Spectral compression of the electromyographic signal due to decreasing muscle fiber conduction velocity

Tutorial. Frequency analysis of the surface EMG signal: Best practices

This tutorial is aimed primarily to non-engineers (clinical researchers, clinicians, neurophysiology technicians, ergonomists, movement and sport scientists, physical therapists) or beginners using, or planning to use, surface electromyography (sEMG) as a monitoring and assessment tool for muscle and neuromuscular evaluations in the prevention and rehabilitation fields. Its first purpose is to explain, with minimal mathematics, basic concepts related to: (a) time and frequency domain description of a signal, (b) Fourier transform, (c) amplitude, phase, and power spectrum of a signal, (d) sampling of a signal, (e) filtering of sEMG signals, (f) cross-spectrum and coherence between two signals, (g) signal stationarity and criteria for epoch selection, (h) myoelectric manifestations of muscle fatigue and (i) fatigue indices. These concepts are consolidated knowledge and are addressed and discussed with examples taken from the literature.

Spatial Dependence of Log-Transformed Electromyography-Force Relation: Model-Based Sensitivity Analysis and Experimental Study of Biceps Brachii

This study investigated electromyography (EMG)-force relations using both simulated and experimental approaches. A motor neuron pool model was first implemented to simulate EMG-force signals, focusing on three different conditions that test the effects of small or large motor units located more or less superficially in the muscle. It was found that the patterns of the EMG-force relations varied significantly across the simulated conditions, quantified by the slope (b) of the log-transformed EMG-force relation. b was significantly higher for large motor units, which were preferentially located superficially rather than for random depth or deep depth conditions (p < 0.001). The log-transformed EMG-force relations in the biceps brachii muscles of nine healthy subjects were examined using a high-density surface EMG. The slope (b) distribution of the relation across the electrode array showed a spatial dependence; b in the proximal region was significantly larger than the distal region, whereas b was not different between the lateral and medial regions. The findings of this study provide evidence that the log-transformed EMG-force relations are sensitive to different motor unit spatial distributions. The slope (b) of this relation may prove to be a useful adjunct measure in the investigation of muscle or motor unit changes associated with disease, injury, or aging.

A Simulation Study to Assess the Factors of Influence on Mean and Median Frequency of sEMG Signals during Muscle Fatigue

Mean and Median frequency are typically used for detecting and monitoring muscle fatigue. These parameters are extracted from power spectral density whose estimate can be obtained by several techniques, each one characterized by advantages and disadvantages. Previous works studied how the implementation settings can influence the performance of these techniques; nevertheless, the estimation results have never been fully evaluated when the power density spectrum is in a low-frequency zone, as happens to the surface electromyography (sEMG) spectrum during muscle fatigue. The latter is therefore the objective of this study that has compared the Welch and the autoregressive parametric approaches on synthetic sEMG signals simulating severe muscle fatigue. Moreover, the sensitivity of both the approaches to the observation duration and to the level of noise has been analyzed. Results showed that the mean frequency greatly depends on the noise level, and that for Signal to Noise Ratio (SNR) less than 10dB the errors make the estimate unacceptable. On the other hand, the error in calculating the median frequency is always in the range 2-10 Hz, so this parameter should be preferred in the tracking of muscle fatigue. Results show that the autoregressive model always outperforms the Welch technique, and that the 3rd order continuously produced accurate and precise estimates; consequently, the latter should be used when analyzing severe fatiguing contraction.

Respiratory Inductance Plethysmography to Assess Fatigability during Repetitive Work

Cumulative fatigue during repetitive work is associated with occupational risk and productivity reduction. Usually, subjective measures or muscle activity are used for a cumulative evaluation; however, Industry 4.0 wearables allow overcoming the challenges observed in those methods. Thus, the aim of this study is to analyze alterations in respiratory inductance plethysmography (RIP) to measure the asynchrony between thorax and abdomen walls during repetitive work and its relationship with local fatigue. A total of 22 healthy participants (age: 27.0 ± 8.3 yrs; height: 1.72 ± 0.09 m; mass: 63.4 ± 12.9 kg) were recruited to perform a task that includes grabbing, moving, and placing a box in an upper and lower shelf. This task was repeated for 10 min in three trials with a fatigue protocol between them. Significant main effects were found from Baseline trial to the Fatigue trials (p < 0.001) for both RIP correlation and phase synchrony. Similar results were found for the activation amplitude of agonist muscle (p < 0.001), and to the muscle acting mainly as a joint stabilizer (p < 0.001). The latter showed a significant effect in predicting both RIP correlation and phase synchronization. Both RIP correlation and phase synchronization can be used for an overall fatigue assessment during repetitive work.

Muscle Fatigue Revisited – Insights From Optically Pumped Magnetometers

So far, surface electromyography (sEMG) has been the method of choice to detect and evaluate muscle fatigue. However, recent advancements in non-cryogenic quantum sensors, such as optically pumped magnetometers (OPMs), enable interesting possibilities to flexibly record biomagnetic signals. Yet, a magnetomyographic investigation of muscular fatigue is still missing. Here, we simultaneously used sEMG (4 surface electrode) and OPM-based magnetomyography (OPM-MMG, 4 sensors) to detect muscle fatigue during a 3 × 1-min isometric contractions of the left rectus femoris muscle in 7 healthy participants. Both signals exhibited the characteristic spectral compression distinctive for muscle fatigue. OPM-MMG and sEMG slope values, used to quantify the spectral compression of the signals, were positively correlated, displaying similarity between the techniques. Additionally, the analysis of the different components of the magnetic field vector enabled speculations regarding the propagation of the muscle action potentials (MAPs). Altogether these results show the feasibility of the magnetomyographic approach with OPMs and propose a potential alternative to sEMG for the study of muscle fatigue.

