Publications
789 results found
Mandrile F, Farina D, Pozzo M, et al., 2003, Stimulation artifact in surface EMG signal: effect of the stimulation waveform, detection system, and current amplitude using hybrid stimulation technique., IEEE Trans Neural Syst Rehabil Eng, Vol: 11, Pages: 407-415, ISSN: 1534-4320
The purpose of this study was to investigate the amplitude properties of the artifact generated on the recorded surface electromyography (EMG) signals during transcutaneous electrical muscle stimulation. The factors which were investigated are the shape of the stimulation waveform, the distance of the stimulating electrode from the recording system, the interelectrode distance of the detection system, the spatial filter used for signal detection, and the stimulation current amplitude. Surface EMG signals were recorded during electrical stimulation of the biceps brachii motor point with a linear adhesive array of eight electrodes. Electrical stimulation was applied with seven stimulation waveforms (mono- and biphasic triangular, sinusoidal, and rectangular), generated by a specifically designed neuromuscular stimulator with hybrid output stage. The stimulation peak current was linearly increased from 0 mA to the maximum tolerated by the subject. The detection systems investigated were single and double differential with interelectrode distances multiple of 5 mm. Two trials for each contraction were performed on three different days. The average rectified artifact values (both absolute and normalized with respect to the corresponding M-wave values) were computed to investigate the artifact amplitude properties. Results indicated that, while the artifact average rectified value, normalized with respect to the M-wave amplitude, depended on the distance of the detecting electrodes from the stimulation point, it did not depend on the stimulation waveform, on the current intensity, on the interelectrode distance, and on the spatial filter. It was concluded that, using hybrid stimulation techniques, the selection of particular stimulation waveforms, interelectrode distances, or spatial filters has a minor effect on the reduction of the artifact when recording M-waves.
Farina D, Kallenberg LAC, Merletti R, et al., 2003, Effect of side dominance on myoelectric manifestations of muscle fatigue in the human upper trapezius muscle., Eur J Appl Physiol, Vol: 90, Pages: 480-488, ISSN: 1439-6319
The purpose of this study was to investigate whether differences in the peripheral and control properties of the neuromuscular system due to long-term preferential use, related to side dominance, affect postural muscles, such as the upper trapezius. Therefore, fatigability properties of the upper trapezius muscles of the dominant and non-dominant side were assessed. Surface EMG signals were detected from the upper trapezius muscles of both sides of nine right- and five left-handed subjects with adhesive linear electrode arrays consisting of eight contact points. Static constant force contractions with the arms 90 degrees abducted were performed by the subjects while holding hand loads of 0 kg, 0.5 kg, and 1 kg. Surface EMG spectral and amplitude variables were computed from the recorded signals. EMG spectral variable rate of change (indicating fatigue) showed a statistically significant difference between the two sides, with the dominant side less fatigable than the non-dominant one. The observed differences held for both the right- and left-handed subject group. A possible explanation for the results is that long preferential use of one side with respect to the other leads to changes in muscle fiber membrane and control properties, in agreement with previous results on limb muscles.
Farina D, Gazzoni M, Merletti R, 2003, Assessment of low back muscle fatigue by surface EMG signal analysis: methodological aspects., J Electromyogr Kinesiol, Vol: 13, Pages: 319-332, ISSN: 1050-6411
This paper focuses on methodological issues related to surface electromyographic (EMG) signal detection from the low back muscles. In particular, we analysed (1) the characteristics (in terms of propagating components) of the signals detected from these muscles; (2) the effect of electrode location on the variables extracted from surface EMG; (3) the effect of the inter-electrode distance (IED) on the same variables; (4) the possibility of assessing fatigue during high and very low force level contractions. To address these issues, we detected single differential surface EMG signals by arrays of eight electrodes from six locations on the two sides of the spine, at the levels of the first (L1), the second (L2), and the fifth (L5) lumbar vertebra. In total, 42 surface EMG channels were acquired at the same time during both high and low force, short and long duration contractions. The main results were: (1) signal quality is poor with predominance of non-travelling components; (2) as a consequence of point (1), in the majority of the cases it is not possible to reliably estimate muscle fiber conduction velocity; (3) despite the poor signal quality, it was possible to distinguish the fatigue properties of the investigated muscles and the fatigability at different contraction levels; (4) IED affects the sensitivity of surface EMG variables to electrode location and large IEDs are suggested when spectral and amplitude analysis is performed; (5) the sensitivity of surface EMG variables to changes in electrode location is on average larger than for other muscles with less complex architecture; (6) IED influences amplitude initial values and slopes, and spectral variable initial values; (7) normalized slopes for both amplitude and spectral variables are not affected by IED and, thus, are suggested for fatigue analysis at different postures or during movement, when IED may change in different conditions (in case of separated electrodes); (8) the surface EMG technique at the g
