A Computational System for Real-Time Muscle Fatigue Monitoring Using Synthetic EMG Signals from the Gastrocnemius

The authors investigated fatigue-induced changes in the frequency content of the surface electromyographic (EMG) signal from the erector spinae muscles. The objective of the study was to understand the EMG changes in fatiguing muscle and to obtain a reliable index of fatigue. Power spectral analysis has been used increasingly in recent years to monitor muscle fatigue, but parameters other than the mean or median frequency have received little attention. Thirty-five healthy volunteers participated. They pulled upward with constant force on a handlebar attached to a floor-mounted load cell while the EMG signal from the erector spinae was recorded at the levels of T10 and L3 at 1024 Hz; 1.0-sec "windows" of the signal were analyzed using fast Fourier transforms, and the resulting power spectra were divided into 10 frequency bands between 5 Hz and 300 Hz. The median frequency, total power, and peak amplitude of the spectra were also calculated. Changes in the frequency content of the EMG signal were examined during submaximal contractions of different intensity and duration. Median frequency decreased steadily during the contractions, whereas total power and peak amplitude increased. The most repeatable and linear index of change was the increase in the EMG signal in the 5-30 Hz frequency band. The middle-to-high frequency component of the EMG signal increased during the early stages of the contractions, but decreased as the endurance limit was approached. Changes in the 5-30 Hz band of the EMG power spectrum provide a more reliable and linear index of fatigue in the erector spinae muscles than do changes in median frequency. In the erector spinae, the early effects of fatigue appear to be delayed by the recruitment of additional motor units.

Fatigue and muscle activation during submaximal elbow flexion in children with cerebral palsy

as the final common pathway from the nervous system to muscle, the motor unit transmits an activation signal generated by the nervous system to engage the contractile proteins and produce the muscle forces needed for reflex responses, automatic behaviors, and voluntary actions ([11][1]). The net

The surface electromyogram (EMG) comprises the sum of the electrical contributions made by the active motor units to the interference signal detected by electrodes placed on the skin overlying the muscle. Because it provides a global measure of motor unit activity, this signal is a valuable tool for