Electromyographic traces of motor unit synchronization of fatigued lower limb muscles during gait

BACKGROUND

The study of the signal in the frequency domain has shown to be a good tool to identify muscular fatigue. Previous research has shown that the low frequency band and 40 Hz frequency band increase their relative intensity with the onset of fatigue. These findings were obtained in rectus femoris, but the behaviours of other muscles of the lower limb are unknown. In this article we explored the changes in the low frequency and 40 Hz frequency band of lower limb muscles with respect to fatigue.

METHODS

Thirty healthy subjects were recruited to analyse the electromyography (EMG) of biceps femoris, tibialis anterior and gastrocnemius medialis and lateralis of both legs during gait. Four two-minutes walks at a self-selected speed were recorded, the first two walks with a normal muscular function and the last two walks after a fatigue protocol. All the signals were decomposed using wavelet transformations. The signals were normalized in time and spectral intensities normalized to the sum of intensities in the frequency domain. Two frequency bands were studied in each walk: the 40-Hz (34-53 Hz) and the low frequency (< 25 Hz) bands. A ratio of the spectral intensities of those frequency bands at each walk was obtained by dividing the 40-Hz frequency band spectral intensity by the low frequency band spectral intensity. Statistical parametric mapping techniques were used to compare the ratios of the prefatigue walks against the postfatigue walks.

RESULTS

The results of the Statistical Non-Parametric Mapping (SnPM) analysis of all muscles depict a higher relative spectral intensity in the low frequency band in the comparison of fatigue versus prefatigue recordings except for the right gastrocnemius lateralis. The critical thresholds F* were exceeded by multiple suprathreshold clusters with p values <0.05, showing that the low frequency band increased its relative spectral intensity in the case of fatigue.

CONCLUSION

The obtained results suggest that the low frequency band increases its relative spectral intensity in all the studied muscles when fatigue onsets. This increase in relative spectral intensity may be linked to an increase in motor unit synchronization promoted by the central nervous system to ensure good motor control.

Implementation and experimental validation of surface electromyogram and force model of Tibialis Anterior muscle for examining muscular factors

This study reports a surface electromyogram and force of contraction model. The objective was to investigate the effect of changes in the size, type and number of motor units in the Tibialis Anterior muscle to surface electromyogram and force of dorsiflexion. A computational model to simulate surface electromyogram and associated force of contraction by the Tibialis Anterior muscle was developed. This model was simulated for isometric dorsiflexion, and comparative experiments were conducted for validation. Repeated simulations were performed to investigate the different parameters and evaluate inter-experimental variability. An equivalence statistical test and the Bland–Altman method were used to observe the significance between the simulated and experimental data. Simulated and experimentally recorded data had high similarity for the three measures: maximal power of power spectral density ( p < 0.0001), root mean square of surface electromyogram ( p < 0.0001) and force recorded at the footplate ( p < 0.03). Inter-subject variability in the experimental results was in-line with the variability in the repeated simulation results. This experimentally validated computational model for the surface electromyogram and force of the Tibialis Anterior muscle is significant as it allows the examination of three important muscular factors associated with ageing and disease: size, fibre type and number of motor units.

Muscle endurance time estimation during isometric training using electromyogram and supervised learning

Constant-force isometric muscle training is useful for increasing the maximal strength , rehabilitation and work-fatigue assessment. Earlier studies have shown that muscle fatigue characteristics can be used for evaluating muscle endurance limit.

STUDY OBJECTIVE

To predict muscle endurance time during isometric task using frequency spectrum characteristics of surface electromyography signals along with analysis of frequency spectrum shape and scale during fatigue accumulation.

METHOD

Thirteen subjects performed isometric lateral raise at 60% MVC of deltoid (lateral) till endurance limit. Time windowed sEMG frequency spectrum was modelled using 2-parameter distributions namely Gamma and Weibull for spectrum analysis and endurance prediction.

RESULTS

Gamma distribution provided better spectrum fitting (P < 0.001) than Weibull distribution. Spectrum Distribution demonstrated no change in shape but shifted towards lower frequency with increase of magnitude at characteristic mode frequency. Support Vector Regression based algorithm was developed for endurance time estimation using features derived from fitted frequency spectrum. Time taken till endurance limit for acquired dataset 38.53 ± 17.33 s (Mean ± Standard Deviation) was predicted with error of 0.029 ± 4.19 s . R-square: 0.956, training and test sets RMSE was calculated as 3.96 and 4.29 s respectively. The application of the algorithm suggested that model required 70% of sEMG signal from maximum time of endurance for high prediction accuracy.

CONCLUSION

Endurance Limit prediction algorithm was developed for quantification of endurance time for optimizing isometric training and rehabilitation. Our method could help personalize and change conventional training method of same weight and duration for all subjects with optimized training parameters, based upon individual sEMG activity.

A Muscle Fibre Conduction Velocity Tracking ASIC for Local Fatigue Monitoring

Electromyography analysis can provide information about a muscle's fatigue state by estimating Muscle Fibre Conduction Velocity (MFCV), a measure of the travelling speed of Motor Unit Action Potentials (MUAPs) in muscle tissue. MFCV better represents the physical manifestations of muscle fatigue, compared to the progressive compression of the myoelectic Power Spectral Density, hence it is more suitable for a muscle fatigue tracking system. This paper presents a novel algorithm for the estimation of MFCV using single threshold bit-stream conversion and a dedicated application-specified integrated circuit (ASIC) for its implementation, suitable for a compact, wearable and easy to use muscle fatigue monitor. The presented ASIC is implemented in a commercially available AMS 0.35 [Formula: see text] CMOS technology and utilizes a bit-stream cross-correlator that estimates the conduction velocity of the myoelectric signal in real time. A test group of 20 subjects was used to evaluate the performance of the developed ASIC, achieving good accuracy with an error of only 3.2% compared to Matlab.