Farina D, Schulte E, Merletti R, et al., 2003, Single motor unit analysis from spatially filtered surface electromyogram signals. Part I: spatial selectivity., Med Biol Eng Comput, Vol: 41, Pages: 330-337, ISSN: 0140-0118
The aim of the study was to compare experimentally, on the basis of single motor unit (MU) activities, the selectivity of different spatial filters commonly used to detect surface electromyogram (EMG) signals. Surface EMG signals were recorded from the biceps brachii and the upper trapezius muscle of five subjects using a two-dimensional (2D) electrode array consisting of 16 pin electrodes. The subjects performed isometric contractions at different elbow angles and shoulder abduction and flexion. The same monopolar surface EMG signals were filtered using longitudinal single and double differential, transverse single and double differential and normal double differential filters. From the single MU action potentials, extracted by automatic EMG decomposition, indexes of transverse (perpendicular with respect to the fibre direction) and longitudinal (along the fibre direction) selectivity were computed. The number of detected MUs was 46 for the upper trapezius, with the arms held in the sagittal plane, and 52 when the arms were held in the frontal plane; 85 MUs were identified from the biceps brachii contractions. The results showed that transverse selectivity was significantly higher for the 2D and transverse one-dimensional (1D) filters with respect to the 1D longitudinal filters, whereas longitudinal selectivity was higher (i.e. MU action potentials were shorter) for the 2D filter and the longitudinal double differential filter. In particular, the relative attenuation of potential amplitude moving 5 mm from the source was, on average (for the two muscles), 16.5% for the least selective filter in the transverse direction (longitudinal single differential) and 35.7% for the most selective one in the same direction (transverse double differential). The MU action potential duration was, on average, 13.8 ms for the most selective filter in the longitudinal direction (longitudinal double differential) and 18.7 ms for the least selective one (transverse double differential
Schulte E, Farina D, Rau G, et al., 2003, Single motor unit analysis from spatially filtered surface electromyogram signals. Part 2: conduction velocity estimation., Med Biol Eng Comput, Vol: 41, Pages: 338-345, ISSN: 0140-0118
The aim of the study was to compare experimentally conduction velocity (CV) estimates obtained with different estimation methods based on surface electromyogram (EMG) signals detected using five spatial filters. The filters investigated were the longitudinal single and double differential, transverse single and double differential, and normal double differential. The same surface EMG signals detected as described in Part 1 were used in this work. CV was estimated with four commonly used delay estimation techniques, i.e. from the distance between the peak values of two waveforms (with and without polynomial interpolation around the peak), and by the maximum likelihood estimate (MLE) based on two or more surface EMG channels. The average standard deviation of CV estimation (for all the MUs and the two muscles together) was 0.61 m s(-1) and 0.79 m s(-1) for the peak method, with and without interpolation, respectively, and 0.50 m s(-1) and 0.31 m s(-1) for the MLE method, from two and more surface EMG channels, respectively. Moreover, the mean of CV estimates varied by as much as 1 m s(-1) depending on the spatial filter used and the method adopted for CV estimation. Considering the dependence on the spatial filter only, the average (over all estimation methods) CV estimates obtained with the five spatial filters were 4.32 m s(-1) (normal double differential), 4.23 m s(-1) (longitudinal double differential), 4.61 m s(-1) (transverse double differential), 4.64 m s(-1) (transverse single differential) and 4.03 m s(-1) (longitudinal single differential). It was concluded that the comparison of single MU CV values obtained in different studies is critical if different spatial filters and processing techniques are used for their estimation. Higher estimates of CV were attributed to a smaller reduction in non-travelling signal components and thus were assumed to be positively biased.
Muhammad W, Meste O, Rix H, et al., 2003, A pseudojoint estimation of time delay and scale factor for M-wave analysis., IEEE Trans Biomed Eng, Vol: 50, Pages: 459-468, ISSN: 0018-9294
A pseudojoint estimation of time scale and time delay between an unknown deterministic transient type signal and a reference signal is proposed. The method is based on the separation between the estimations of the two dependent parameters. The time autocorrelation function (TACF) preserves the time scale and is invariant with respect to the time delay between the signals. The time scale factor can, thus, be estimated independently from time delay using the TACFs of the two signals. After estimating the time scale factor, the signal can be scaled by the estimated amount. The time delay is then estimated without bias due to the time scale factor. To obtain high resolution joint estimates, the time scale factor is estimated in the scale domain from the scale transforms of the TACFs of the two signals. The proposed method has low computational cost. Moreover, the results on synthetic signals show good performance of the method with respect to the Cramér-Rao Lower Bound and the joint Maximum Likelihood Estimation. A possible application of the technique to the analysis of electromyogram (EMG) signals detected during electrically elicited contractions is also presented. In a few representative cases, it is shown that the time scale estimate reveals myoelectric manifestations of muscle fatigue and is less affected by M-wave truncation than spectral EMG attributes.
