Nonlinear surface EMG analysis to detect changes of motor unit conduction velocity and synchronization.

Amplitude and frequency content of the surface electromyographic (EMG) signal reflect central and peripheral modifications of the neuromuscular system. Classic surface EMG spectral variables applied to assess muscle functions are the centroid and median power spectral frequencies. More recently, nonlinear tools have been introduced to analyze the surface EMG; among them, the recurrence quantification analysis (RQA) was shown to be particularly promising for the detection of muscle status changes. The purpose of this work was to analyze the effect of motor unit short-term synchronization and conduction velocity (CV) on EMG spectral variables and two variables extracted by RQA, the percentage of recurrence (%Rec) and determinism (%Det). The study was performed on the basis of a simulation model, which allowed changing the degree of synchronization and mean CV of a number of motor units, and of an experimental investigation of the surface EMG signal properties detected during high-force-level isometric fatiguing contractions of the biceps brachii muscle. Simulations and experimental results were largely in agreement and show that 1) spectral variables, %Rec, and %Det are influenced by CV and degree of synchronization; 2) spectral variables are highly correlated with %Det (R = -0.95 in the simulations and -0.78 and -0.75 for the initial values and normalized slopes, respectively, in the experimental signals), and thus the information they provide on muscle properties is basically the same; and 3) variations of %Det and %Rec in response to changes in muscle properties are significantly larger than the variations of spectral variables. This study validates RQA as a means for fatigue assessment with potential advantages (such as the higher sensitivity to changes of muscle status) with respect to the classic spectral analysis.     

RQA在肌电分析中的应用

介绍了递归图的生成方法和定量递归分析（RQA）中递归点的百发数,确定性线段的百分数,线段分布香农熵等分析量的意义。应用RQA分析肱二头肌及肱桡肌在不同负重下的肌电信号,发现肽二头肌肌电信号的递归点百分数的比肱肌高,有较强的周期性嵌入。与同一信号所作的FFT谱分析相比较,RQA法有较同的区分灵敏性,是肌电分析的一种新方法,它在其他复杂的生理信号处理中也有十分广阔的应用前景。     

EMG recurrence quantifications in dynamic exercise

This study was designed to evaluate the suitability of nonlinear recurrence quantification analysis (RQA) in assessing electromyograph (EMG) signals during dynamic exercise. RQA has been proven to be effective in analyzing nonstationary signals. The subject group consisted of 19 male patients diagnosed with low back pain. EMG signals were recorded from left and right paraspinal muscles during isoinertial exercise both before and after 12 weeks of regimented physical therapy. Autorecurrence analysis was performed between the left and right EMG signals individually, and cross-recurrence analysis was performed on the left-right EMG pairs. Spectral analysis of the EMG signals was employed as an independent, objective measure of fatigue. Increase in the RQA variable % determinism during the 90-s dynamic tests was found to be a good marker for fatigue. Before physical therapy, this nonlinear marker revealed simultaneous increases in motor unit recruitment within each pool and between left and right pools. After physical therapy, the motor unit recruitment was less within and between pools, indicative of increased fatigue resistance. Finally, fatigue resistance (less increase in % determinism) correlated well with subjective scores of pain relief. Taken together, these latter results indicate that recurrence analysis may be useful in charting the efficacy of a specific exercise therapy program in reducing low back pain by elevating the fatigue threshold.     

Nonlinear smooth orthogonal decomposition of kinematic features of sawing reconstructs muscle fatigue evolution as indicated by electromyography

Tracking or predicting physiological fatigue is important for developing more robust training protocols and better energy supplements and/or reducing muscle injuries. Current methodologies are usually impractical and/or invasive and may not be realizable outside of laboratory settings. It was recently demonstrated that smooth orthogonal decomposition (SOD) of phase space warping (PSW) features of motion kinematics can identify fatigue in individual muscle groups. We hypothesize that a nonlinear extension of SOD will identify more optimal fatigue coordinates and provide a lower-dimensional reconstruction of local fatigue dynamics than the linear SOD. Both linear and nonlinear SODs were applied to PSW features estimated from measured kinematics to reconstruct muscle fatigue dynamics in subjects performing a sawing motion. Ten healthy young right-handed subjects pushed a weighted handle back and forth until voluntary exhaustion. Three sets of joint kinematic angles were measured from the right upper extremity in addition to surface electromyography (EMG) recordings. The SOD coordinates of kinematic PSW features were compared against independently measured fatigue markers (i.e., mean and median EMG spectrum frequencies of individual muscle groups). This comparison was based on a least-squares linear fit of a fixed number of the dominant SOD coordinates to the appropriate local fatigue markers. Between subject variability showed that at most four to five nonlinear SOD coordinates were needed to reconstruct fatigue in local muscle groups, while on average 15 coordinates were needed for the linear SOD. Thus, the nonlinear coordinates provided a one-order-of-magnitude improvement over the linear ones.     