Logarithmic Power-Frequency: An Alternative Method for Emg-Based Fatigue Assessment

The purpose of this study was to explore different methods of processing EMG signals with a goal of obtaining more sensitive measures of fatigue. Two groups of 28 and 16 participants performed isometric efforts in arm abduction and torso extension until exhaustion respectively at three exertion levels (30, 50 and 70% of maximum). Electromyographic signals were recorded from the middle deltoid muscle and the erector Spinae muscles at the L4/L5 level for the first and the second group, respectively. Three new parameters, peak amplitude frequency, slope of lower frequency, and slope of higher frequency, were derived from logarithmic power versus logarithmic frequency over a 20–200 Hz bandwidth. Changes of these parameters over time were found to be sensitive to fatigue and to different levels of exertion. The first two parameters were more sensitive than median power frequency during arm abductions, but less sensitive than mean power frequency. In torso extensions, the slope of higher frequency gave better performance than the slope of lower frequency. This alternative method appears to have promise for future EMG-based assessments of localized muscle fatigue.

Atrial Conduction Velocity Correlates with Frequency Content of Bipolar Signal

BACKGROUND

Anisotropy in conduction velocity (CV) is a key substrate abnormality influencing atrial arrhythmias. In skeletal muscle fibers, CV and frequency content of the surface electromyogram signal are directly related. We hypothesized that in human atria the frequency content of the bipolar signal, recorded on the endocardial surface, is directly related to the local CV.

METHODS

In 15 patients submitted to ablation of supraventricular arrhythmias, incremental pacing was performed through an octapolar catheter inserted into the coronary sinus (CS), alternatively from both extremities in two different sequences: CS bipole 1-2 as the pacing site and CS bipole 7-8 as the detection site in the first, and vice versa in the second. The pacing cycle length (PCL) was stepwise decreased from 600 ms to 500 ms, 400 ms, 300 ms, until 250 ms. Estimation of the CV was performed as the ratio between the distance traveled by the propagating pulse and the propagation time. The frequency distribution of the signal energy was estimated using the fast Fourier transform, and the characteristic frequency (CF) was estimated as the barycenter of the frequency spectrum.

RESULTS

A total of 2,496 bipolar signals were analyzed; CV and CF were estimated and compared. The single patient and group data analysis showed a significant direct correlation between CV and CF of the local bipolar signal.

CONCLUSIONS

Comparing the degree of spectral compression among signals registered in different points of the endocardial cardiac surface in response to decreasing PCL enables to map local differences in CV, a useful arrhythmogenic substrate index.

Muscle fatigue increases beta-band coherence between the firing times of simultaneously active motor units in the first dorsal interosseous muscle

Synchronization between the firing times of simultaneously active motor units (MUs) is generally assumed to increase during fatiguing contractions. To date, however, estimates of MU synchronization have relied on indirect measures, derived from surface electromyographic (EMG) interference signals. This study used intramuscular coherence to investigate the correlation between MU discharges in the first dorsal interosseous muscle during and immediately following a submaximal fatiguing contraction, and after rest. Coherence between composite MU spike trains, derived from decomposed surface EMG, were examined in the delta (1-4 Hz), alpha (8-12 Hz), beta (15-30 Hz), and gamma (30-60 Hz) frequency band ranges. A significant increase in MU coherence was observed in the delta, alpha, and beta frequency bands postfatigue. In addition, wavelet coherence revealed a tendency for delta-, alpha-, and beta-band coherence to increase during the fatiguing contraction, with subjects exhibiting low initial coherence values displaying the greatest relative increase. This was accompanied by an increase in MU short-term synchronization and a decline in mean firing rate of the majority of MUs detected during the sustained contraction. A model of the motoneuron pool and surface EMG was used to investigate factors influencing the coherence estimate. Simulation results indicated that changes in motoneuron inhibition and firing rates alone could not directly account for increased beta-band coherence postfatigue. The observed increase is, therefore, more likely to arise from an increase in the strength of correlated inputs to MUs as the muscle fatigues.

Effect of number of motor units and muscle fibre type on surface electromyogram

Reduction in number of motor units (nMU) and fast fibre ratio (FFR) is associated with disease or atrophy when this is rapid. There is a need to study the effect of nMU and FFR to analyse the association with ageing and disease. This study has developed a mathematical model to investigate the relationship between nMU and FFR on surface electromyogram (sEMG) of the biceps muscles. The model has been validated by comparing the simulation outcomes with experiments comparing the sEMG of physically active younger and older cohort. The results show that there is statistically significant difference between the two groups, and the simulation studies closely model the experimental results. This model can be applied to identify the cause of muscle weakness among the elderly due to factors such as muscle dystrophy or preferential loss of type F muscle fibres.

Verification of the muscle fatigue detection capability of a unipolar-leads system using a surface electromyogram model

In this study, the muscle fatigue detection capability of bipolar and unipolar lead systems used for surface electromyogram measurement was verified by simulation. The constructed model simplified the isometric contraction of the biceps brachii. There were two simulation experiments: 1) the addition and deletion of white noise and 2) the addition and deletion of hum noise. The pattern result of simulation 1) suggested the possibility that the muscle fatigue detection capability of a unipolar-leads system was high. The pattern 2) result showed the unipolar-leads system had a small influence of filtering, and suggested that the mixing of hum noise could be disregarded.

A subject-independent method for automatically grading electromyographic features during a fatiguing contraction

Many studies have attempted to monitor fatigue from electromyogram (EMG) signals. However, fatigue affects EMG in a subject-specific manner. We present here a subject-independent framework for monitoring the changes in EMG features that accompany muscle fatigue based on principal component analysis and factor analysis. The proposed framework is based on several time- and frequency-domain features, unlike most of the existing work, which is based on two to three features. Results show that latent factors obtained from factor analysis on these features provide a robust and unified framework. This framework learns a model from EMG signals of multiple subjects, that form a reference group, and monitors the changes in EMG features during a sustained submaximal contraction on a test subject on a scale from zero to one. The framework was tested on EMG signals collected from 12 muscles of eight healthy subjects. The distribution of factor scores of the test subject, when mapped onto the framework was similar for both the subject-specific and subject-independent cases.

