EMG Spectrum Research Articles

Evaluation of Muscle Fatigue in Spinal Surgery Instruments Based on sEMG-JASA

Based on the joint analysis of EMG spectrum and amplitude method (JASA), a study on muscle fatigue assessment of spinal surgical instruments based on surface EMG signals was carried out, and a comparative evaluation of the operating comfort before and after the optimization of spinal surgical instruments was completed. A total of 17 subjects were recruited to collect the surface EMG signals of their brachioradialis and biceps. Five surgical instruments before and after optimization were selected for data comparison, and the operating fatigue time proportion of each group of instruments under the same task was calculated based on the RMS and MF eigenvalues. The results showed that when completing the same operation task, the operation fatigue time of the surgical instruments before optimization was significantly higher than that after optimization (P<0.05); there was no significant difference in the fatigue status of brachioradialis and biceps when operating the same instrument (P>0.05). These results provide objective data and reference for the ergonomic design of surgical instruments and fatigue damage protection.

EMG Signal Processing for the Study of Localized Muscle Fatigue-Pilot Study to Explore the Applicability of a Novel Method.

This pilot study aimed to explore a method for characterization of the electromyogram frequency spectrum during a sustained exertion task, performed by the upper limb. Methods: Nine participants underwent an isometric localized muscle fatigue protocol on an isokinetic dynamometer until exhaustion, while monitored with surface electromyography (sEMG) of the shoulder’s external rotators. Firstly, three methods of signal energy analysis based on primer frequency contributors were compared to the energy of the entire spectrum. Secondly, the chosen method of analysis was used to characterize the signal energy at beginning (T1), in the middle (T2) and at the end (T3) of the fatigue protocol and compared to the torque output and the shift in the median frequencies during the trial. Results: There were statistically significant differences between T1 and T3 for signal energy (p < 0.007) and for central frequency of the interval (p = 0.003). Moreover, the isometric peak torque was also different between T1 and T3 (p < 0.001). Overall, there were no differences between the signal energy enclosed in the 40 primer frequency contributors and the analysis of the full spectrum energy; consequently, it was the method of choice. The reported fatigue and the decrease in the produced muscle torque was consistent with fatigue-induced alterations in the electromyogram frequency spectrum. In conclusion, the developed protocol has potential to be considered as an easy-to-use method for EMG-based analysis of isometric muscle exertion until fatigue. Thus, the novelty of the proposed method is to explore, in muscle fatigue, the use of only the main contributors in the frequency domain of the EMG spectrum, avoiding surplus information, that may not represent muscle functioning. However, further studies are needed to investigate the stability of the present findings in a more comprehensive sample.

Simplified Optimal Estimation of Time-Varying Electromyogram Standard Deviation (EMGσ): Evaluation on Two Datasets.

To facilitate the broader use of EMG signal whitening, we studied four whitening procedures of various complexities, as well as the roles of sampling rate and noise correction. We separately analyzed force-varying and constant-force contractions from 64 subjects who completed constant-posture tasks about the elbow over a range of forces from 0% to 50% maximum voluntary contraction (MVC). From the constant-force tasks, we found that noise correction via the root difference of squares (RDS) method consistently reduced EMG recording noise, often by a factor of 5–10. All other primary results were from the force-varying contractions. Sampling at 4096 Hz provided small and statistically significant improvements over sampling at 2048 Hz (~3%), which, in turn, provided small improvements over sampling at 1024 Hz (~4%). In comparing equivalent processing variants at a sampling rate of 4096 Hz, whitening filters calibrated to the EMG spectrum of each subject generally performed best (4.74% MVC EMG-force error), followed by one universal whitening filter for all subjects (4.83% MVC error), followed by a high-pass filter whitening method (4.89% MVC error) and then a first difference whitening filter (4.91% MVC error)—but none of these statistically differed. Each did significantly improve from EMG-force error without whitening (5.55% MVC). The first difference is an excellent whitening option over this range of contraction forces since no calibration or algorithm decisions are required.