Farina D, Arendt-Nielsen L, Merletti R, et al., 2003, Selectivity of spatial filters for surface EMG detection from the tibialis anterior muscle., IEEE Trans Biomed Eng, Vol: 50, Pages: 354-364, ISSN: 0018-9294
Many spatial filters have been proposed for surface electromyographic (EMG) signal detection. Although theoretical and modeling predictions on spatial selectivity are available, there are no extensive experimental validations of these techniques based on single motor unit (MU) activity detection. The aim of this study was to compare spatial selectivity of one- and two-dimensional (1-D and 2-D) spatial filters for EMG signal detection. Intramuscular and surface EMG signals were recorded from the tibialis anterior muscle of ten subjects. The simultaneous use of intramuscular wire and surface recordings (with the spike triggered averaging technique) allowed investigation of the activity of single MUs at the skin surface. The surface EMG signals were recorded with a grid of point electrodes (3 x 3 electrodes) and a ring electrode system at 15 locations over the muscle, with the wires detecting signals from the same intramuscular location. For most subjects, it was possible to classify, from the intramuscular recordings, the activity of the same MUs for all the contractions. The surface EMG signals were averaged with the intramuscularly detected MU action potentials as triggers. In this way, eight spatial filters--longitudinal and transversal, single and double differential (LSD, TSD, LDD, TDD), Laplacian (NDD), inverse binomial filter of the second order (IB2), inverse rectangle filter (IR), and differential ring system (C1)--could be compared on the basis of their spatial selectivity. The distance from the source (transversal with respect to the muscle fiber orientation) after which the surface detected potential did not exceed +/- 5% of the maximal peak-to-peak amplitude (detection distance) was statistically smaller for the 2-D systems and TDD than for the other filters. The MU action potential duration was significantly shorter with LDD and with the 2-D systems than with the other filters. The 2-D filters investigated (including C1) showed very similar performance a
Merlo A, Farina D, Merletti R, 2003, A fast and reliable technique for muscle activity detection from surface EMG signals., IEEE Trans Biomed Eng, Vol: 50, Pages: 316-323, ISSN: 0018-9294
The estimation of on-off timing of human skeletal muscles during movement is an important issue in surface electromyography (EMG) signal processing with relevant clinical applications. In this paper, a novel approach to address this issue is proposed. The method is based on the identification of single motor unit action potentials from the surface EMG signal with the use of the continuous wavelet transform. A manifestation variable is computed as the maximum of the outputs of a bank of matched filters at different scales. A threshold is applied to the manifestation variable to detect EMG activity. A model, based on the physical structure of the muscle, is used to test the proposed technique on synthetic signals with known features. The resultant bias of the onset estimate is lower than 40 ms and the standard deviation lower than 30 ms in case of additive colored Gaussian noise with signal-to-noise ratio as low as 2 dB. Comparison with previously developed methods was performed, and representative applications to experimental signals are presented. The method is designed for a complete real-time implementation and, thus, may be applied in clinical routine activity.
Merletti R, Farina D, Gazzoni M, 2003, The linear electrode array: a useful tool with many applications., J Electromyogr Kinesiol, Vol: 13, Pages: 37-47, ISSN: 1050-6411
In this review we describe the basic principles of operation of linear electrode arrays for the detection of surface EMG signals, together with their most relevant current applications. A linear array of electrodes is a system which detects surface EMG signals in a number of points located along a line. A spatial filter is usually placed in each point for signal detection, so that the recording of EMG signals with linear arrays corresponds to the sampling in one spatial direction of a spatially filtered version of the potential distribution over the skin. Linear arrays provide indications on motor unit (MU) anatomical properties, such as the locations of the innervation zones and tendons, and the fiber length. Such systems allow the investigation of the properties of the volume conductor and its effect on surface detected signals. Moreover, linear arrays allow to estimate muscle fiber conduction velocity with a very low standard deviation of estimation (of the order of 0.1-0.2 m/s), thus providing reliable indications on muscle fiber membrane properties and their changes in time (for example with fatigue or during treatment). Conduction velocity can be estimated from a signal epoch (global estimate) or at the single MU level. In the latter case, MU action potentials are identified from the interference EMG signals and conduction velocity is estimated for each detected potential. In this way it is possible, in certain conditions, to investigate single MU control and conduction properties with a completely non-invasive approach. Linear arrays provide valuable information on the neuromuscular system properties and appear to be promising tools for applied studies and clinical research.