HIGHLIGHTED TOPICSNeural Control of MovementCommentaryGary C. SieckGary C. SieckPublished Online:01 Apr 2004https://doi.org/10.1152/japplphysiol.00074.2004MoreSectionsPDF (12 KB)Download PDF ToolsExport citationAdd to favoritesGet permissionsTrack citations This issue of the Journal introduces the second Highlighted Topics series for 2004, “Neural Control of Movement.” Three outstanding articles in this issue contribute important findings that advance our knowledge of neuromotor control and muscle fatigue.Motor units are the basic functional elements of neuromuscular control. In an article entitled “Low threshold motor unit membrane properties vary with contraction intensity during sustained activation with surface EMG visual feedback,” Dr. D. Farina and colleagues (1) illustrate the utility of visual feedback of surface multichannel EMG signals to control the activity of single motor units. After training subjects to vary the force of the abductor pollicis and abductor digiti minimi, these investigators used surface EMG recordings of these muscles to observe a single dominant motor unit and modulate its firing rate around two target values for a brief period. Using this noninvasive feedback technique, Farina and colleagues analyzed properties of single motor units during and after periods of sustained activity. It was found that motor unit conduction velocity changed significantly with motor unit firing rate and as a consequence of sustained activity. The slowing of conduction velocity over time was greater for higher sustained motor unit firing rates. These results indicate that changes in single motor unit conduction velocity is one of the earliest signs of peripheral modifications in the neuromuscular system induced by sustained contractions. This investigation also revealed a correlation between single motor unit conduction velocity and instantaneous firing rate, indicating an effect of interpulse interval on muscle fiber membrane properties. During sustained activity of these muscles, both recruitment of additional motor units and motor unit substitution occurred. Thus this study clearly demonstrates the utility of surface EMG recording and visual feedback in the noninvasive analysis of peripheral properties of the neuromuscular system at the level of motor units.Although numerous studies have explored muscle fatigue, the causes of task failure during dynamic contractions (the most frequent modality in activities of daily living) have not been carefully investigated. In a study entitled “Limiting mechanisms of force production after repetitive dynamic contractions in human triceps surae,” Klass and colleagues (2) assess the mechanisms that limit muscle performance after a series of brief moderate dynamic contractions. These investigators examined the neuromuscular adjustments in the human triceps surae muscle through a combination of voluntary, reflex, and electrically induced contractions. They observed that both the range of motion about the ankle joint and maximal voluntary force were reduced after a fatiguing task and that the force-generating capacity of the muscle was more significantly affected at short lengths than at neutral length. Furthermore, although central fatigue and neuromuscular propagation were not significantly altered after the fatigue task, there was a small modulation in spinal reflex activities. The apparent decline in spinal excitatory afferent inputs to the motoneuron pool did not have a direct deleterious effect on voluntary activation. In contrast, alterations in the time course of twitch and postactivation potentiation indicated that intracellular mechanisms limited force production after the fatiguing task. Contrary to sustained isometric efforts, the force decline after brief dynamic contractions did not involve neural mechanisms. These findings therefore support the “task dependency” concept, that the mechanisms responsible for muscle fatigue depend on the task performed. It also emphasizes the need to investigate the mechanisms of task failure rather than to identify a global cause for muscle fatigue.Also focusing on muscle fatigue, Dr. G. Sjøgaard and colleagues (3) explore neural control during voluntary shoulder movements and positions in the third featured article in this issue, entitled “Intramuscular pressure and EMG relate during static contractions but dissociate with movement and fatigue.” These investigators used measures of electrical muscle activation (EMG) and mechanical muscular response (intramuscular pressure or IMP) to evaluate tissue exertion. Compared with static contractions, both electrical and mechanical peak responses were larger; however, only EMG was velocity dependent, whereas IMP was not. These observations suggest that maintaining shoulder position involves lower exertion than does moving toward the same position (in this study, 90° shoulder abduction). From this point of view, dynamic activity is not considered preferential to static activity, in contrast to what is often stated in occupational settings. While imposing prolonged, sustained shoulder positioning, these investigators evaluated both muscular fatigue and load sharing between shoulder stabilizers (supraspinatus and trapezius muscles) and prime movers (deltoideus muscle). In supraspinatus, EMG amplitude increased, suggesting development of fatigue. Surprisingly, in contrast, IMP did not increase, and for most subjects IMP actually decreased, indicating an attenuation in force contribution. EMG results indicated that fatigue development in the supraspinatus muscle was actually underestimated, since fatigue would have been even larger had the same force been maintained. Interestingly, the large increase in EMG activity in the trapezius and deltoideus muscles may not be due solely to fatigue but may also relate to increases in force development in these muscles. This interpretation is particular to the trapezius muscle and is supported by relatively fast recovery, indicating less fatigue than in the other two muscles. The development of fatigue may modulate load sharing between synergistic muscles and can be revealed by EMG recordings only when used in combination with other measures such as IMP. References 1 Farina D, Gazzoni M, and Camelia F. Low-threshold motor unit membrane properties vary with contraction intensity during sustained activation with surface EMG visual feedback. J Appl Physiol 96: 1505-1515, 2004.Link | ISI | Google Scholar2 Klass M, Guissard N, and Duchateau J. Limiting mechanisms of force production after repetitive dynamic contractions in human triceps surae. J Appl Physiol 96: 1516-1521, 2004.Link | ISI | Google Scholar3 Sjøgaard G, Jensen BR, Hargens AR, and Søgaard K. Intramuscular pressure and EMG relate during static contractions but dissociate with movement and fatigue. J Appl Physiol 96: 1522-1529, 2004.Link | ISI | Google Scholar Download PDF Previous Back to Top Next FiguresReferencesRelatedInformation More from this issue > Volume 96Issue 4April 2004Pages 1504-1504 Copyright & PermissionsCopyright © 2004 the American Physiological Societyhttps://doi.org/10.1152/japplphysiol.00074.2004History Published online 1 April 2004 Published in print 1 April 2004 Metrics