Understanding the effect of window length and overlap for assessing sEMG in dynamic fatiguing contractions: A non-linear dimensionality reduction and clustering

The Short-Time Fourier transform (STFT) is a helpful tool to identify muscle fatigue with clinical and sports applications. However, the choice of STFT parameters may affect the estimation of myoelectrical manifestations of fatigue. Here, we determine the effect of window length and overlap selections on the frequency slope and the coefficient of variation from EMG spectrum features in fatiguing contractions. We also determine whether STFT parameters affect the relationship between frequency slopes and task failure. Eighty-eight healthy adult men performed one-leg heel-rise until exhaustion. A factorial design with a window length of 50, 100, 250, 500, and 1000 ms with 0, 25, 50, 75, and 90% of overlap was used. The frequency slope was non-linearly fitted as a task failure function, followed by a dimensionality reduction and clustering analysis. The STFT parameters elicited five patterns. A small window length produced a higher slope frequency for the peak frequency (p < 0.001). The contrary was found for the mean and median frequency (p < 0.001). A larger window length elicited a higher slope frequency for the mean and peak frequencies. The largest frequency slope and dispersion was found for a window length of 50 ms without overlap using peak frequency. A combination of 250 ms with 50% of overlap reduced the dispersion both for peak, median, and mean frequency, but decreased the slope frequency. Therefore, the selection of STFT parameters during dynamic contractions should be accompanied by a mechanical measure of the task failure, and its parameters should be adjusted according to the experiment’s requirements.

Analysis of Spasticity Patient by Using sEMG to detect Fatigue Level During Rehabilitation

Spasticity is a feature of altered skeletal muscle performance with the constraint of tendon reflex activity. The level of fatigue in spastic patients is difficult to be measured without a high-end measurement system. This work aims to evaluate the effectiveness of spasticity robotic arms robot and surface Electromyogram (sEMG) on the observation and measurement of the arms-hand skill in stroke patients during rehabilitation. The result will provide an overview of criteria and conditions for the implementation of the technology in clinical practice. This study assesses the fatigue level among spasticity patients based on the localized muscle voluntary of the patient measured using the spasticity robotic arms (SRA) and Joint Analysis of EMG Spectrum and Amplitude (JASA). The data signal was changed to spectrum and medium frequency to evaluate the fatigue where the non-implant surface electromyogram was recorded in each motor unit in real-time. The analysis JASA method able to shows the level of fatigue in a multi-degree range of motion. The sampling data signal was integrated with therobotic therapy to overcome the over-exercise or lack of training during rehabilitation. The five axes of SRA can assist the therapy to perform in multi-degree rotation with the robust flexion-extension and abduction-adduction rotations. The accuracy between RSA and LSA is 0.003 ± 0.0910 of amplitude frequency against ROM. Further investigation in Medium Frequency (MDF) is 32.81 ± 45.341 revolution between RSA and LSA is 93.9% accuracy. The effect between RSA and LSA kinematic ROM is 0.6875 ± 9.0401accuracy in 95% between each assessment in MDF. The revolute and prismatic motion was able to overcome the difficulty of spasticity patient range of motion because of stroke. The Surface EMG for non-invasive assessment of muscles (SENIAM) assessment Fugl-Meyer Assessment (FMA) is used to guide the active-passive assisted motion. The fatigue detection method was evaluated based on eight male and eight female subjects. The process of the exercise made the patient fatigue because due to the muscle unable to carry the burden of the force from the SRA robot in 95% cases for RSA and 75% in LSA. The success of work proves the JASA method and SRA robot therapy able to assist to determine the level of fatigue among spasticity patients.

Performance Evaluation of a Wearable Tattoo Electrode Suitable for High-Resolution Surface Electromyogram Recording.

