An EMG fractal indicator having different sensitivities to changes in force and muscle fatigue during voluntary static muscle contractions.

During a sustained contraction, electromyographic signals (EMGs) undergo a spectral compression. This fatigue behaviour induces a shift of the mean and the median frequencies to lower frequencies. On the other hand, several studies conclude that the mean/median frequency can increase, decrease or remain constant with an increasing force level. Such inconsistency is embarrassing since the fatigue state may be influenced by the force level. In this paper, we propose a frequency indicator which is sensitive to the force level independently of the fatigue state evaluated at 70% of the maximal voluntary contraction. Ten healthy volunteers participated in the study and both surface EMGs (from the short head of the biceps brachii) and force signals were measured. This study compared force and fatigue effects on the EMGs during short (3-s) isometric contractions at different strength intensities and during a sustained isometric contraction until exhaustion. The EMGs partly show 1/falpha spectral behaviours since their power spectral densities may experimentally fit with two linear segments in a log-log representation. The measured "right" slope produces variations of force as 20 times the variations of fatigue. 1/falpha Behaviour may be related to stochastic fractals. This fractal indicator is a new frequency indicator that is thus complementary to other known classical frequency indicators when studying force during unknown fatigue states.     

Validation of the wavelet spectral estimation technique in biceps brachii and brachioradialis fatigue assessment during prolonged low-level static and dynamic contractions.

An experiment was carried out to investigate the myoelectrical manifestations of fatigue of the Biceps Brachii and Brachioradialis muscles in low-level (15% MVC) prolonged isometric and dynamic contractions. The range of the joint angle was 70-110 degrees and the mean speed of flexion and extension was about 33.33 degrees /s (1.2 s for 40 degrees ). The use of Wavelet transform (IMNF) in weakly stationary dynamic SEMG signals was validated in comparison with the Fourier transform (MPF). The development of fatigue and its myoelectrical manifestations (increase in RMS and decrease in mean frequency) in dynamic contractions show no deviations from what is found in literature for both spectral estimation techniques. The benefit of Wavelets is its future use in non-stationary conditions. Lower IMNF slopes in dynamic compared to isometric contractions for Biceps Brachii might be an indication that wavelets reflect more the changes in muscle fiber propagation velocity. The results of the use of Wavelet transform in detecting frequency modulations in different movement phases of the dynamic tests show that in the eccentric phase a systematic shift towards lower frequencies occurs. It also reveals the great possibilities of phase separation using Wavelets with high resolution and low interaction.     

An estimation of the influence of force decrease on the mean power spectral frequency shift of the EMG during repetitive maximum dynamic knee extensions.

Frequency analysis of myoelectric (ME) signals, using the mean power spectral frequency (MNF), has been widely used to characterize peripheral muscle fatigue during isometric contractions assuming constant force. However, during repetitive isokinetic contractions performed with maximum effort, output (force or torque) will decrease markedly during the initial 40-60 contractions, followed by a phase with little or no change. MNF shows a similar pattern. In situations where there exist a significant relationship between MNF and output, part of the decrease in MNF may per se be related to the decrease in force during dynamic contractions. This study estimated force effects on the MNF shifts during repetitive dynamic knee extensions. Twenty healthy volunteers participated in the study and both surface ME signals (from the right vastus lateralis, vastus medialis, and rectus femoris muscles) and the biomechanical signals (force, position, and velocity) of an isokinetic dynamometer were measured. Two tests were performed: (i) 100 repetitive maximum isokinetic contractions of the right knee extensors, and (ii) five gradually increasing static knee extensions before and after (i). The corresponding ME signal time-frequency representations were calculated using the continuous wavelet transform. Compensation of the MNF variables of the repetitive contractions was performed with respect to the individual MNF-force relation based on an average of five gradually increasing contractions. Whether or not compensation was necessary was based on the shape of the MNF-force relationship. A significant compensation of the MNF was found for the repetitive isokinetic contractions. In conclusion, when investigating maximum dynamic contractions, decreases in MNF can be due to mechanisms similar to those found during sustained static contractions (force-independent component of fatigue) and in some subjects due to a direct effect of the change in force (force-dependent component of fatigue). In order to compare MNF shifts during sustained static and repetitive dynamic contractions it is necessary to estimate the force-dependent component of fatigue of dynamic contractions. Our results are preliminary and have to be confirmed in larger experiments using single dynamic contractions when determining the MNF-force relationship of the unfatigued situation.     