Pozzo M, Farina D, Merletti R, 2003, Electromyography: Detection, processing, and applications, Biomedical Technology and Devices Handbook, ISBN: 9780849311406
An essential characteristic of animals is their ability to move in the surrounding environment. The actuators of movement are the muscles whose contractions generate forces on the skeletal segments to which they are connected. Functional properties of muscles, that is, their contractile properties, cannot easily be investigated in vivo, both because of the difficulty of inserting force sensors in series with the tendons and because, in normal conditions, different muscles act on the same skeletal segment. Besides mechanical properties, the activity of skeletal muscles is also associated with the generation of electric signals that can be recorded by electrodes inserted in the muscle (intramuscular recordings) or fixed over the skin (surface recordings). The electric signals generated by the muscles during their activity are referred to as electromyographic (EMG) signals. Although muscles have been subject of study for centuries, only recently has the importance of their electrical activity been acknowledged for the study of their properties. Galvani (1737-1789) showed that muscle contractions can be induced by electrical stimulation. Duchenne (1949) first used electrical stimulation to investigate the contractile muscle properties. In 1929 Adrian and Bronk measured muscle electrical activity by needle electrodes, the so-called concentric needle, with the possibility of detecting potentials of single motor units.
Farina D, Merletti R, Indino B, et al., 2002, Surface EMG crosstalk between knee extensor muscles: experimental and model results., Muscle Nerve, Vol: 26, Pages: 681-695, ISSN: 0148-639X
Surface electromyographic (EMG) crosstalk between vastus lateralis, vastus medialis, and rectus femoris muscles was evaluated by selective electrical stimulation of one muscle and recording from the stimulated and another muscle with linear surface arrays of eight electrodes. The ratio between the amplitude of the signals recorded over nonstimulated and stimulated muscles and their correlation coefficient were used as indices to quantify crosstalk. Single-differential and double-differential detection systems were used with interelectrode distances in the range 10-40 mm. The multichannel EMG signals clearly showed that crosstalk is largely due to nonpropagating potentials that correspond in time to the end of the propagation of the action potentials generated by the stimulated muscle. The crosstalk signal increased with increasing interelectrode distance and was statistically higher for single- than for double-differential recordings. The correlation-based indices of crosstalk were poorly correlated with the amplitude-based indices. Moreover, the characteristic spectral frequencies of the signals detected over the nonstimulated muscles were statistically higher than those from the stimulated muscles. A mathematical model of signal generation was used to explain the experimental findings. This study clarifies many controversial findings of past investigations and creates the basis for crosstalk interpretation, simulation, and reduction.
Farina D, Fattorini L, Felici F, et al., 2002, Nonlinear surface EMG analysis to detect changes of motor unit conduction velocity and synchronization., J Appl Physiol (1985), Vol: 93, Pages: 1753-1763, ISSN: 8750-7587
Amplitude and frequency content of the surface electromyographic (EMG) signal reflect central and peripheral modifications of the neuromuscular system. Classic surface EMG spectral variables applied to assess muscle functions are the centroid and median power spectral frequencies. More recently, nonlinear tools have been introduced to analyze the surface EMG; among them, the recurrence quantification analysis (RQA) was shown to be particularly promising for the detection of muscle status changes. The purpose of this work was to analyze the effect of motor unit short-term synchronization and conduction velocity (CV) on EMG spectral variables and two variables extracted by RQA, the percentage of recurrence (%Rec) and determinism (%Det). The study was performed on the basis of a simulation model, which allowed changing the degree of synchronization and mean CV of a number of motor units, and of an experimental investigation of the surface EMG signal properties detected during high-force-level isometric fatiguing contractions of the biceps brachii muscle. Simulations and experimental results were largely in agreement and show that 1) spectral variables, %Rec, and %Det are influenced by CV and degree of synchronization; 2) spectral variables are highly correlated with %Det (R = -0.95 in the simulations and -0.78 and -0.75 for the initial values and normalized slopes, respectively, in the experimental signals), and thus the information they provide on muscle properties is basically the same; and 3) variations of %Det and %Rec in response to changes in muscle properties are significantly larger than the variations of spectral variables. This study validates RQA as a means for fatigue assessment with potential advantages (such as the higher sensitivity to changes of muscle status) with respect to the classic spectral analysis.