High-density surface electromyography (HD-sEMG) has been utilized extensively in neuromuscular research. Despite its potential advantages, limitations in electrode design have largely prevented widespread acceptance of the technology. Commercial electrodes have limited spatial fidelity, because of a lack of sharpness of the signal, and variable signal stability. We demonstrate here a novel tattoo electrode that addresses these issues. Our dry HD electrode grid exhibits remarkable deformability which ensures superior conformity with the skin surface, while faithfully recording signals during different levels of muscle contraction. We fabricated a 4 cm×3 cm tattoo HD electrode grid on a stretchable electronics membrane for sEMG applications. The grid was placed on the skin overlying the biceps brachii of healthy subjects, and was used to record signals for several hours while tracking different isometric contractions. The sEMG signals were recorded successfully from all 64 electrodes across the grid. These electrodes were able to faithfully record sEMG signals during repeated contractions while maintaining a stable baseline at rest. During voluntary contractions, broad EMG frequency content was preserved, with accurate reproduction of the EMG spectrum across the full signal bandwidth. The tattoo grid electrode can potentially be used for recording high-density sEMG from skin overlying major limb muscles. Layout programmability, good signal quality, excellent baseline stability, and easy wearability make this electrode a potentially valuable component of future HD electrode grid applications. The tattoo electrode can facilitate high fidelity recording in clinical applications such as tracking the evolution and time-course of challenging neuromuscular degenerative disorders.

Fatigue Induced Changes of the EMG Profile of Select Lower Extremity Muscles in Competitive Cyclists

PURPOSE: To determine the effect of fatigue on the median frequency (MF) and amplitude (AMP) of select lower extremity muscles in competitive cyclists. METHODS: Five category 4 or above cyclists (29.6 yrs ± 16.0) were recruited for this pilot study. Data collection consisted of 2 sessions. At session one, the subject’s maximum work load (MWL) was determined during an incremental cycling test. At session two, EMG activity of the rectus femoris (RF), vastus medialis (VM) and lateralis (VL), semitendinosus (ST), biceps femoris (BF), gastrocnemius (GS), tibialis anterior (TA) and gluteus maximus (GM) were recorded bilaterally at 2400 Hz using surface electrodes during a fatigue protocol. The fatigue protocol consisted of a 4-minute warm-up at 55% of their MWL followed by 5, alternating efforts at 90% and 55% of their MWL for 1 and 2-minutes respectively. This was followed by a continuous cycling effort at 90% of their MWL until fatigue (pedaling rate < 80 RPM). For each muscle, the EMG data were band pass filtered and the MF was determined using a time-frequency analysis based on power spectra estimation (short-time Fourier transform). The average MF and average peak AMP was calculated for each trial. The average change in MF and average peak AMP from the 1st trial to the fatigue trial for each muscle were calculated. RESULTS: The average MF for the RF, VM, VL, ST, BF, and TA increased by 3.0, 3.4, 5.8, 4.2, 1.2, and 0.6 %, respectively from trial 1 to the fatigue trial while the MF for the GM and GS decreased by 7.3 and 5.8%, respectively. The average peak AMP for the RF, VM, VL, ST, BF, and GM increased by 44.9, 27.5, 23.4, 18.6, 38.3, and 51.6%, respectively while the average peak AMP for the TA and GS decreased by 2.0 and 6.3%, respectively. CONCLUSION: According to Luttmann et al’s (1996) joint analysis of EMG spectrum and amplitude theory, the quadriceps (RF, VM, VL) and hamstring (BF, ST) muscles demonstrated an increase in force production, while the GS and TA exhibited a decrease force production during fatigue. Only the GM exhibited a classical fatigue pattern of activity (decrease MF, increase AMP). These results suggest that in the current testing paradigm both central and peripheral fatigue may be contributing to the inability to maintain pedaling rate. Funding was provided in part by the 2016 NEACSM Undergraduate Research Experience Grant.