Time and frequency domain responses of the mechanomyogram and electromyogram during isometric ramp contractions: a comparison of the short-time Fourier and continuous wavelet transforms.

The purposes of this study were to examine the mechanomyographic (MMG) and electromyographic (EMG) time and frequency domain responses of the vastus lateralis (VL) and rectus femoris (RF) muscles during isometric ramp contractions and compare the time-frequency of the MMG and EMG signals generated by the short-time Fourier transform (STFT) and continuous wavelet transform (CWT). Nineteen healthy subjects (mean+/-SD age=24+/-4 years) performed two isometric maximal voluntary contractions (MVCs) before and after completing 2-3, 6-s isometric ramp contractions from 5% to 100% MVC with the right leg extensors. MMG and surface EMG signals were recorded from the VL and RF muscles. Time domains were represented as root mean squared amplitude values, and time-frequency representations were generated using the STFT and CWT. Polynomial regression analyses indicated cubic increases in MMG amplitude, MMG frequency, and EMG frequency, whereas EMG amplitude increased quadratically. From 5% to 24-28% MVC, MMG amplitude remained stable while MMG frequency increased. From 24-28% to 76-78% MVC, MMG amplitude increased rapidly while MMG frequency plateaued. From 76-78% to 100% MVC, MMG amplitude plateaued (VL) or decreased (RF) while MMG frequency increased. EMG amplitude increased while EMG frequency changed only marginally across the force spectrum with no clear deflection points. Overall, these findings suggested that MMG may offer more unique information regarding the interactions between motor unit recruitment and firing rate that control muscle force production during ramp contractions than traditional surface EMG. In addition, although the STFT frequency patterns were more pronounced than the CWT, both algorithms produced similar time-frequency representations for tracking changes in MMG or EMG frequency.     

Time/frequency events of surface mechanomyographic signals resolved by nonlinearly scaled wavelets

The purpose of this investigation is to introduce a wavelet analysis designed for analyzing short events reflecting bursts of muscle activity in non-stationary mechanomyographic (MMG) signals. A filter bank of eleven nonlinearly scaled wavelets that maintain the optimal combination of time and frequency resolution across the frequency range of MMG signals (5–100 Hz) was used for the analysis. A comparison with the short-time Fourier transform, Wigner-Ville transform and continuous wavelet transform using a test signal with known time–frequency characteristics showed that the MMG wavelet analysis resolved the intensity, timing, and frequencies of events in a more distinct way without overemphasizing high or low frequencies or generating interference terms. The analysis was used to process MMG signals from the vastus lateralis, rectus femoris, and vastus medialis muscles obtained during maximal concentric and eccentric isokinetic movements. Muscular events were observed that were precisely located in time and frequency in a muscle-specific way, thereby showing periods of synergistic contractions of the quadriceps muscles. The MMG wavelet spectra showed different spectral bands for concentric and eccentric isokinetic movements. In addition, the high and low frequency bands seemed to be activated independently during the isokinetic movement. What generates these bands is not yet known, however, the MMG wavelet analysis was able to resolve them, and is therefore applicable to non-stationary MMG signals.     

肌肉动态收缩期间表面肌电信号的时频分析

介绍了用于肌肉动态收缩期间非平稳表面肌电信号的时频分析方法。用短时傅里叶变换、Wigner-Ville分布及Choi-Williams分布计算了表面肌电信号的时频分布,用于信号频率内容随时间演化的可视化观察。通过计算瞬时频谱参数,对肌肉疲劳的电表现进行量化描述。分析了反复性的膝关节弯曲和伸展运动期间从股外侧肌所记录的表面肌电信号。发现和在静态收缩过程中观察到的平均频率线性下降不同,在动态收缩期间瞬时平均频率的变化过程是非线性的并且更为复杂,且与运动的生物力学条件有关。研究表明将时频分析技术应用于动态收缩期间的表面肌电信号可以增加用传统的频谱分析技术不能得到的信息。     

The effects of four time-varying factors on the mean frequency of a myoelectric signal.