Madeleine P, Farina D, Merletti R, et al., 2002, Upper trapezius muscle mechanomyographic and electromyographic activity in humans during low force fatiguing and non-fatiguing contractions., Eur J Appl Physiol, Vol: 87, Pages: 327-336, ISSN: 1439-6319
The purposes of this study were firstly to compare and investigate localised fatigue in the upper trapezius muscle in various arm positions as assessed by mechanomyographic (MMG) and surface electromyographic (EMG) signals and secondly to study the effects of different normalisation methods on MMG and EMG signals during non-fatiguing and fatiguing low level isometric contractions. The MMG, EMG and rate of perceived exertion were recorded from 11 subjects in five arm positions (0 degrees abduction and 0 degrees flexion, 45 degrees and 90 degrees flexion, 45 degrees and 90 degrees abduction) with different bilateral arm loads during 3 s for non-fatiguing (0-0.5-1 kg hand-load) and 3 min for fatiguing contractions (1 kg hand-load). The root mean square (RMS), average rectified value (ARV), mean power frequency (MNF), and median power frequency (MDF) of the MMG and EMG signals were computed and normalised with respect to the initial values obtained in the current arm position or in the reference position (0 degrees abduction and 0 degrees flexion) corresponding to the normal postural activity of the trapezius muscle. For fatiguing contractions, differences in magnitude of the increase in the RMS or ARV and decrease in the MNF or MDF were observed for EMG and MMG. The MMG amplitude and spectral changes followed the subjective sensation of fatigue and were not correlated to their EMG counterparts, suggesting that they may reflect different phenomena. For non-fatiguing contractions, normalisation to the current arm position entailed the loss of dynamic amplitude changes suggesting that a single reference contraction in the middle part of the range of movement is enough for proper normalisation of EMG and MMG signals. For fatiguing contractions, normalisation of the EMG and MMG to some extent can lead to a misleading interpretation. Assessment of the upper trapezius muscle by means of MMG may be valuable in ergonomics.
Farina D, Cescon C, Merletti R, 2002, Influence of anatomical, physical, and detection-system parameters on surface EMG., Biol Cybern, Vol: 86, Pages: 445-456, ISSN: 0340-1200
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.
Farina D, Madeleine P, Graven-Nielsen T, et al., 2002, Standardising surface electromyogram recordings for assessment of activity and fatigue in the human upper trapezius muscle., Eur J Appl Physiol, Vol: 86, Pages: 469-478, ISSN: 1439-6319
The objectives of this work were to determine optimal surface electromyogram (EMG) electrode locations, and inter-electrode distance (IED), when assessing activity and fatigue in the human upper trapezius muscle. Surface EMG signals were recorded from the upper trapezius muscle of 11 healthy male subjects using a linear array of 16 surface electrodes. Five arm positions were investigated (arms at the side of the body, 45 degrees and 90 degrees flexion, 45 degrees and 90 degrees abduction). Fatiguing (1 kg hand load held for 3 min) and non-fatiguing (no load, 0.5 kg and 1 kg hand load held for 3 s) contractions were made. The variabilities of the average rectified value, root mean square, mean and median power spectral frequency and slope over time of these parameters as functions of electrode location and IED (from 5 mm over a range of 35 mm in steps of 5 mm) were quantitatively evaluated. A criterion for selecting the optimal electrode position was applied. This criterion indicated an optimal location measured from the acromion (38% of the distance from the lateral edge of acromion to the spine of the seventh cervical vertebra) which was statistically the same for all the EMG descriptors, arm positions and IED investigated. Finally, it was found that both EMG variables and indexes of muscle fatigue depended on IED which should thus be properly standardised. On the basis of the sensitivity of the EMG descriptors to electrode location and cross-talk reduction, an IED of 20 mm is suggested when a global analysis of activity in the upper trapezius muscle is made using a single pair of electrodes. This study emphasises that a surface EMG analysis of the upper trapezius muscle, following a proper placement of the electrodes and selection of IED, can give reliable indications of muscle activity and fatigue. Data on the myoelectric manifestations of muscle fatigue of the upper trapezius muscle are provided for the optimal electrode location.