Muscle fatigue is characterised by a decrease in the ability of muscles to perform required functions, which is accompanied by accumulation of metabolites, changes in ionic balance and electrical properties of muscle tissue. These physiological changes lead to marked transformations of electromyographic (EMG) signals, including a shift of their spectrum to lower frequencies. Such changes affect the quality of signal recognition and control accuracy of bioelectric prostheses, since most myoelectric control algorithms are based on the stability of spectral and amplitude characteristics of EMG signals. This paper investigates the influence of muscle fatigue on the characteristics of EMG signals and the accuracy of myoelectric control in bioelectric upper limb prostheses. The physiological mechanisms underlying changes in EMG signals during fatigue are analysed, including a slowing of the rate of conduction of action potentials along muscle fibres and changes in the recruitment of motor units. These factors result in decreased median frequency and increased amplitude of EMG signals, making it difficult to accurately classify and control them with a prosthesis. To address this problem, a method of muscle fatigue compensation based on adjusting the median frequency of the EMG signal is considered. The method is a spectral analysis of the current EMG signal to determine its median frequency and subsequent scaling of the time axis of the signal. This allows shifting the signal spectrum back to the higher frequencies characteristic of the fatigued state of the muscle and restoring the original spectral characteristics of the signal. Keywords: Bioelectric prosthesis, Electromyographic signals (EMG), myoelectric control, muscle fatigue, Adaptive classification algorithms, Biosignal processing

The aim of the study was to investigate the adaptations of motor unit discharge rate and additional motor unit recruitment in different regions of the upper trapezius muscle during sustained contraction. Intramuscular EMG signals were recorded from three locations (cranial, middle, and caudal) within the upper trapezius of eleven healthy men during 60-s static shoulder abduction at 25% of the maximal force. Surface EMG signals were recorded concurrently with a 10 x 5 electrode grid. Fifty-one (cranial location), 39 (middle), and 19 (caudal) motor units were identified from the intramuscular EMG signals. Motor unit discharge rates at the beginning of the contraction were greater in the caudal than in the other two locations (cranial: 16.5 +/- 3.4 pps; n = 28, middle: 16.2 +/- 3.4 pps; n = 32, caudal: 19.6 +/- 3.1 pps; n = 13; P < 0.05). Because the decrease in discharge rate over time was larger for the caudal location, at the end of the contraction the discharge rates were comparable at all locations (cranial: 15.7 +/- 3.3 pps; n = 28, middle: 14.9 +/- 2.3 pps; n = 32, caudal: 15.8 +/- 3.6 pps; n = 13). Additional motor unit recruitment was observed in all locations but more frequently in the caudal region (19 motor units recruited after the beginning of the contraction vs. only 4 in each of the other two locations). The mean position of the distribution of surface EMG amplitude over the grid moved by 1.4 +/- 0.7 mm (P < 0.001) in the cranial direction at the end with respect to the beginning of the contraction. The results showed that the neural drive received by the upper trapezius depends on the muscle region, which may indicate non-uniform descending drive to the motor neuron pool.

Conduction velocity in ischemic muscle: effect on EMG frequency spectrum.

The main aim of the present study was to examine the effect of the maximum voluntary contraction (MVC) on the mean absolute value (MAV) and on the median frequency (MDF) of simulated surface electromyographic (sEMG) signals generated in a cylindrical, multilayer, volume conductor constituted by bone, muscle, fat, and skin layers and detected by the longitudinal single (LSD) and double (LDD) differential systems. The study was made for two values (5 and 10 mm) of the interelectrode distances (IED) and three values (20, 25, and 30 Hz) of the peak firing rate (PFR) of the first recruited motor unit (MU) in the case of narrow (30%) and broad (70%) recruitment ranges (RRs) of MU when the MVC level varied from 10% to 100% in steps of 10%. The results show that an increase of MVC level leads to an increase of MAV and a decrease of MDF of the simulated sEMG signals. Moreover, for the same RR of MU, the MAV values were larger for the large IED and the large PFR. However, with the MDF values, inverse results were obtained.