Daily activities involve dynamic muscle contractions that yield nonstationary myoelectric signals (MESs). The purpose of this work was to determine the individual effects of four time-varying factors (the number and firing rate of active motor units, muscle force and joint angle) on the mean frequency of a MES. Previous theoretical and experimental work revealed that although changes in the number and firing rate of active motor units contribute to the nonstationarities of the signal, they do not significantly affect the mean frequency. In the experimental work, 12 subjects performed 25 static contractions, one for each force (20, 30, 40, 50 and 60% of maximum voluntary contraction) and elbow joint angle (50, 70, 90, 110 and 130 degrees extension) combination. A MES was recorded from the surface of the biceps brachii during each contraction. The results indicated that muscle force only weakly affects the mean frequency. Also shown was that alteration in muscle geometry resulting from changes in elbow joint angle does significantly affect the mean frequency. Knowing this is important for the assessment of muscle fatigue during dynamic contractions.     

Median frequency of the electromyographic signal: effect of time-window location on brief step contractions.

The purpose of this study was to determine, for different back muscles, if the median frequency (MF) of the electromyographic (EMG) power spectrum changes according to the position of the time window during a 5 s step contraction. Twenty males with no known back problems were standing upright in a dynamometer allowing lower limb and pelvis stabilization. Trunk extension efforts were performed by pushing on a force platform positioned at the T4 level while the extension moment at L5/S1 was displayed as visual feedback. The EMG signals from four homologous back muscles (multifidus at L5, ilicostalis lumborum at L3, and longissimus at L1 and T10) were collected using active surface electrodes during two 5 s static step contractions performed at five force levels (10, 20, 40, 60 and 80% of the maximal voluntary contraction). The root mean square (RMS) and MF values of the EMG signals corresponding to three 250 ms time windows (beginning, middle and end of each step contraction) were computed. The RMS values of several back muscles increased from the first to the third time window for contractions performed at high force levels only. However, a concomitant decrease in the MF values was observed only for the left multifidus muscle. It was concluded that muscle fatigue does not generally manifest itself during 5 s step contractions through the EMG signal. However, it is recommended to use step contractions lasting less than 5 s and to choose a time window located in the first 1-3 s to completely eliminate the possible effects of fatigue.     

EMG frequency content changes with increasing force and during fatigue in the quadriceps femoris muscle of men and women.

The purpose of this study was to determine the effect of gender on changes in electromyographic (EMG) signal characteristics of the quadriceps muscles with increasing force and with fatigue. A total of fourteen healthy adults (seven men, seven women) participated in the study. Subjects had to perform isometric ramp contractions in knee extension with the force gradually increasing from 0 to 100% of the maximal voluntary contraction (MVC) in a 6-s period. Subjects then performed a fatigue task, consisting of a sustained maximum isometric knee extension contraction held until force decreased below 50% of the pre-fatigue MVC. Subjects also performed a single ramp contraction immediately after the fatigue task. The Root Mean Square (RMS) amplitude, mean power frequency (MPF) and median frequency (MF) of EMG signals obtained from the vastus lateralis, vastus medialis and rectus femoris were calculated at nine different force levels from the ramp contractions (10, 20, 30, 40, 50, 60, 70, 80 and 90% MVC), as well as every 5 s during the fatigue task. The main results were a more pronounced increase in EMG RMS amplitude for the three muscles and in MPF for the VL muscle with force in men compared with women. No significant effect of gender was found with regards to fatigue. These observations most likely reflect a moderately greater type II fiber content and/or area in the VL muscle of men compared to that of women.     

Cross-comparison of time- and frequency-domain methods for monitoring the myoelectric signal during a cyclic, force-varying, fatiguing hand-grip task.

Various conventional methods to estimate the mean and median power spectral frequencies, and amplitude of the surface electromyogram during 30-90 min, cyclic, force-varying, constant-posture contractions were cross-compared in an experimental trial. The aim was to determine the most appropriate algorithm implementations and reduce the total number of algorithms that need to be considered when monitoring time trends. Subjects produced hand-grip contractions in a repeated intermittent pattern until exhaustion. For all estimated parameters: analysis of contraction levels below 25% maximum voluntary contraction produced poor estimates due to high relative measurement noise; parameter reproducibility was best when comparisons were aligned to the actual force produced rather than the target force and when the biomechanics of the contraction were more consistent; and estimates were not greatly influenced by the rate of change of the force trajectory. For frequency parameters: estimates based on the short-time Fourier transform were similar to those based on time-varying autoregressive methods; longer duration analysis windows exhibited better repeatability; and simple frequency-domain noise filters were not effective in reducing the impact of measurement noise. For amplitude estimates: whitening reduced the variance of the amplitude estimate; and the best analysis window duration was a trade-off between bias (decreased with a short duration window) and variance (decreased with a long duration window).     