An alternative approach in muscle fatigue evaluation from the surface EMG signal

The aim of this study was to compare the intervals of time between adjacent zero crossings (ZCI), an alternative frequency-temporal parameter, with the root-mean-square (RMS) value and the median frequency (F(med)) from the surface EMG (sEMG) signal in muscle fatigue analysis. Twenty right-handed volunteers performed isometric contractions of right biceps brachii muscle while sEMG signals were collected from it at three different and arbitrary load levels until fatigue. The mean ZCI presented a significant correlation with F(med) but not with RMS value and it also presented lower coefficients of variation than others. The results pointed that mean ZCI properties can contribute more than F(med) and RMS value on the interpretation of the muscle function under fatigue conditions.

A sEMG model with experimentally based simulation parameters

A differential, time-invariant, surface electromyogram (sEMG) model has been implemented. While it is based on existing EMG models, the novelty of this implementation is that it assigns more accurate distributions of variables to create realistic motor unit (MU) characteristics. Variables such as muscle fibre conduction velocity, jitter (the change in the interpulse interval between subsequent action potential firings) and motor unit size have been considered to follow normal distributions about an experimentally obtained mean. In addition, motor unit firing frequencies have been considered to have non-linear and type based distributions that are in accordance with experimental results. Motor unit recruitment thresholds have been considered to be related to the MU type. The model has been used to simulate single channel differential sEMG signals from voluntary, isometric contractions of the biceps brachii muscle. The model has been experimentally verified by conducting experiments on three subjects. Comparison between simulated signals and experimental recordings shows that the Root Mean Square (RMS) increases linearly with force in both cases. The simulated signals also show similar values and rates of change of RMS to the experimental signals.

Towards a genioglossus surface EMG model of obstructive sleep apnea

The behaviour and activity of the genioglossus muscle during sleep is of considerable interest to investigators of obstructive sleep apnea syndrome. Therefore, we contribute an model of genioglossus EMG activity during breathing, based on recent physiological findings. We present the modelling techniques and simulation results. The model incorporates new data on fibre type, motor unit type and motor unit firing characteristics. Although we report its use for modelling genioglossus surface EMG, this model can be used to simulate both genioglossus surface and intramuscular EMGs of various electrode configurations. We also discuss the simulation results in the context of the limited experimental data available for surface genioglossus EMG in obstructive sleep apnea.

Surface EMG based muscle fatigue evaluation in biomechanics

In the last three decades it has become quite common to evaluate local muscle fatigue by means of surface electromyographic (sEMG) signal processing. A large number of studies have been performed yielding signal-based quantitative criteria of fatigue in primarily static but also in dynamic tasks. The non-invasive nature of this approach has been particularly appealing in areas like ergonomics and occupational biomechanics, to name just the most prominent ones. However, a correct appreciation of the findings concerned can only be obtained by judging both the scientific value and practical utility of methods while appreciating the corresponding advantages and limitations. The aim of this paper is to serve as a state of the art summary of this issue. The paper gives an overview of classical and modern signal processing methods and techniques from the standpoint of applicability to sEMG signals in fatigue-inducing situations relevant to the broad field of biomechanics. Time domain, frequency domain, time-frequency and time-scale representations, and other methods such as fractal analysis and recurrence quantification analysis are described succinctly and are illustrated with their biomechanical applications, research or clinical alike. Examples from the authors' own work are incorporated where appropriate. The future of this methodology is projected by estimating those methods that have the greatest chance to be routinely used as reliable muscle fatigue measures.

Pain-induced changes in cervical muscle activation do not affect muscle fatigability during sustained isometric contraction

This study investigated whether pain-induced changes in cervical muscle activation affect myoelectric manifestations of cervical muscle fatigue. Surface EMG signals were detected from the sternocleidomastoid and splenius capitis muscles bilaterally from 14 healthy subjects during 20-s cervical flexion contractions at 25% of the maximal force. Measurements were performed before and after the injection of 0.5 ml of hypertonic (painful) or isotonic (control) saline into either the sternocleidomastoid or splenius capitis in two experimental sessions. EMG average rectified value and mean power spectral frequency were estimated throughout the sustained contraction. Sternocleidomastoid or splenius capitis muscle pain resulted in lower sternocleidomastoid EMG average rectified value on the side of pain (P < 0.01). However, changes over time of sternocleidomastoid EMG average rectified value and mean frequency (myoelectric manifestations of fatigue) during sustained flexion were not changed during muscle pain. These results demonstrate that pain-induced modifications of cervical muscle activity do not change myoelectric manifestations of fatigue. This finding has implications for interpreting the mechanisms underlying greater cervical muscle fatigue in people with neck pain disorders.

Acoustic correlates of fatigue in laryngeal muscles: findings for a criterion-based prevention of acquired voice pathologies

PURPOSE

The objective was to identify acoustic correlates of laryngeal muscle fatigue in conditions of vocal effort.

METHOD

In a previous study, a technique of electromyography (EMG) served to define physiological signs of "voice fatigue" in laryngeal muscles involved in voicing. These signs correspond to spectral changes in contraction potentials. A corpus of vocalizations from the 7 participants in the EMG study was used to explore the effects of muscle fatigue on voice acoustics. Each participant produced vocalizations at regular intervals (50 in all) extending across a day (12-14 hr). The participants also produced 5 min of loud speech with peaks of 74 dBA at 1 m between each vocalization. Twenty acoustic parameters were measured using the Multi-Dimensional Voice Program (Kay Elemetrics, Lincoln Park, NJ).

RESULTS

The analyses showed no consistent correlations between acoustic parameters and estimates of muscle fatigue. However, in all cases, nonlinear jumps occurred in the frequency of amplitude tremor at points where fatigue estimates showed a critical shift. These jumps were robust despite changes in F0 in some individuals.

CONCLUSION

A brief rise in voice tremor can correspond to a critical change in laryngeal muscle tissues seen as a condition where continued vocal effort can increase the risk of lesions or other conditions affecting voice.