Farina D, Arendt-Nielsen L, Merletti R, et al., 2002, Assessment of single motor unit conduction velocity during sustained contractions of the tibialis anterior muscle with advanced spike triggered averaging., J Neurosci Methods, Vol: 115, Pages: 1-12, ISSN: 0165-0270
This paper describes an improved spike triggered averaging technique for the assessment of control properties and conduction velocity (CV) of single motor units (MUs) of the tibialis anterior muscle during voluntary muscle contractions. The method is based on the detection of multi-channel surface EMG signals (with linear electrode arrays) and intramuscularly recorded single MU action potentials (MUAPs). Intramuscular electrodes were inserted in the muscle taking into account the MU structural properties (innervation zone, tendon locations, length of the fibers), assessed by the linear array surface EMG detection technique. An algorithm for intramuscular EMG signal decomposition is used to identify single MUAP trains. The MUAPs detected by the intramuscular EMG decomposition algorithm were used to trigger and average the multi-channel EMG signals. CV of single averaged surface MUAPs was estimated by the use of advanced signal processing methods based on multi-channel recordings which allow to consistently reduce the variance of CV estimates compared with traditional two channel delay estimators. The number of averaged potentials can thus be limited, resulting in high temporal resolution CV estimates. The developed technique was tested on recordings from the tibialis anterior muscle in 11 volunteers during fatigue. It was shown that the method allows the assessment of single MU CV changes (fatigue) as small as 0.1 m/s with less than 2 s data epochs. The method allows reliable assessment of firing rate and conduction properties of single MUs with applications for the investigation of central and peripheral fatigue mechanisms.
Merletti R, Farina D, Gazzoni M, et al., 2002, Effect of age on muscle functions investigated with surface electromyography., Muscle Nerve, Vol: 25, Pages: 65-76, ISSN: 0148-639X
The purpose of this study was to investigate changes in the surface electromyographic (EMG) signal as a means of defining age-related central and peripheral mechanisms affecting muscle fatigue. Spectral and temporal variables of the surface EMG signal were studied during voluntary isometric contractions of the dominant biceps brachii muscle in a group of 8 healthy elderly men (age range 67-86 years) and a group of 10 healthy young men (age range 23-34 years). The maximal torque developed and the rate of decrease (slope) of spectral variables and conduction velocity (CV) were statistically higher in the young subjects than in the elderly subjects. Motor unit (MU) CV distribution was also estimated from the surface EMG signal and no statistical difference was observed in its variance between the two groups. These results confirm previous findings from the tibialis anterior muscle. Thus, changes in fiber type distribution and decrease in MU firing rate with aging may be factors determining the decrease in maximal voluntary contraction torque and in myoelectric manifestations of muscle fatigue.
Farina D, Fosci M, Merletti R, 2002, Motor unit recruitment strategies investigated by surface EMG variables., J Appl Physiol (1985), Vol: 92, Pages: 235-247, ISSN: 8750-7587
During isometric contractions of increasing strength, motor units (MUs) are recruited by the central nervous system in an orderly manner starting with the smallest, with muscle fibers that usually show the lowest conduction velocity (CV). Theory predicts that the higher the velocity of propagation of the action potential, the higher the power at high frequencies of the detected surface signal. These considerations suggest that the power spectral density of the surface detected electromyogram (EMG) signal may give indications about the MU recruitment process. The purpose of this paper is to investigate the potential and limitations of spectral analysis of the surface EMG signal as a technique for the investigation of muscle force control. The study is based on a simulation approach and on an experimental investigation of the properties of surface EMG signals detected from the biceps brachii during isometric linearly increasing torque contractions. Both simulation and experimental data indicate that volume conductor properties play an important role as confounding factors that may mask any relation between EMG spectral variables and estimated CV as a size principle parameter during ramp contractions. The correlation between spectral variables and CV is thus significantly lower when the MU pool is not stable than during constant-torque isometric contractions. Our results do not support the establishment of a general relationship between spectral EMG variables and torque or recruitment strategy.
Farina D, Merletti R, 2001, An experimental and model based investigation of the potential and limitations of surface EMG spectral analysis for assessment of motor unit recruitment strategy, Pages: 1209-1212, ISSN: 0589-1019
Characteristic frequencies of surface EMG power spectrum have been used in the past as indicative of motor unit (MU) recruitment, since they are rather insensitive to changes of MU firing rates and thus they should remain constant when only rate coding is used to modulate muscle force. However, this speculation has not been yet validated by simulated and experimental data. In this paper, a model of surface EMG signal generation and detection is used to simulate EMG signals detected during linearly increasing force contractions. Different MU control strategies (corresponding to different ways for force generation by recruitment and rate coding) are simulated. A number of simulations are performed to study the effect of random distribution of MUs in the muscle's cross-section upon the surface EMG. The results are compared with those obtained analyzing the EMG signals detected experimentally during linearly increasing force contractions of the biceps brachii muscle in 10 subjects. Results show that the volume conductor properties may act as confounding factors which may mask any relationship between characteristic spectral frequencies and conduction velocity as a size principle parameter. It is concluded that more advanced signal processing techniques which aim at the analysis of single MU activity are required for the surface EMG based assessment of central nervous system control strategy.