Muscle fatigue and calibration of EMG measurements

Amplitude electromyography (EMG) is often used as an estimator of muscular load. Such measurements can, however, be biased by other factors, for example muscular fatigue. The aim of this study was to examine the influence of fatigue on amplitude parameters of the EMG. The test subjects raised the arm to 90⁹ of abduction in the plane of the scapula. The hand was loaded with 0, 1 and 2 kg during 5, 3 and 2 min respectively. EMG was recorded from the trapezius muscle, and spectral and amplitude parameters were calculated. There was a significant rise of the EMG amplitude as a sign of fatigue at all load levels: 7% min⁻¹ at 0 kg, 15% min⁻¹ at 1 kg, and 19% min⁻¹ at 2 kg. At 0 kg hand load there was no change of the spectral parameters but at higher load levels there was a significant decline of mean power frequency: 3% min⁻¹ at 1 kg and 11% at 2 kg. The amplitude rise due to muscle fatigue may seriously jeopardize calibration measurements unless the duration of the load is kept limited.     

表面肌电信号的肌肉疲劳判别研究进展

肌肉在周期的收缩或静态的拉伸过程中,会渐渐进入疲劳状态,肌肉疲劳特性的研究在康复医学、运动医学领域具有重要作用。表面肌电信号是从肌肉表面通过电极记录下来的反映神经肌肉系统活动的一维时间序列非平稳生物电信号,是评价局部肌肉疲劳的有效工具。本研究从时域和频域、时频域线性方法下的测量指标和非线性方法下的指标来综述表面肌电信号的疲劳研究进展,同时比较各种方法的优缺点,并对使用表面肌电信号来判别疲劳研究做了进一步的展望。     

Intramuscular and surface electromyogram changes during muscle fatigue

Twelve male subjects were tested to determine the effects of motor unit (MU) recruitment and firing frequency on the surface electromyogram (EMG) frequency power spectra during sustained maximal voluntary contraction (MVC) and 50% MVC of the biceps brachii muscle. Both the intramuscular MU spikes and surface EMG were recorded simultaneously and analyzed by means of a computer-aided intramuscular spike amplitude-frequency histogram and frequency power spectral analysis, respectively. Results indicated that both mean power frequency (MPF) and amplitude (rmsEMG) of the surface EMG fell significantly (P less than 0.001) together with a progressive reduction in MU spike amplitude and firing frequency during sustained MVC. During 50% MVC there was a significant decline in MPF (P less than 0.001), but this decline was accompanied by a significant increase in rmsEMG (P less than 0.001) and a progressive MU recruitment as evidenced by an increased number of MUs with relatively large spike amplitude. Our data suggest that the surface EMG amplitude could better represent the underlying MU activity during muscle fatigue and the frequency powers spectral shift may or may not reflect changes in MU recruitment and rate-coding patterns.     

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.     

Adaptive filtering for ECG rejection from surface EMG recordings.

Surface electromyograms (EMG) of back muscles are often corrupted by electrocardiogram (ECG) signals. This noise in the EMG signals does not allow to appreciate correctly the spectral content of the EMG signals and to follow its evolution during, for example, a fatigue process. Several methods have been proposed to reject the ECG noise from EMG recordings, but seldom taking into account the eventual changes in ECG characteristics during the experiment. In this paper we propose an adaptive filtering algorithm specifically developed for the rejection of the electrocardiogram corrupting surface electromyograms (SEMG). The first step of the study was to choose the ECG electrode position in order to record the ECG with a shape similar to that found in the noised SEMGs. Then, the efficiency of different algorithms were tested on 28 erector spinae SEMG recordings. The best algorithm belongs to the fast recursive least square family (FRLS). More precisely, the best results were obtained with the simplified formulation of a FRLS algorithm. As an application of the adaptive filtering, the paper compares the evolutions of spectral parameters of noised or denoised (after adaptive filtering) surface EMGs recorded on erector spinae muscles during a trunk extension. The fatigue test was analyzed on 16 EMG recordings. After adaptive filtering, mean initial values of energy and of mean power frequency (MPF) were significantly lower and higher respectively. The differences corresponded to the removal of the ECG components. Furthermore, classical fatigue criteria (increase in energy and decrease in MPF values over time during the fatigue test) were better observed on the denoised EMGs. The mean values of the slopes of the energy-time and MPF-time linear relationships differed significantly when established before and after adaptive filtering. These results account for the efficacy of the adaptive filtering method proposed here to denoise electrophysiological signals.     