Fatigue of the plantar intrinsic foot muscles increases navicular drop

Our purpose was to assess the effect of foot intrinsic muscle fatigue on pronation, as assessed with navicular drop, during static stance. Twenty-one healthy young adults participated. Navicular drop was measured before and after fatiguing exercise of the plantar foot intrinsic muscles. Surface electromyography of the abductor hallucis muscle was recorded during maximum voluntary isometric contractions (MVIC) in order to find the baseline median frequency (MedF). Subjects then performed sets of 75 repetitions of isotonic flexion contractions of the intrinsic foot muscles against a 4.55 kg weight on a custom pulley system. After each set an MVIC was performed to track shifts in MedF. After a MedF shift of at least 10%, navicular drop measurements were repeated. Subjects exhibited 10.0+/-3.8mm of navicular drop at baseline and 11.8+/-3.8mm after fatigue (p<0.0005). The change in navicular drop was significantly correlated with change in MedF (r=.47, p=.03). The intrinsic foot muscles play a role in support of the medial longitudinal arch in static stance. Disrupting the function of these muscles through fatigue resulted in an increase in pronation as assessed by navicular drop.

Simulation analysis of interference EMG during fatiguing voluntary contractions. Part I: What do the intramuscular spike amplitude–frequency histograms reflect?

Decline in amplitude of EMG signals and in the rate of counts of intramuscularly recorded spikes during fatigue is often attributed to a progressive reduction of the neural drive only. As a rule, alterations in intracellular action potential (IAP) are not taken into account. To test correctness of the hypothesis, the effect of various discharge frequency patterns as well as changes in IAP shape and muscle fibre propagation velocity (MFPV) on the spike amplitude-frequency histogram of intramuscular interference EMG signals were simulated and analyzed. It was assumed that muscle was composed of four types of motor units (MUs): slow-twitch fatigue resistant, fast-twitch fatigue resistant, fast intermediate, and fast fatigable. MFPV and IAP duration at initial stage before fatigue as well as their changes differed for individual MU types. Fatigability of individual MU types in normal conditions as well as in the case of ischaemic or low oxygen conditions due to restricted blood flow was also taken into account. It was found that spike amplitude-frequency histogram is poorly sensitive to MU firing frequency, while it is highly sensitive to IAP profile lengthening. It is concluded that spike amplitude-frequency analysis can hardly provide a correct measure of MU rate-coding pattern during fatigue.

Improved surface EMG electrode for measuring genioglossus muscle activity

Activation of the genioglossus (GG) muscles is necessary to maintain the patency of the upper airway. In the condition of obstructive sleep apnea (OSA) this mechanism fails and the possible role of fatigue in its pathogenesis is still not fully understood. In this paper, a new electrode design for recording the genioglossus surface electromyogram (sEMG) is presented. The new design differs from a widely used GG surface electrode in both electrode configuration (unilateral rather than bilateral) and electrode material (Ag-AgCl rather than stainless steel (SS)). The separate effects of these factors were evaluated during force-varying and fatiguing contractions on normal human subjects and using GG sEMG model simulations. Unilateral sEMG was found to have lower amplitude, lower frequency content and a different rate of change of median frequency during fatiguing contractions. It was shown to overcome several disadvantages posed by the bilateral configuration and be more selective. Ag-AgCl has more favorable impedance characteristics and resulted in greater signal amplitudes. It was concluded that the new design is more suitable for detecting GG sEMG and allows more reliable interpretation of changes in sEMG due to physiological mechanisms, thus providing a new methodology for studying GG function and the role of fatigue in OSA.

Differences in the activity of the muscles in the forearm of individuals with a congenital absence of the hand

The spectral content of the myoelectric signals from the muscles of the remnant forearms of three persons with congenital absences (CA) of their forearms was compared with signals from their intact contra-lateral limbs, similar muscles in three persons with acquired losses (AL) and seven persons without absences [no loss (NL)]. The observed bandwidth for the CA subjects was broader with peak energy between 200 and 300 Hz. While the signals from the contra-lateral limbs and the AL and NL subjects was in the 100-150 Hz range. The mean skew of the signals from the AL subjects was 46.3 +/- 6.7 and those with NL of 45.4 +/- 8.7, while the signals from those with CAs had a skew of 11.0 +/- 11. The structure of the muscles of one CA subject was observed ultrasonically. The muscle showed greater disruption than normally developed muscles. It is speculated that the myographic signal reflects the structure of the muscle which has developed in a more disorganized manner as a result of the muscle not being stretched by other muscles across the missing distal joint, even in the muscles that are used regularly to control arm prostheses.

Simulation of intramuscular EMG signals detected using implantable myoelectric sensors (IMES)

The purpose of this study was to test the feasibility of recording independent electromyographic (EMG) signals from the forearm using implantable myoelectric sensors (IMES), for myoelectric prosthetic control. Action potentials were simulated using two different volume conductor models: a finite-element (FE) model that was used to explore the influence of the electrical properties of the surrounding inhomogeneous tissues and an analytical infinite volume conductor model that was used to estimate the approximate detection volume of the implanted sensors. Action potential amplitude increased progressively as conducting electrodes, the ceramic electrode casing and high resistivity encapsulation tissue were added to the model. For the muscle fiber locations examined, the mean increase in EMG root mean square amplitude when the full range of material properties was included in the model was 18.2% (+/-8.1%). Changing the orientation of the electrode with respect to the fiber direction altered the shape of the electrode detection volume and reduced the electrode selectivity. The estimated detection radius of the IMES electrode, assuming a cylindrical muscle cross section, was 4.8, 6.2, and 7.5 mm for electrode orientations of 0 degree, 22.5 degrees, and 45 degrees with respect to the muscle fiber direction.