Comparison of Fourier and wavelet transform procedures for examining the mechanomyographic and electromyographic frequency domain responses during fatiguing isokinetic muscle actions of the biceps brachii.

The primary purpose of the present study was to compare the fast Fourier transform (FFT) with the discrete wavelet transform (DWT) for determining the mechanomyographic (MMG) and electromyographic (EMG) center frequency [mean power frequency (mpf), median frequency (mdf), or wavelet center frequency (cf)] patterns during fatiguing isokinetic muscle actions of the biceps brachii. Seven men (mean+/-SD age=23+/-3 years) volunteered to perform 50 consecutive maximal, concentric isokinetic muscle actions of the dominant forearm flexors at a velocity of 180 degrees s(-1). Non-parametric "run" tests indicated significant (p<0.05) trends in the MMG and EMG signals for the 5th, 25th, and 45th muscle actions for all subjects, thereby confirming non-stationarity of the MMG and EMG signals. There were significant (p<0.05) correlations among the average normalized mpf, mdf, and cf values for contractions 1-50 for both MMG (r=0.671-0.935) and EMG (r=0.956-0.987). Polynomial regression analyses demonstrated quadratic decreases in normalized MMG mpf (R2=0.439), MMG mdf (R2=0.258), MMG cf (R2=0.359), EMG mpf (R2=0.952), EMG mdf (R2=0.914) and EMG cf (R2=0.888) across repetitions. The primary finding of this study was the similarity in the mpf, mdf, and cf patterns for both MMG and EMG, which suggested that, despite the concerns over non-stationarity, Fourier based methods are acceptable for determining the patterns for normalized MMG and EMG center frequency during fatiguing dynamic muscle actions at moderate velocities.     

Correlations between short-time Fourier- and continuous wavelet transforms in the analysis of localized back and hip muscle fatigue during isometric contractions.

The aims of the current study were to examine the stationarities of surface electromyographic (EMG) signals obtained from eight bilateral back and hip muscles during a modified Biering-Sørensen test, and to investigate whether short-time Fourier (STFT) and continuous wavelet transforms (CWT) provided similar information with regard to EMG spectral parameters in the analysis of localized muscle fatigue. Twenty healthy subjects participated in the study after giving their informed consent. Reverse arrangement tests showed that 91.6% of the EMG signal epochs demonstrated no significant trends (all p > 0.05), meaning 91.6% of the EMG signal epochs could be considered as stationary signals. Pearson correlation coefficients showed that STFT and CWT in general provide similar information with respect to the EMG spectral variables during isometric back extensions, and as a consequence STFT can still be used.     

Effects of immobilization on electromyogram power spectrum changes during fatigue.

The maximal force and median frequency (MF) of the electromyogram (EMG) power density spectrum (PDS) have been compared in disused (6 weeks' immobilization) and control (contralateral) human adductor pollicis muscles during fatigue induced by voluntary or electrically-triggered (30 Hz) contractions. The results indicated that after 6 weeks' immobilization, MF was not significantly different in disused and control muscles although the force and integrated EMG were drastically reduced during a maximal voluntary contraction (MVC; by 55% and 45%, respectively, n = 8). During sustained 60 s MVC, the force decreased at the same rate in immobilized and control muscles, but the shift of MF towards lower frequency values was smaller (P less than 0.05) in disused muscle as compared to control by (14% vs 28%, respectively). In electrically-induced fatigue, the force decrease and the MF shift were larger after inactivity (41% and 43% in one subject, and 50% and 54% in the other subject, respectively) as compared to control (29% and 34% in one subject, and 37% and 38% in the other subject, respectively). These results emphasize the caution that should be exercised when EMG signals are quantified by computing the power density spectrum. The different effects of fatigue during voluntary and electrically-imposed contractions in disused and control muscles indicated that immobilization induced changes in the neural command for the contraction which compensated, at least in part, for its decreased contractile efficiency and resistance to fatigue.     

Interpretation of EMG spectral alterations and alteration indexes at sustained contraction.