Farina D, Cescon C, 2001, Concentric-ring electrode systems for noninvasive detection of single motor unit activity., IEEE Trans Biomed Eng, Vol: 48, Pages: 1326-1334, ISSN: 0018-9294
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.
Farina D, Colombo R, Merletti R, et al., 2001, Evaluation of intra-muscular EMG signal decomposition algorithms., J Electromyogr Kinesiol, Vol: 11, Pages: 175-187, ISSN: 1050-6411
We propose and test a tool to evaluate and compare EMG signal decomposition algorithms. A model for the generation of synthetic intra-muscular EMG signals, previously described, has been used to obtain reference decomposition results. In order to evaluate the performance of decomposition algorithms it is necessary to define indexes which give a compact but complete indication about the quality of the decomposition. The indexes given by traditional detection theory are in this paper adapted to the multi-class EMG problem. Moreover, indexes related to model parameters are also introduced. It is possible in this way to compare the sensitivity of an algorithm to different signal features. An example application of the technique is presented by comparing the results obtained from a set of synthetic signals decomposed by expert operators having no information about the signal features using two different algorithms. The technique seems to be appropriate for evaluating decomposition performance and constitutes a useful tool for EMG signal researchers to identify the algorithm most appropriate for their needs.
Farina D, Merletti R, 2001, A novel approach for precise simulation of the EMG signal detected by surface electrodes., IEEE Trans Biomed Eng, Vol: 48, Pages: 637-646, ISSN: 0018-9294
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.
Farina D, Muhammad W, Fortunato E, et al., 2001, Estimation of single motor unit conduction velocity from surface electromyogram signals detected with linear electrode arrays., Med Biol Eng Comput, Vol: 39, Pages: 225-236, ISSN: 0140-0118
This work addresses the problem of estimating the conduction velocity (CV) of single motor unit (MU) action potentials from surface EMG signals detected with linear electrode arrays during voluntary muscle contractions. In ideal conditions, that is without shape or scale changes of the propagating signals and with additive white Gaussian noise, the maximum likelihood (ML) is the optimum estimator of delay. Nevertheless, other methods with computational advantages can be proposed; among them, a modified version of the beamforming algorithm is presented and compared with the ML estimator. In real cases, the resolution in delay estimation in the time domain is limited because of the sampling process. Transformation to the frequency domain allows a continuous estimation. A fast, high-resolution implementation of the presented multichannel techniques in the frequency domain is proposed. This approach is affected by a negligible decrease in performance with respect to ideal interpolation. Application of the ML estimator, based on two-channel information, to ten firings of each of three MUs provides a CV estimate affected by a standard deviation of 0.5 m s(-1); the modified beamforming and ML estimators based on five channels provide a CV standard deviation of less than 0.1 m s(-1) and allow the detection of statistically significant differences between the CVs of the three MUs. CV can therefore be used for MU classification.
Muhammad W, Meste O, Rix H, et al., 2001, A novel approach for joint estimation of time delay and scale factor with applications to the M-wave analysis, Pages: 1093-1096, ISSN: 0589-1019
In this paper we propose a method for joint estimation of delay and scale factor between two deterministic and unknown signals. The method is based on the separation of the two parameters. The scale factor is estimated from the autocorrelation functions (ACFs) of the two signals. The ACFs are independent on the delay while they maintain the scale factor. The delay is estimated by scaling one of the two signals by the estimated scale factor, so that the delay estimation is not biased by the scale factor. The method proposed is compared with the maximum likelihood joint estimation and provides better performance for a rather large range of signal to noise ratios. Potential applications of the technique in surface EMG signal analysis are discussed and results related to the M-wave processing are reported.
Meste O, Muhammad W, Rix H, et al., 2001, On the estimation of muscle fiber conduction velocity using a co-linear electrodes array, Pages: 1101-1104, ISSN: 0589-1019
The problem of estimating the average Conduction Velocity (CV) in the muscle fibers is considered. The velocity is estimated from an array of noisy deterministic and unknown Motor Unit Action Potentials (MUAP) acquired by an array of K co-linear electrodes. In this array a vector of (K-1) independent time delays (TD) are to be estimated. For a given length of the array, the number K has to be determined in order to improve the estimation of the velocity. In this communication we show the influence of the value of K in the CV estimation in presence of noise and changes in the MUAP shape along the array.