Utility of traditional and alternative EMG-based measures of fatigue during low-moderate level isometric efforts

Traditional electromyographic (EMG) measures (e.g., amplitude, mean and median frequencies of the power spectra) have demonstrated inconsistent abilities in monitoring localized muscle fatigue at relatively low effort levels. In the present study, several alternative EMG-based fatigue indices were evaluated, derived using a logarithmic representation of the power spectrum, the fractal dimension of the raw signal, and a Poisson distribution fit to the power spectrum. These methods, along with traditional approaches, were applied to EMG data obtained from three separate experiments. In the first two experiments, 24 participants performed sustained isometric shoulder abductions and torso extensions at 30% of maximum voluntary strength (MVC). In the third experiment, another group of 12 participants performed similar shoulder exercises at 15% and 30% MVC, with repeatability assessed at 15% MVC. Both traditional and alternative EMG measures were analyzed for their 'utility', in terms of sensitivity to fatigue, variability, repeatability, and predictive ability. Results demonstrated that parameters derived from fractal analysis and the Poisson distribution demonstrated high utility. These alternative approaches appear promising as fatigue indices for low level isometric tasks.

Simulation analysis of interference EMG during fatiguing voluntary contractions. Part II--changes in amplitude and spectral characteristics

Capabilities of amplitude and spectral methods for information extraction from interference EMG signals were assessed through simulation and preliminary experiment. Muscle was composed of 4 types of motor units (MUs). Different hypotheses on changes in firing frequency of individual MUs, intracellular action potential (IAP) and muscle fibre propagation velocity (MFPV) during fatigue were analyzed. It was found that changes in amplitude characteristics of interference signals (root mean square, RMS, or integrated rectified value, IEMG) detected by intramuscular and surface electrodes differed. RMS and IEMG of surface detected interference signals could increase even under MU firing rate reduction and without MU synchronisation. IAP profile lengthening can affect amplitude characteristics more significantly than MU firing frequency. Thus, an increase of interference EMG amplitude is unreliable to reflect changes in the neural drive. The ratio between EMG amplitude and contraction response can hardly characterise the so-called 'neuromuscular efficiency'. The recently proposed spectral fatigue indices can be used for quantification of interference EMG signals. The indices are practically insensitive to MU firing frequency. IAP profile lengthening and decrease in MFPV enhanced the index value, while recruitment of fast fatigable MUs reduced it. Sensitivity of the indices was higher than that of indices traditionally used.

Is fatigue all in your head? A critical review of the central governor model

The central governor model has recently been proposed as a general model to explain the phenomenon of fatigue. It proposes that the subconscious brain regulates power output (pacing strategy) by modulating motor unit recruitment to preserve whole body homoeostasis and prevent catastrophic physiological failure such as rigor. In this model, the word fatigue is redefined from a term that describes an exercise decline in the ability to produce force and power to one of sensation or emotion. The underpinnings of the central governor model are the refutation of what is described variously as peripheral fatigue, limitations models, and the cardiovascular/anaerobic/catastrophe model. This argument centres on the inability of lactic acid models of fatigue to adequately explain fatigue. In this review, it is argued that a variety of peripheral factors other than lactic acid are known to compromise muscle force and power and that these effects may protect against "catastrophe". Further, it is shown that a variety of studies indicate that fatigue induced decreases in performance cannot be adequately explained by the central governor model. Instead, it is suggested that the concept of task dependency, in which the mechanisms of fatigue vary depending on the specific exercise stressor, is a more comprehensive and defensible model of fatigue. This model includes aspects of both central and peripheral contributions to fatigue, and the relative importance of each probably varies with the type of exercise.

Physiologic features of vocal fatigue: electromyographic spectral-compression in laryngeal muscles

OBJECTIVES

This study addresses the problem of defining observable attributes of "vocal fatigue" as a physiologic condition. The aim was to determine the applicability of electromyography (EMG) spectral compression in observing fatigue in laryngeal muscles arising from prolonged vocal effort.

STUDY DESIGN

Single institution, nonrandomized, prospective analysis of subjects evaluated in an academic, tertiary care center.

METHODS

In adapting EMG techniques, we report pretest observations that bear on the choice of voicing tasks serving to induce and estimate muscle fatigue and the selection of muscles that are particularly involved in effortful vocalization. On this basis, an experiment was designed where intramuscular EMG was used to record lateral cricoarytenoid potentials of seven subjects at regular intervals across a 12 to 14 hour period (50 samples per subject). Between each of these samples, the participants were required to produce loud speech for 3 minutes with peaks of 74 dBA at 1 meter.

RESULTS

The results show fatigue-related spectral compression for all subjects and nonlinear changes across time indicating critical values beyond which fatigue is persistent.

CONCLUSION

Spectral compression appears to present a robust attribute of fatigue-related changes in muscles involved in vocalization. There are several implications with respect to research on the prevention of acquired voice pathologies.

Effect of muscle fatigue on internal model formation and retention during reaching with the arm

The motor system adapts to novel dynamic environments by forming internal models that predict the muscle forces needed to move skillfully. The goal of this study was to determine how muscle fatigue affects internal model formation during arm movement and whether an internal model acquired while fatigued could be recalled accurately after rest. Twelve subjects adapted to a viscous force field applied by a lightweight robot as they reached to a target. They then reached while being resisted by elastic bands until they could no longer touch the target. This protocol reduced the strength of the muscles used to resist the force field by ∼20%. The bands were removed, and subjects adapted again to the viscous force field. Their adaptive ability, quantified by the amount and time constant of adaptation, was not significantly impaired following fatigue. The subjects then rested, recovering ∼70% of their lost force-generation ability. When they reached in the force field again, their prediction of the force field strength was different than in a nonfatigued state. This alteration was consistent with the use of a higher level of effort than normally used to counteract the force field. These results suggest that recovery from fatigue can affect recall of an internal model, even when the fatigue did not substantially affect the motor system’s ability to form the model. Recovery from fatigue apparently affects recall because the motor system represents internal models as a mapping between effort and movement and relies on practice to recalibrate this mapping.

