Many previous studies were focused on the influence of anatomical, physical, and detection-system parameters on recorded surface EMG signals. Most of them were conducted by simulations. Previous EMG models have been limited by simplifications which did not allow simulation of several aspects of the EMG generation and detection systems. We recently proposed a model for fast and accurate simulation of the surface EMG. It characterizes the volume conductor as a non-homogeneous and anisotropic medium, and allows simulation of EMG signals generated by finite-length fibers without approximation of the current-density source. The influence of thickness of the subcutaneous tissue layers, fiber inclination, fiber depth, electrode size and shape, spatial filter transfer function, interelectrode distance, length of the fibers on surface, single-fiber action-potential amplitude, frequency content, and estimated conduction velocity are investigated in this paper. Implications of the results on electrode positioning procedures, spatial filter design, and EMG signal interpretation are discussed.

Two physiological factors are assumed in this paper to mainly determine the myoelectric manifestations of fatigue: (1) the decrease of the conduction velocity (CV) of motor unit action potentials (MUAP) (peripheral fatigue), and (2) the increase of MU synchronization by the central nervous system (central fatigue). To describe separately the peripheral and central components of the myoelectric manifestations of fatigue, we investigated the following indexes: (1) mean spectral frequency - MNF, (2) median spectral frequency - MDF, (3) root mean square - RMS, (4) average rectified value - ARV, (5) estimation of muscle fiber conduction velocity - ECV, (6) percentage of determinism - %DET, (7) spectral indexes defined as the ratio between signal spectral moments - FI(k), (8) MNF estimated by autoregressive analysis - MNF(AR), (9) MNF estimated by Choi-Williams time-frequency representation - MNF(CWD), (10) MNF estimated by continuous wavelet transform - MNF(CWT), (11) signal entropy - S, (12) fractal dimension - FD. The indexes were tested with a set of synthetic EMG signals, with different CV distribution and level of MU synchronization. The indexes were calculated on epochs of 0.5s. It was observed that ECV is uncorrelated with the level of simulated synchronization (promising index of peripheral fatigue). On the other hand FD was the index least affected by CV changes and most related to the level of synchronism (promising index of central fatigue). A representative application to some experimental signals from vastus lateralis muscle during an isometric endurance test supported the results of the simulations. The vector (ECV, FD) is suggested to provide selective indications of peripheral and central fatigue. The description of EMG fatigue by a bi-dimensional vector opens new perspectives in the assessment of muscle properties, with potential application in both clinical and sport sciences.

To understand better the features of the mechanomyogram (MMG) with different force levels and muscle architectures, the MMG signals detected at many points along three muscles were analysed by the application of a linear array of MMG sensors (up to eight) over the skin. MMG signals were recorded from the biceps brachii, tibialis anterior and upper trapezius muscles of the dominant side of ten healthy male subjects. The accelerometers were aligned along the direction of the muscle fibres. One accelerometer was located over the distal muscle innervation zone, and the other six or seven accelerometers were placed over the muscle, forming an array of sensors with fixed distances between them. The array covered almost the entire muscle length in all cases. MMG signals detected from adjacent accelerometers had similar shapes, with correlation coefficients ranging from about 0.5 to about 0.9. MMG amplitude and characteristic spectral frequencies significantly depended on accelerometer location. The MMG amplitude was maximum at the muscle belly for the biceps brachii and the tibialis anterior. Higher MMG characteristic spectral frequencies were associated with higher amplitudes in the case of the biceps brachii, whereas the opposite was observed for the tibialis anterior muscle. In the upper trapezius, the relationship between characteristic spectral frequencies, MMG amplitude and contraction force depended on the accelerometer location. This suggested that MMG spectral features do not only reflect the mechanical properties of the recruited muscle fibres but depend on muscle architecture and motor unit territorial distribution. It was concluded that the location of the accelerometer can have an influence on both amplitude and spectral MMG features, and this dependence should be considered when MMG signals are used for muscle assessment.

No abstract

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 study presents analytical, simulation, and experimental analyses of amplitude cancellation of motor-unit action potentials (APs) in the interference electromyogram (EMG) and its relation to the size of the spike-triggered average (STA) EMG. The amount of cancellation of motor-unit APs decreases monotonically as a function of the ratio between the root mean square (RMS) of the motor-unit AP and the RMS of the interference EMG signal. The theoretical derivation of this association indicates a method to measure cancellation in individual motor units by STA of the interference and squared EMGs. The theoretical relation was examined in both simulated EMG signals generated by populations of 200 motor units and experimental recordings of 492 and 184 motor-unit APs in the vastus medialis and abductor digiti minimi muscles, respectively. Although the theoretical relation predicted (R2 = 0.95; P < 0.001) the amount of cancellation in the simulated EMGs, the presence of motor-unit synchronization decreased the strength of the association for small APs. The decrease in size of the STA obtained from the squared EMG relative to that extracted from the interference EMG was predicted by the experimental measure of cancellation (R2 = 0.65; P < 0.001, for vastus medialis; R2 = 0.26; P < 0.05, for abductor digiti minimi). The results indicate that cancellation of APs in the interference EMG can be analytically predicted and experimentally measured with STA from the discharge times of the motor units into the surface EMG.

This article is the second part of a larger review work that has been structured in three parts. The three parts concern a) advances in surface EMG detection and processing techniques, b) recent progress in surface EMG clinical research applications, and c) myoelectric control in neurorehabilitation. This second part concerns state of the art applications of surface EMG techniques to a) the external anal sphincter in relation to episiotomy and incontinence; b) the assessment of postural control mechanisms; c) exercise physiology, electrical stimulation and muscle cramps; and d) ergonomics and work-related neuromuscular disorders. The material is presented with an effort to fill gaps left by previous reviews and identify areas open for future research.

PurposeOver the past decade, linear and non-linear surface electromyography descriptors for central and peripheral components of fatigue have been developed. In the current study, we tested fractal dimension (FD) and conduction velocity (CV) as myoelectric descriptors of central and peripheral fatigue, respectively. To this aim, we analyzed FD and CV slopes during sustained fatiguing contractions of the quadriceps femoris in healthy humans.MethodsA total of 29 recreationally active women (mean age±standard deviation: 24±4 years) and two female elite athletes (one power athlete, age 24 and one endurance athlete, age 30 years) performed two knee extensions: (1) at 20% maximal voluntary contraction (MVC) for 30 s, and (2) at 60% MVC held until exhaustion. Surface EMG signals were detected from the vastus lateralis and vastus medialis using bidimensional arrays.ResultsCentral and peripheral fatigue were described as decreases in FD and CV, respectively. A positive correlation between FD and CV (R=0.51, p<0.01) was found during the sustained 60% MVC, probably as a result of simultaneous motor unit synchronization and a decrease in muscle fiber CV during the fatiguing task.ConclusionsCentral and peripheral fatigue can be described as changes in FD and CV, at least in young, healthy women. The significant correlation between FD and CV observed at 60% MVC suggests that a mutual interaction between central and peripheral fatigue can arise during submaximal isometric contractions.