Changes in electromyogram power spectra of facial and jaw-elevator muscles during fatigue

Endurance and changes in electromyogram (EMG) power spectra were investigated during a fatiguing static contraction at 50% of the maximum EMG amplitude in two jaw-elevator muscles (masseter and temporalis) and five facial muscles (frontalis, corrugator supercilii, zygomaticus major, orbicularis oris, and buccinator). Relatively high endurance was found in orbicularis oris, frontalis, and corrugator supercilii muscles; intermediate endurance was found in zygomaticus major, buccinator, and temporalis muscles; and low endurance was found in the masseter muscle. The last muscle showed a relatively fast linear decrease of the median frequency of the power spectrum. The other muscles showed a much slower, exponential decrease. The median frequency appeared to reflect reliably the changes in the shape of the power spectra during fatigue. Large differences between the shape of power spectra of different muscles in the unfatigued state were found. These, however, were unrelated to endurance and degree of spectral shift during fatigue.     

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.     

Fatigue-induced changes in muscle fiber action potentials estimated by wavelet analysis

We aimed to investigate fatigue-induced changes in the spectral parameters of slow (SMF) and fast fatigable muscle fiber (FMF) action potentials using discrete wavelet (DWT) and fast Fourier (FFT) transforms. Intracellular potentials were recorded during repetitive stimulation of isolated muscle fibers immersed in Ca²⁺-enriched medium, while extracellular potentials were obtained from muscle fibers pre-exposed to electromagnetic microwaves (MMW, 2.45 GHz, 20 mW/cm²). The changes in the frequency distribution of the action potentials during the period of uninterrupted fiber activity were used as criteria for fatigue assessment. The wavelet coefficients’ changes in the calculated frequency scales demonstrated a contribution of the increased [Ca²⁺]₀ to an earlier compression of the frequency spectrum towards lower ranges. Root mean square (RMS) analysis of the wavelet coefficients calculated from SMF potentials showed a reduction of the higher frequencies (scale 1) by 90% in elevated [Ca²⁺]₀ vs. 55% in controls and an increase of low frequencies (scale 5) by 323% vs. 187%, respectively. For FMF potentials a decrease of 71% vs. 59% for high frequencies (scale 1, elevated [Ca²⁺]₀ vs. control) and an increase of 386% vs. 295% in scale 5, respectively, were observed. MMW pre-exposure resulted in increased muscle fiber resistance to fatigue. The fatigue-induced decrease of potential high frequencies (SMF: 59% vs. 96%, MMW vs. control; FMF: 30% vs. 92%, respectively), and the increase of low frequencies (SMF: 200% vs. 207%, MMW vs. control; FMF: 93% vs. 314%, respectively) were significantly smaller and delayed in exposed muscle fibers. Data from RMS analysis indicate that DWT provides a reliable method for estimation of muscle fatigue onset and progression.     

Surface EMG power spectrum and intramuscular pH in human vastus lateralis muscle during dynamic exercise

The relationship between intramuscular pH and the frequency components of the surface electromyographic (EMG) power spectrum from the vastus lateralis muscle was studied in eight healthy male subjects during brief dynamic exercise. The studies were carried out in placebo control and metabolic alkalosis induced by oral administration of NaHCO3. At the onset of exercise, blood pH was 0.08 units higher in alkalosis compared with placebo. Muscle lactate accumulation during exercise was higher in alkalosis (32 +/- 5 mmol/kg wet wt) than in placebo (17 +/- 4 mmol/kg wet wt), but no difference in intramuscular pH was found between the two conditions. The EMG power spectrum was shifted toward lower frequencies during fatigue in the control condition (10.1 +/- 0.9%), and these spectral shifts, evaluated from changes in the mean power frequency (MPF) of the EMG power spectrum, were further accentuated in alkalosis (19 +/- 2%). Although the changes in frequency components of EMG correlated with muscle lactate accumulation (r = 0.68, P less than 0.01), no direct relationship with muscle pH was observed. We conclude that alkalosis results in a greater reduction in MPF associated with a higher muscle lactate accumulation. However, the good correlation observed between the two variables is not likely causative, and a dissociation between intramuscular pH and the increase in the low-frequency content of EMG power spectrum appears during muscle fatigue.     