Alterations of the electromyographic power spectrum have been studied extensively to assess fatigue development in the neuromuscular system. Usually, a data reduction has been applied to create an index based on the mean power frequency or the median frequency. The physiological origin of the spectrum alterations has been (and to some extent still is) incompletely known. However, during the 1980s, substantial progress has been made in this field. The factors affecting the electromyographic power spectrum discussed in this review are action potential velocity decrease, firing statistics alterations, action potential modification, muscle temperature, additional recruitment at fatigue, and force level. Their impact on three commonly used fatigue indexes, mean power frequency, median frequency, and zero crossing rate, is also reviewed.     

Predicting isometric force from muscular activation using a physiologically inspired model

Motivated by biochemical processes during muscular contraction, a model is constructed that predicts isometric force from surface electromyographic signals (sEMG). The model is experimentally validated and then it is used to predict contractions from sEMG data. The calculated simulations reveal a highly non-linear relationship between sEMG and isometric force.     

Time-frequency methods applied to muscle fatigue assessment during dynamic contractions.

This paper discusses the assessment of the electrical manifestations of muscle fatigue during dynamic contractions. In the past, the study of muscle fatigue was restricted to isometric constant force contractions because, in this contraction paradigm, the myoelectric signal may be considered as wide sense stationary over epochs lasting up to two or three seconds, and hence classic spectral estimation techniques may be applied. Recently, the availability of spectral estimation techniques specifically designed for nonstationary signal analysis made it possible to extend the employment of muscle fatigue assessment to cyclic dynamic contractions, thus increasing noticeably its possible clinical applications. After presenting the basics of time-frequency distributions, we introduce instantaneous spectral parameters well suited to tracking spectral changes due to muscle fatigue, discuss the issues of quasi-stationarity and quasi-cyclostationarity, and present different strategies of signal analysis to be utilized with cyclic dynamic contractions. We present preliminary results obtained by analyzing data collected from paraspinal muscles during repetitive lift movements, from the first dorsal interosseus during abduction-adduction movements of the index finger, and from knee flexors and extensors during isokinetic exercise. In conclusion, data herein reported demonstrate that the described techniques allow for evidencing the electrical manifestations of muscle fatigue in different paradigms of cyclic dynamic contractions. We believe that the extension of the objective assessment of the electrical manifestations of muscle fatigue from static to dynamic contractions may increase considerably the interest of researchers and clinicians and open new application fields, as ergonomics and sports medicine.     

Duration of differential activations is functionally related to fatigue prevention during low-level contractions

The aim of this study was to investigate the importance of duration of differential activations between the heads of the biceps brachii on local fatigue during prolonged low-level contractions. Fifteen subjects carried out isometric elbow flexion at 5% of maximal voluntary contraction (MVC) for 30 min. MVCs were performed before and at the end of the prolonged contraction. Surface electromyographic (EMG) signals were recorded from both heads of the biceps brachii. Differential activation was analysed based on the difference in EMG amplitude (activation) between electrodes situated at the two heads. Differential activations were quantified by the power spectral median frequency of the difference in activation between the heads throughout the contraction. The inverse of the median frequency was used to describe the average duration of the differential activations. The relation between average duration of the differential activations and the fatigue-induced reduction in maximal force was explored by linear regression analysis. The main finding was that the average duration of differential activation was positively associated to relative maximal force at the end of the 30 min contraction (R² = 0.5, P < 0.01). The findings of this study highlight the importance of duration of differential activations for local fatigue, and support the hypothesis that long term differential activations prevent fatigue during prolonged low-level contractions.     

Effect of load, speed, and activity history on the EMG signals from the intact human muscle

A specially instrumented bicycle ergometer is utilized in this investigation to induce reproducable loading conditions on the muscles of the lower extremity at different speeds. Various tehcniques for evaluating the electromyographic signals from the vastas medialis muscle are investigated for different load and speed conditions and shown to be essentially equivalent. The RMS signal power computed by means of a real time spectral analyzer is shown to be a convenient means of quantification of the dynamic EMG signals. The electromyographic signals are shown to be stable under repeated static or dynamic conditions but not under sustained isometric static loading.     

Assessment of low back muscle fatigue by surface EMG signal analysis: methodological aspects.

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 global level of amplitude and spectral analysis cannot be used to characterize fatigue properties of low back muscles during very low level, long duration contractions since in these cases the non-stable MU pool has a major influence on the EMG variables. These considerations clarify issues only partially investigated in past studies. The limitations indicated above are important and should be carefully discussed when presenting surface EMG results as a means for low back muscle assessment in clinical practice.