The use of correlation integrals in the study of localized muscle fatigue of elbow flexors during maximal efforts

Innovative applications of non-linear time series analysis have recently been used to investigate physiological phenomena. In this study, we investigated the feasibility of using the correlation integral to monitor the localized muscle fatigue process in the biceps brachii during sustained maximal efforts. The subjects performed isometric maximum contractions until failure in elbow flexion (90 degrees from neutral). The median and the 70th percentile frequency of the Surface electromyography (SEMG) power spectrum, the integrated SEMG, and the Correlation Integral (CI) were evaluated during the trials. The linear correlation between these variables and the elbow torque production was used to quantify the ability of a parameter to follow the fatiguing process. The CI had the highest linear correlation with torque (0.77 (0.12SD)), while the spectral indices correlations with torque were much lower. The decreasing trend of the torque production was followed by the spectral indices for only the beginning part of the contraction, while the CI increased sharply after the torque production fell to about 0.60 of the MVC. This suggests that the CI is sensitive to different changes of the SEMG signal during fatigue than the spectral variables.

Intracellular action potential generation and extinction strongly affect the sensitivity of M-wave characteristic frequencies to changes in the peripheral parameters with muscle fatigue

Changes in muscle fibre propagation velocity (MFPV) and shape of intracellular action potentials (IAPs) accompany peripheral muscle fatigue. We have shown through mathematical simulations that the effects of IAP generation and extinction reduced the sensitivity of the mean (fmean) and median (fmed) frequency of M-wave power spectra to individual changes in MFPV. Due to the differences in weighting of the spectral components used for calculation of the characteristic frequencies, the highest spectral components of the M-wave affected the fmean more than the fmed. These components are related to the M-wave leading edge that reflects the IAP depolarization phase. They reduced the sensitivity of the spectral moment of order 1 to individual changes in MFPV and increased its sensitivity to IAP changes. Since the changes of the IAP depolarization phase during the final stages of peripheral muscle fatigue affected the fmean more, the range of the relative reductions of the fmean and fmed were approximately the same under combined changes in IAP and MFPV. The sensitivities of M-wave characteristic frequencies depended also on the electrode arrangement and position as well as on the length of active muscle fibres.

A Technique to Track Individual Motor Unit Action Potentials in Surface EMG by Monitoring Their Conduction Velocities and Amplitudes

The speed of propagation of an action potential along a muscle fiber, its conduction velocity (CV), can be used as an indication of the physiological or pathological state of the muscle fiber membrane. The motor unit action potential (MUAP), the waveform resulting from the spatial and temporal summation of the individual muscle fiber action potentials of that motor unit (MU), propagates with a speed referred to as the motor unit conduction velocity (MUCV). This paper introduces a new algorithm, the MU tracking algorithm, which estimates MUCVs and MUAP amplitudes for individual MUs in a localized MU population using SEMG signals. By tracking these values across time, the electrical activity of the localized MU pool can be monitored. An assessment of the performance of the algorithm has been achieved using simulated SEMG signals. It is concluded that this analysis technique enhances the suitability of SEMG for clinical applications and points toward a future of noninvasive diagnosis and assessment of neuromuscular disorders.

Volume Conduction in an Anatomically Based Surface EMG Model

A finite-element model to simulate surface electromyography (EMG) in a realistic human upper arm is presented. The model is used to explore the effect of limb geometry on surface-detected muscle fiber action potentials. The model was based on magnetic resonance images of the subject's upper arm and includes both resistive and capacitive material properties. To validate the model geometry, experimental and simulated potentials were compared at different electrode sites during the application of a subthreshold sinusoidal current source to the skin surface. Of the material properties examined, the closest approximation to the experimental data yielded a mean root-mean-square (rms) error of the normalized surface potential of 18% or 27%, depending on the site of the applied source. Surface-detected action potentials simulated using the realistic volume conductor model and an idealized cylindrical model based on the same limb geometry were then compared. Variation in the simulated limb geometry had a considerable effect on action potential shape. However, the rate of decay of the action potential amplitude with increasing distance from the fiber was similar in both models. Inclusion of capacitive material properties resulted in temporal low-pass filtering of the surface action potentials. This effect was most pronounced in the end-effect components of action potentials detected at locations far from the active fiber. It is concluded that accurate modeling of the limb geometry, asymmetry, tissue capacitance and fiber curvature is important when the specific action potential shapes are of interest. However, if the objective is to examine more qualitative features of the surface EMG signal, then an idealized volume conductor model with appropriate tissue thicknesses provides a close approximation.

The effects of bipolar electrode montage on conduction velocity estimation from the surface electromyogram

This study examines the influence of the bipolar electrode montage on conduction velocity (CV) estimation. Electrode montage refers to the combination of two parameters, the inter-electrode distance (IED), the distance between the two electrodes of a bipolar pair, and the inter-signal distance (ISD), the distance between two bipolar signals used to calculate CV. Data from the biceps brachii (BB) and tibialis anterior (TA) of healthy subjects are analysed. Two approaches are used for CV estimation. The first returns a single value per epoch. The second is based on finding velocity values from individual peaks in the signal and results in a peak velocity (PV) distribution being generated per epoch. It is concluded that CV estimation is significantly dependent on the choice of the (IED, ISD) electrode montage. The main results are that the electrode montage affects (1) the mean PV and CV estimates, (typically P < 0.001), (2) the degree of spatial variability, and (3) the width of the PV distributions. The combination of a small IED and large an ISD is recommended.

Surface electromyogram signal modelling

The paper reviews the fundamental components of stochastic and motor-unit-based models of the surface electromyogram (SEMG). Stochastic models used in ergonomics and kinesiology consider the SEMG to be a stochastic process whose amplitude is related to the level of muscle activation and whose power spectral density reflects muscle conduction velocity. Motor-unit-based models for describing the spatio-temporal distribution of individual motor-unit action potentials throughout the limb are quite robust, making it possible to extract precise information about motor-unit architecture from SEMG signals recorded by multi-electrode arrays. Motor-unit-based models have not yet been proven as successful, however, for extracting information about recruitment and firing rates throughout the full range of contraction. The relationship between SEMG and force during natural dynamic movements is much too complex to model in terms of single motor units.