Issues in relation to the repeatability of and correlation between EMG and Borg scale assessments of neck muscle fatigue.

INTRODUCTION: The repeatability of subjective and objective assessments of neck muscle fatigue is very important with regard to the clinical applicability of these methods. METHOD: To establish between-days reliability, 33 healthy volunteers performed a 60% maximum voluntary isometric contraction test from a standing position in all neck movements. Cervical muscle fatigue was assessed on three separate occasions from the spectral (median frequency, MF) and amplitude (root mean square, RMS) analysis of the electromyogram (EMG) signal recorded from the cervical paraspinal group, splenius capitis, levator scapulae and sternocleidomastoid. Subjective assessment of fatigue was rated by employing the Borg scale. Intraclass correlation coefficient ICC((1,1)), standard error of measurement (SEM), smallest detectable difference (SDD) indices and Pearson's correlation co-efficient were calculated for the analysis of the results. RESULTS: Normalised median frequency (MF) slope had low repeatability and large between-day error (ICC((1,1))=0.28-0.61; SEM=0.33-0.60%/s; SDD=132.7-703.2%) for the protagonist muscles of each movement. Initial median frequency (IMF) had moderate to good reliability and small error (ICC((1,1))=0.64-0.81; SEM=2.8-8.8Hz; SDD=19.9-38.5%). The RMS slope yielded also poor repeatability. The Borg assessment was more reliable than the EMG estimate though variability between sessions was still quite high (SDD=29.2-136.5%). No correlation was found between the EMG and Borg assessment of neck muscle fatigue (r=-0.01-0.39). CONCLUSION: The protocol used for assessing neck muscle fatigue proved to be reliable only for the IMF but the clinical usefulness of this measure remains questionable. The lack of correlation between objective and subjective estimation of neck muscle fatigue was possibly a consequence of the poor measurement repeatability. Further research is needed to identify the factors responsible for these results on neck area.     

Effects of aging on EMG variables during fatiguing isometric contractions

The purpose of this study was to evaluate the neuromuscular adaptation that occurred with aging, by comparing young and aged subjects with respect to changes in surface EMG from the tibialis anterior muscle during fatiguing contractions. EMG variables such as the averaged rectified value (ARV), median frequency (MDF), and muscle fiber conduction velocity (MFCV) were calculated during maximal (MVC, 3 sec) and submaximal (60% MVC, 60 sec) isometric contractions. Muscular force, ARV, MDF, and MFCV during MVC were significantly greater in the young than in the elderly (p < 0.05). EMG amplitude increased and the waveform slowed in all subjects during submaximal contractions, indicating the development of local muscle fatigue. As fatigue progressed, the ARV increased and the MDF and MFCV decreased significantly (p < 0.01). The fatigue-induced changes in the MDF and MFCV were significantly smaller in aged than in young subjects (p < 0.05), a trend also seen in the ARV change, which means that the elderly cannot be fatigued as much as the young with contractions of the same relative intensity. These results as a whole suggest that the aged subjects hold an adaptive motor strategy to cope with age-related neuromuscular deteriorations, due to the decline of motor unit activation and selective atrophy of fast twitch muscle fibers.     

Electromyographic Parameters of Muscle Fatigue in Patients with Parkinsonism

The authors studied muscle fatigue in patients with parkinsonism receiving pathogenetic therapy and in elderly healthy subjects by means of turn-amplitude analysis of surface electromyography (EMG). The healthy subjects reacted to fatigue with a significant increase in the amplitude and number of EMG turns during static exercise and a decrease in the peak ratio. In patients with parkinsonism, fatigue began after an exercise that was half of that in the healthy subjects with a decrease in the number of turns and mean amplitude and an increase in peak ratio. These data show that dynamics of strength and EMG parameters differs in patients with parkinsonism and healthy subjects.     

