) and two stimulation amplitudes were used to induce different degrees of fatigue. One stimulation amplitude was supramaximal, the second was adjusted to induce a response (M-wave) about 30% of the maximal. Results were compared with those reported in previous work on healthy adults (age range 18 to 43 years). The main findings of this work are: (a) when voluntary contraction level is increased from 20% MVC to 80% MVC conduction velocity and spectral variables increase; this increase is significantly smaller in elderly subjects, (b) during sustained contractions at 80% MVC the decrease of conduction velocity and spectral variables is significantly smaller in elderly subjects, (c) during contractions induced by supramaximal stimulation at 40 Hz the decrease of conduction velocity and spectral variables is not significantly different in the two age groups. It is concluded that points a and b reflect the age related decrease of number and size of fast twitch fibers indicated by histological data. Point c is discussed and possible explanations are suggested.

Indices of muscle fatigue.

Myoelectric signal variables and mechanical variables are known to change during sustained voluntary or electrically elicited contractions. These phenomena reflect changes in the properties of the muscle fiber and its membrane. Such changes are generally called "fatigue." Muscle fiber conduction velocity and myoelectric signal spectral parameters (mean and median frequency) show a linear or curvilinear decrease in time, depending on the level of voluntary or electrically elicited contraction. Amplitude paramaters [average rectified value (ARV) and root mean-square (RMS) value] and force often show a dome-shaped pattern with respect to time. In previous research, these patterns have been fitted with least-square regression curves or lines whose parameters (decrement, time constant, initial slope) have been considered indicators of the amount and rate of muscle property changes and therefore of ongoing fatigue. A new index of fatigue is proposed in this work. The product of a reference value (e.g., the first value of the time series) and the time of observation defines a reference rectangle. The area between the upper side of such rectangle and the experimental data points is divived by the area of the reference rectangle to provide this index. This area ratio index may be computed either as an attribute of a contraction or as a function of time; it is regression-free, it is dimensionless, it varies between 0 and 1 for decreasing patterns, it is negative for increasing patterns, and it is little affected by experimental point fluctuations except for the value that defines the reference rectangle. With respect to other indices, the area ratio index provides a quantitative approach to fatigue that is consistent with the intuitive definition of fatigue. If applied to different myoelectric signal variables, the resulting area ratios may be interpreted as the components of a fatigue vector.