ObjectiveTo investigate the electrophysiological basis of pyridostigmine enhancement of endurance performance documented earlier in patients with spinal muscular atrophy (SMA). MethodsWe recorded surface electromyography (sEMG) in four upper extremity muscles of 31 patients with SMA types 2 and 3 performing endurance shuttle tests (EST) and maximal voluntary contraction (MVC) measurements during a randomized, double blind, cross-over, phase II trial. Linear mixed effect models (LMM) were used to assess the effect of pyridostigmine on (i) time courses of median frequencies and of root mean square (RMS) amplitudes of sEMG signals and (ii) maximal RMS amplitudes during MVC measurements. These sEMG changes over time indicate levels of peripheral muscle fatigue and recruitment of new motor units, respectively. ResultsIn comparison to a placebo, patients with SMA using pyridostigmine had fourfold smaller decreases in frequency and twofold smaller increases in amplitudes of sEMG signals in some muscles, recorded during ESTs (p < 0.05). We found no effect of pyridostigmine on MVC RMS amplitudes. ConclusionssEMG parameters indicate enhanced low-threshold (LT) motor unit (MU) function in upper-extremity muscles of patients with SMA treated with pyridostigmine. This may underlie their improved endurance. SignificanceOur results suggest that enhancing LT MU function may constitute a therapeutic strategy to reduce fatigability in patients with SMA.

Electromyography (EMG) detects electrically or neurogically activated muscle cells on the basis of waveform characteristics from a recorded signal. EMG is useful for evaluating and recording movement abnormalities. The EMG signals can also detect neuromuscular activation level and recruitment order in addition to analyze the biomechanics of human or animal movement (De Luca, 1984; Furey, 1963). The EMG signals are generated based on superimposed motor action potentials during active movement. The myoelectric signals are the instantaneous algebraic summation of all electrical discharges produced by a contraction of the muscle fibers. Muscle fatigue is quantified using surface EMG signals based on the power spectrum which is the Fourier transform of EMG time series (Knowlton et al., 1951; Mannion & Dolan, 1994; Mannion et al., 1997c). Normal electrical source is a muscle membrane potential of approximately -90 mV, and measured EMG potentials range between less than 50 μV and up to 20 to 30 mV, depending on the muscle under observation (Herzog et al., 1987; Nigg et al., 1988). Typical repetition rate of muscle motor unit firing is approximately 7–20 Hz, depending on the size of the muscle, previous axonal damage, and other factors (Hoffmann, 1968; Rack & Ross, 1975). Therefore, the EMG range can be utilized in many clinical and biomechanical applications as a diagnostics tool for identifying neuromuscular diseases, assessing low back pain (LBP), kinesiology, and disorders of motor control. EMG signals are also used as a control signal for prosthetic devices such as prosthetic hands, arms, and lower limbs. It is unknown how the median frequency (MF) of an individual depends on posture, extent of physical activity prior to measurements, and other attributing factors. Such factors may influence the shift of the MF in the fatigue measurement, which is not a consistent indicator for injuries to low back muscles. Subjects with LBP have less endurance and thus smaller MF during sustained muscle contractions (Mannion et al., 1997a; Roy et al., 1997). The MF of the EMG signal is used to characterize physiological aspects of skeletal muscles. The signal from surface EMG is the instantaneous algebraic summation of action potentials from muscle fibers, and its power spectrum can be estimated from a fast Fourier transform of the signal. Fourier transform is a linear analysis of a signal and gives the power spectrum P(f) (Hobbie, 1997). A linear system is described mathematically by equations with oscillatory or exponentially growing solutions. In contrast, EMG time series have an irregular pattern so

We investigated the firing rate of motor units in the vastus lateralis muscle in five healthy young men (mean = 21.4 yr, SD = 0.9) during a sequence of isometric constant-torque contractions repeated to exhaustion. The contractions were sustained at 20% of the maximal voluntary level, measured at the beginning of the test sequence. Electromyographic (EMG) signals were recorded via quadrifilar fine-wire electrodes and subsequently decomposed into their constituent motor unit action potentials to obtain the motor unit firing times. In addition, we measured the whole muscle mechanical properties during the fatigue task using electrical stimulation. The firing rate of motor units first decreased within the first 10-20% of the endurance time of the contractions and then increased. The firing rate increase was accompanied by recruitment of additional motor units as the force output remained constant. The elicited twitch and tetanic torque responses first increased and then decreased. The two processes modulated in a complementary fashion at the same time. Our data suggest that, when the vastus lateralis muscle is activated to maintain a constant torque output, its motoneuron pool receives a net excitatory drive that first decreases to compensate for the short-lived potentiation of the muscle force twitch and then increases to compensate for the diminution of the force twitch. The underlying inverse relationship between the firing rate and the recruitment threshold that has been reported for nonfatigued contractions is maintained. We, therefore, conclude that the central nervous system control of vastus lateralis motor units remains invariant during fatigue in submaximal isometric isotonic contractions.