Farina D, Arendt-Nielsen L, Merletti R, et al., 2001, A spike triggered averaging technique for high resolution assessment of single motor unit conduction velocity changes during fatiguing voluntary contractions, Pages: 1097-1100, ISSN: 0589-1019
In this paper we propose an improved spike triggered averaging technique for the assessment of control properties and conduction velocity (CV) of single motor units (MUs) during voluntary sub-maximal muscle contractions. The method is based on the detection of multi-channel surface EMG signals (with linear electrode arrays) and intramuscular recorded single MU action potentials (MUAPs). Intramuscular electrodes are inserted taking into account the MU structural properties (innervation zone and tendon locations, length of the fibers), assessed by the linear array surface EMG detection. A technique for intramuscular EMG signal decomposition is used to identify single M UAP trains. The M UAPs obtained from the intramuscular EMG decomposition algorithm are used to trigger and average the multi-channel EMG signals. CV of single averaged surface M UAPs is estimated by the use of advanced signal processing methods based on multi-channel recordings which allow to consistently reduce the variance of CV estimates with respect to traditional two channel delay estimators. The number of averaged potentials can thus be reduced, improving temporal resolution. The technique proposed is tested with recordings from the tibialis anterior muscle of 11 volunteers. It is shown that the method allows the assessment of CV changes (fatigue) of single MUs as small as 0.1 m/s with a limited number of averages (temporal resolution of 1-2 seconds), leading to a consistent improvement with respect to traditional surface EMG spike triggered averaging techniques. The method has potential usefulness in a number of basic and applied research fields.
Merletti R, Farina D, Gazzoni M, et al., 2001, Surface electromyography: A window on the muscle, a glimpse on the central nervous system, Europa Medicophysica, Vol: 37, Pages: 57-68, ISSN: 0014-2573
This work provides an overview of the state of the art in the field of surface EMG for non invasive characterization of muscles and identification of CNS muscle control strategies: it is in part a tutorial and in part a review. The mechanisms of EMG signal generation, propagation, detection, processing and interpretation are briefly summarized. The main results of the European Concerted Action "Surface EMG for Non Invasive Assessment of Muscles" (SENIAM) are outlined. Specific attention is focused on the key issue of proper electrode location over the muscle, that is in between the innervation zone and the muscle tendon junction. The information content of multichannel EMG obtained with an electrode array is described and the concept of motor unit (MU) signature is explained. The recognition and classification of MU signatures during an isometric contraction strongly supports the possibility of surface EMG decomposition into the constituent (superficial) motor unit action potential trains: examples are given. Applications for monitoring myoelectric manifestations of muscle fatigue are presented as well as applications in gait analysis. Most applications of the technique are very "treacherous" and require specific competence and knowledge. The incorrect modalities of data collection and interpretation are outlined.
Farina D, Crosetti A, Merletti R, 2001, A model for the generation of synthetic intramuscular EMG signals to test decomposition algorithms., IEEE Trans Biomed Eng, Vol: 48, Pages: 66-77, ISSN: 0018-9294
As more and more intramuscular electromyogram (EMG) decomposition programs are being developed, there is a growing need for evaluating and comparing their performances. One way to achieve this goal is to generate synthetic EMG signals having known features. Features of interest are: the number of channels acquired (number of detection surfaces), the number of detected motor unit action potential (MUAP) trains, their time-varying firing rates, the degree of shape similarity among MUAPs belonging to the same motor unit (MU) or to different MUs, the degree of MUAP superposition, the MU activation intervals, the amount and type of additive noise. A model is proposed to generate one or more channels of intramuscular EMG starting from a library of real MUAPs represented in a 16-dimensional space using their Associated Hermite expansion. The MUAP shapes, regularity of repetition rate, degree of superposition, activation intervals, etc. may be time variable and are described quantitatively by a number of parameters which define a stochastic process (the model) with known statistical features. The desired amount of noise may be added to the synthetic signal which may then be processed by the decomposition algorithm under test to evaluate its capability of recovering the signal features.
Merletti R, Rainoldi A, Farina D, 2001, Surface electromyography for noninvasive characterization of muscle., Exerc Sport Sci Rev, Vol: 29, Pages: 20-25, ISSN: 0091-6331
Surface electromyography for noninvasive characterization of muscle. Exerc. Sport Sci. Rev., Vol. 29, No. 1, pp 20-25, 2001. Linear electrode arrays are used for noninvasive muscle characterization to study individual motor unit properties and the myoelectric manifestations of muscle fatigue during sustained contractions. The location of an electrode pair with respect to the innervation zone(s), the deterministic rather than stochastic nature of the signal, and the possibility of noninvasive fiber typing are discussed.
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