Muscle fiber conduction velocity estimation by using normalized peak-averaging technique

In order to compute the muscle fiber conduction velocity (MFCV) and to clarify how action potentials are conducted, the normalized peak-averaging technique (NPAT) was newly employed together with computer softwares. Twelve pairs of surface electromyograms were selected from biceps brachii muscles during contraction at a level of 50% of the maximum voluntary isometric contraction in seven healthy volunteers. The techniques to compute MFCV from the time delay of the peaks (P-NPAT) and from the cross correlation (CC-NPAT) of averaged pulses were compared to the cross-correlation technique (CCT). The spread rate of averaged pulses was computed to estimate the spread of MFCVs in different motor units. Tri-phasic averaged pulses were obtained clearly by averaging more than 500 detected pulses. The P-NPAT and CC-NPAT highly correlated with the CCT in the computed MFCVs. The MFCVs obtained by P-NPAT were generally larger than those obtained by CCT, and the spread rates had in the definite values. These results suggest that the MFCV could be computed and the spread of MFCVs would be estimated from averaged pulses. The MFCV of a patient with myotonic dystrophy was also studied, and it was suggested that the NPAT would be clinically useful.

Simulation analysis of the ability to estimate motor unit propagation velocity non-invasively by different two-channel methods and types of multi-electrodes

Ability to estimate motor unit propagation velocity correctly using different two-channel methods for delay estimation and different non-invasive spatial filters was analysed by simulation. It was established that longitudinal double difference electrodes could be not a better choice than simple bipolar parallel electrodes. Spatial filtration with a new multi-electrode (performing difference between signals detected by two transversal double difference electrodes positioned along the muscle fibres) promises to give the best estimate. Delay estimation between reference points is more preferable than that based on the cross-correlation technique, which is considerably sensitive to the fundamental properties of the muscle fibre extracellular fields. Preliminary averaging and approximation of the appropriate parts of the signals around chosen reference points could reduce the larger noise sensitivity and the effects of local tissue inhomogeneities as well as eliminate the sampling problem. A correct estimate of the propagation velocity could be impossible, even in the case of not very deep motor units (15 or 10 mm, depending on the spatial filter used) with relatively long (about 120 mm) muscle fibres. In the case of fibres with asymmetrical location of the end-plates in respect to the fibre ends, the propagation velocity estimates could be additionally biased above the longer semilength of the motor unit fibres.

Analysis and simulation of changes in EMG amplitude during high-level fatiguing contractions

Changes in surface electromyographic (EMG) amplitude during sustained, fatiguing contractions are commonly attributed to variations in muscle fiber conduction velocity (MFCV), motor unit firing rates, transmembrane action potentials and the synchronization or recruitment of motor units. However, the relative contribution of each factor remains unclear. Analytical relationships relating changes in MFCV and mean motor unit firing rates to the root mean square (RMS) and average rectified (AR) value of the surface EMG signal are derived. The relationships are then confirmed using model simulation. The simulations and analysis illustrate the different behaviors of the surface EMG RMS and AR value with changing MFCV and firing rate, as the level of motor unit superposition varies. Levels of firing rate modulation and short-term synchronization that, combined with variations in MFCV, could cause changes in EMG amplitude similar to those observed during sustained isometric contraction of the brachioradialis at 80% of maximum voluntary contraction were estimated. While it is not possible to draw conclusions about changes in neural control without further information about the underlying motor unit activation patterns, the examples presented illustrate how a combined analytical and simulation approach may provide insight into the manner in which different factors affect EMG amplitude during sustained isometric contractions.

Rectification and non-linear pre-processing of EMG signals for cortico-muscular analysis

Rectification of the electromyographic (EMG) signal is a commonly used pre-processing procedure that allows detection of significant coherence between EMG and measured cortical signals. However, despite its accepted and wide-spread use, no detailed analysis has been presented to offer insight into the precise function of rectification. We begin this paper with arguments based on single motor unit action potential (AP) trains to demonstrate that rectification effectively enhances the firing rate information of the signal. Enhancement is achieved by shifting the peak of the AP spectrum toward the lower firing rate frequencies, whilst maintaining the firing rate spectra. A similar result is obtained using the analytic envelope of the signal extracted using the Hilbert transform. This argument is extended to simulated EMG signals generated using a published EMG model. Detection of firing rate frequencies is obtained using phase randomised surrogate data, where the original EMG power spectrum exceeds the averaged rectified surrogate spectra at integer multiples of firing rate frequencies. Model simulations demonstrate that this technique accurately determines grouped firing rate frequencies. Extraction of grouped firing rate frequencies prior to coherency analyses may further aid interpretation of significant cortico-muscular coherence findings.

Agonist-antagonist common drive during fatiguing knee extension efforts using surface electromyography

AIM

This study examined the electromyographic (EMG) activity of knee extensor agonists and a knee extensor antagonist muscle during fatiguing isometric extensions across a range of force levels.

METHODS

Five female subjects performed isometric knee extensions at 25%, 50%, 75% and 100% of their maximal voluntary contraction (MVC) with the knee flexed to 75 degrees. Surface EMG (SEMG) was recorded with bipolar electrodes from the vastus lateralis (VL), vastus medialis (VM), rectus femoris (RF) and biceps femoris (BF) and the root-mean-squared (RMS) amplitude and the percentage frequency compression of these recordings were calculated. Commonality and cross talk between recordings were also examined.

RESULTS

Cross talk between recordings was deemed negligible despite significant levels of commonality between the agonist and antagonist SEMG, which was attributed to common drive. SEMG RMS amplitude increased significantly for all muscles during the 25%, 50%, 75% MVC knee extensions until task failure, and decreased significantly for 100% MVC. The frequency spectrum of the SEMG compressed significantly for all muscles and % MVC levels. The VM, VL and BF SEMG recordings responded similarly to fatigue. The RF's frequency spectrum compressed to a significantly higher degree.

CONCLUSIONS

The VM, VL, RF, and BF fatigue in parallel, with high similarity between VM, VL and BF, giving support to the concept of a shared agonist-antagonist motoneuron pool.