The physiological mechanisms determining the progressive decline in the maximal muscle torque production capacity during isometric contractions to task failure are known to depend on task demands. Task-specificity of the associated adjustments in motor unit discharge rate (MUDR), however, remains unclear. This study examined MUDR adjustments during different submaximal isometric knee extension tasks to failure. Participants performed a sustained and an intermittent task at 20% and 50% of maximal voluntary torque (MVT), respectively (Experiment 1). High-density surface EMG signals were recorded from vastus lateralis (VL) and medialis (VM) and decomposed into individual MU discharge timings, with the identified MUs tracked from recruitment to task failure. MUDR was quantified and normalised to intervals of 10% of contraction time (CT). MUDR of both muscles exhibited distinct modulation patterns in each task. During the 20% MVT sustained task, MUDR decreased until ∼50% CT, after which it gradually returned to baseline. Conversely, during the 50% MVT intermittent task, MUDR remained stable until ∼40-50% CT, after which it started to continually increase until task failure. To explore the effect of contraction intensity on the observed patterns, VL and VM MUDR was quantified during sustained contractions at 30% and 50% MVT (Experiment 2). During the 30% MVT sustained task, MUDR remained stable until ∼80-90% CT in both muscles, after which it continually increased until task failure. During the 50% MVT sustained task the increase in MUDR occurred earlier, after ∼70-80% CT. Our results suggest that adjustments in MUDR during submaximal isometric contractions to failure are contraction modality- and intensity-dependent. KEY POINTS: During prolonged muscle contractions a constant motor output can be maintained by recruitment of additional motor units and adjustments in their discharge rate. Whilst contraction-induced decrements in neuromuscular function are known to depend on task demands, task-specificity of motor unit discharge behaviour adjustments is still unclear. In this study, we tracked and compared discharge activity of several concurrently active motor units in the vastii muscles during different submaximal isometric knee extension tasks to failure, including intermittent vs. sustained contraction modalities performed in the same intensity domain (Experiment 1), and two sustained contractions performed at different intensities (Experiment 2). During each task, motor units modulated their discharge rate in a distinct, biphasic manner, with the modulation pattern depending on contraction intensity and modality. These results provide insight into motoneuronal adjustments during contraction tasks posing different demands on the neuromuscular system.