Time-frequency analysis of surface electromyographic signals during fatiguing isokinetic muscle actions

The purpose of this study was to use a wavelet analysis designed specifically for electromyography (EMG) signals in combination with a trend plot to examine changes in EMG intensity patterns during maximal, fatiguing isokinetic muscle actions. Eleven men (mean ± SD age = 22.4 ± 1.1 years) and 7 women (mean ± SD age = 22.7 ± 2.1 years) performed 50 consecutive maximal concentric isokinetic muscle actions of the dominant leg extensors at a velocity of 180°·s(-1). During each muscle action, a bipolar surface EMG signal was detected from the vastus lateralis. All signals were then processed with a wavelet analysis designed specifically for EMG signals, which resulted in EMG intensity patterns. The patterns for each subject were then analyzed with a trend plot, which provided information regarding the changes that occurred because of fatigue. The results indicated that for all the 18 subjects, the EMG intensity patterns moved in a predictable manner in pattern space, but the changes to the patterns were different for each subject. These findings reflect the complex changes that occur in the EMG signal during fatigue. These changes cannot be characterized fully with a single amplitude and center frequency parameter and can be useful for athletes and coaches who need to track the fatigue status of individual muscles.     

Effect of diaphragm fatigue on neural respiratory drive.

To test the hypothesis that diaphragm fatigue leads to an increase in neural respiratory drive, we measured the esophageal diaphragm electromyogram (EMG) during CO(2) rebreathing before and after diaphragm fatigue in six normal subjects. The electrode catheter was positioned on the basis of the amplitude and polarity of the diaphragm compound muscle action potential recorded simultaneously from four pairs of electrodes during bilateral anterior magnetic phrenic nerve stimulation (BAMPS) at functional residual capacity. Two minutes of maximum isocapnic voluntary ventilation (MIVV) were performed in six subjects to induce diaphragm fatigue. A maximal voluntary breathing against an inspiratory resistive loading (IRL) was also performed in four subjects. The reduction of transdiaphragmatic pressure elicited by BAMPS was 22% (range 13-27%) after 2 min of MIVV and was similar, 20% (range 13-26%), after IRL. There was a linear relationship between minute ventilation (VE) and the root mean square (RMS) of the EMG during CO(2) rebreathing before and after fatigue. The mean slope of the linear regression of RMS on VE was similar before and after diaphragm fatigue: 2.80 +/- 1.31 vs. 3.29 +/- 1.40 for MIVV and 1.51 +/- 0.31 vs 1.55 +/- 0.31 for IRL, respectively. We conclude that the esophageal diaphragm EMG can be used to assess neural drive and that diaphragm fatigue of the intensity observed in this study does not affect respiratory drive.     

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.     

Evaluation of measurement strategies to increase the reliability of EMG indices to assess back muscle fatigue and recovery.

The purpose of this study was to assess different measurement strategies to increase the reliability of different electromyographic (EMG) indices developed for the assessment of back muscle impairments. Forty male volunteers (20 controls and 20 chronic low back pain patients) were assessed on three sessions at least 2 days apart within 2 weeks. Surface EMG signals were recorded from four pairs (bilaterally) of back muscles (multifidus at the L5 level, iliocostalis lumborum at L3, and longissimus at L1 and T10) while the subjects performed, in a static dynamometer, two static trunk extension tasks at 75% of the maximal voluntary contraction separated by a 60 s rest period: (1) a 30 s fatigue task and (2) a 5 s recovery task. Different EMG indices (based on individual muscles or averaged across bilateral homologous muscles or across all muscles) were computed to evaluate muscular fatigue and recovery. Intra-class correlation coefficient (ICC) and standard error of measurement (SEM) in percentage of the grand mean were calculated for each EMG variable. Reliable EMG indices are achieved for both healthy and chronic low back pain subjects when (1) electrodes are positioned on medial back muscles (multifidus at the L5 level and longissimus at L1) and (2) measures are averaged across bilateral muscles and/or across two fatigue tests performed within a session. The most reliable EMG indices were the bilateral average of medial back muscles (ICC range: 0.68-0.91; SEM range: 5-35%) and the average of all back muscles (ICC range: 0.77-0.91; SEM range: 5-30%). The averaging of measures across two fatigue tests is predicted to increase the reliability by about 13%. With regards to EMG indices of fatigue, the identification of the most fatigable muscle also lead to satisfactory results (ICC range: 0.74-0.79; SEM range: 21-26%). The assessment of back muscle impairments through EMG analysis necessitates the use of multiple electrodes to achieve reliable results.