A 55-year-old woman was admitted to the hospital with unstable gait followed by four-limb weakness with lower limb predominance. Several days before the onset of neurological symptoms, she developed mild respiratory symptoms, generalized myalgias without fever, and an episode of diarrhea. On initial examination, she demonstrated moderate weakness mainly affecting the lower limbs (she could stand but was unable to walk), decreased proprioception, distal hypoesthesia, and generalized areflexia. A polymerase chain reaction nasal swab test was positive for severe acute respiratory syndrome–coronavirus 2; respiratory support was not required. Blood tests, cerebrospinal fluid analysis, chest X ray, and cranial computed tomography revealed no abnormalities. Due to suspected Guillain-Barré syndrome (GBS), electrodiagnostic studies (EDx) were performed on day 9 after admission, and the patient was treated with intravenous immunoglobulin 0.4 g/kg for 5 days. An initial nerve conduction study (NCS) revealed increased temporal dispersion (158%) and reduced proximal/distal compound muscle action potential (CMAP) size (0.5) in the right median and ulnar nerves with elbow stimulation (normal distal CMAP), reduced tibial conduction velocities bilaterally (29 m/s), and absent tibial and median F waves. Thus, the patient met three criteria for demyelinating polyneuropathy.1 Electromyographic signals were recorded, using a 38 × 0.45-mm Neuroline concentric needle (Ambu, Ballerup, Denmark), from the right deltoid, extensor digitorum communis, first dorsal interosseous, tensor fascia latae, and vastus lateralis, and bilaterally from the tibialis anterior and gastrocnemius, and then bandpass filtered at 20 Hz to 10 kHz and stored using a KeyPoint.Net 3.22 device (Alpine Biomed, Fountain Valley, California). Spontaneous activity was qualitatively analyzed and motor unit potentials (MUPs) from electromyographic (EMG) signals with 200 ± 50 turns/s were quantitatively analyzed offline using decomposition-based quantitative EMG2 and near-fiber EMG (NFEMG),3, 4 which together aid in the diagnosis of neuromuscular disorders by quantifying intrinsic motor unit (MU) morphological and electrophysiological properties. A near-fiber MUP (NFM) is created by low-pass double-differentiation filtering a MUP, which, like SFEMG bandpass filtering, emphasizes contributions from fibers close to the needle detection surface (near fibers [NFs]). MUP area represents MU size. NFM duration (the time between the NFM onset and end positions) and NFM dispersion (the time between the first and last detected NF contribution) do not reflect MU size; rather, they reflect MU electrophysiological temporal dispersion (ie, differences in MU axonal branch conduction, neuromuscular junction [NMJ] transmission, and muscle fiber action potential [MFAP] conduction times). NFM segment jitter reflects NFM temporal instabilities, caused by variability in MU axonal branch conduction, NMJ transmission, and MFAP conduction times. Initially, low-amplitude and -frequency positive sharp waves and fibrillation potentials were recorded bilaterally from the tibialis anterior and gastrocnemius. Recruitment was reduced in all muscles sampled, with a predominance of large-area and irregularly shaped MUPs recorded from early-recruited MUs (more pronounced in distal lower limb muscles). Initial NFEMG measures showed increased dispersion and segment jitter in nearly all lower limb muscles sampled (Figure 1). Subsequent EDx, performed 5 weeks later, showed improved NCS results. Although the criteria for demyelinating polyneuropathy were still met, significant clinical improvement was seen, as the patient was able to walk with minor assistance. In addition, MUP area, NFM dispersion, and segment jitter were all reduced Figure 1. Figure 2 shows examples of initial and subsequently recorded MUPs and NFMs. In GBS, early recruitment of MUs with large MUPs is a consequence of conduction block affecting small-diameter axons.5 However, the electrophysiology of MUPs in GBS (ie, quantification of MUP size, temporal dispersion, and stability) is not usually included in the diagnostic protocols for GBS.6 Our results could be explained by both a transient impairment of smaller diameter myelinated motor axons (possibly a consequence of conduction block affecting proximal nerve segments, manifesting as early recruitment of large MUs and reduced numbers of small area MUPs) and possible transient electrophysiological impairment of either MU distal axonal branches or their NMJs (manifesting as transient increased NFM dispersion and segment jitter). Also, axonal degeneration and rapid regeneration of short myelinated segments of intramuscular terminal axonal branches has been associated with immune-mediated subtypes of GBS,7 which could explain the early active denervation and rapid motor recovery observed. These findings support the combined use of EMG and NFEMG in suspected polyneuropathy. Because MUP area reflects MU size while NFM duration, dispersion, and stability reflect MU electrophysiological dispersion and stability, respectively, their combined use can provide valuable information for early diagnosis and management of treatable disorders. The authors declare no potential conflicts of interest. We confirm that we have read the Journal's position on issues involved in ethical publication and affirm that this report is consistent with those guidelines. Data available on request due to privacy/ethical restrictions

We developed a model to investigate the influence of the muscle force twitch on the simulated firing behavior of motoneurons and muscle force production during voluntary isometric contractions. The input consists of an excitatory signal common to all the motor units in the pool of a muscle, consistent with the "common drive" property. Motor units respond with a hierarchically structured firing behavior wherein at any time and force, firing rates are inversely proportional to recruitment threshold, as described by the "onion skin" property. Time- and force-dependent changes in muscle force production are introduced by varying the motor unit force twitches as a function of time or by varying the number of active motor units. A force feedback adjusts the input excitation, maintaining the simulated force at a target level. The simulations replicate motor unit behavior characteristics similar to those reported in previous empirical studies of sustained contractions: 1) the initial decrease and subsequent increase of firing rates, 2) the derecruitment and recruitment of motor units throughout sustained contractions, and 3) the continual increase in the force fluctuation caused by the progressive recruitment of larger motor units. The model cautions the use of motor unit behavior at recruitment and derecruitment without consideration of changes in the muscle force generation capacity. It describes an alternative mechanism for the reserve capacity of motor units to generate extraordinary force. It supports the hypothesis that the control of motoneurons remains invariant during force-varying and sustained isometric contractions.