Characteristics of EMG frequency bands in temporomandibullar disorders patients

The aim of the present study was to determine whether any specific frequency bands of surface electromyographic (sEMG) signals are more susceptible to alterations in patients with temporomandibular disorders (TMD), when compared with healthy subjects. Twenty-seven healthy adults (19 women and eight men; mean age: 23±6.68years) and 27 TMD patients (20 women and seven men; mean age: 24±5.89years) voluntarily participated in the experiment. sEMG data were recorded from the right and left masseter muscles (RM and LM) and the right and left anterior temporalis muscles (RT and LT) as the participants performed tests of chewing (CHW) and maximal clenching effort (MCE). Frequency domain analysis of the sEMG signal was used to analyze differences between TMD patients and healthy subjects in relation to the Power Spectral Density Function (PSDF). The analysis focused on the median frequency (MDF) of the sEMG signal and PSDF frequency bands after the EMG spectrum was divided into twenty-five frequency band of 20Hz each. The Mann-Whitney test was used to compare MDF between TMD patients and healthy subjects and the frequency bands were analyzed using three-way ANOVA with three factors: frequency band, muscle and group. The results of the analysis confirmed that the median frequency values in TMD patients were significantly higher (p<0.05) than those recorded for healthy subjects in the two experimental conditions (MCE and CHW), for all of the muscles assessed (RM, LM, RT and LT). In addition, frequency content between 20 and 100Hz of the normalized PSDF range was significantly lower (p<0.05) in TMD patients than in healthy. This study contributes to quantitatively identify TMD dysfunctions, by non-invasive sEMGs; this assessment is clinically important and still lacking nowadays.

ANALYSIS OF TREMOR ACTIVITY OF ANTAGONIST MUSCLES IN ESSENTIAL TREMOR AND PARKINSON’S DISEASES

OBJECTIVE: Essential tremor (ET) is commonly difficult to distinguish clinically from Parkinson’s disease (PD), that’s why the research of electrophysiological profile of tremor in these diseases is of current interest. PURPOSE OF STUDY: to analyze and compare the specifics of tremor in antagonist muscles in patients with ET and PD using cross-spectral electromyographic analysis. METHODS: Sixty two (62) patients with PD and 35 patients with ET underwent electrophysiological examination (accelerometry and EMG) to evaluate the options of rest and postural tremor. We pointed out a subgroup of PD patients with essential-like phenotype of tremor (23 patients). Results: We revealed differences between the groups in following outcomes: muscle tremor pattern (phase relation) in rest, total power in 1-30 Hz frequency range, amount of harmonic peaks in the flexor carpi ulnaris EMG spectrum in postural tremor, level of EMG-EMG coherence and visual detection of muscle burst activity in 8-12 Hz frequency range. CONCLUSION. The above mentioned outcomes are promising for further investigation as potential differential markers of ET and PD.

Simulation of surface EMG for the analysis of muscle activity during whole body vibratory stimulation

This study aims to reproduce the effect of motor-unit synchronization on surface EMG recordings during vibratory stimulation to highlight vibration evoked muscle activity. The authors intended to evaluate, through numerical simulations, the changes in surface EMG spectrum in muscles undergoing whole body vibration stimulation. In some specific bands, in fact, vibration induced motion artifacts are also typically present.In addition, authors meant to compare the simulated EMGs with respect to real recordings in order to discriminate the effect of synchronization of motor units discharges with vibration frequencies from motion artifacts.Computations were performed using a model derived from previous studies and modified to consider the effect of vibratory stimulus, the motor unit synchronization and the endplates-electrodes relative position on the EMG signal.Results revealed that, in particular conditions, synchronization of MUs’ discharge generates visible peaks at stimulation frequency and its harmonics. However, only a part of the total power of surface EMGs might be enclosed within artifacts related bands (±1Hz centered at the stimulation frequency and its superior harmonics) even in case of strong synchronization of motor units discharges with the vibratory stimulus.

Identification of common synaptic inputs to motor neurons from the rectified electromyogram

Oscillatory common inputs of cortical or peripheral origin can be identified from the motor neuron output with coherence analysis. Linear transmission is possible despite the motor neuron non-linearity because the same input is sent commonly to several neurons. Because of the linear transmission, common input components to motor neurons can be investigated from the surface EMG, for example by EEG-EMG or EMG-EMG coherence. In these studies, there is an open debate on the utility and appropriateness of EMG rectification. The present study addresses this issue using an analytical, simulation and experimental approach. The main novel theoretical contribution that we report is that the spectra of both the rectified and the raw EMG contain input spectral components to motor neurons. However, they differ by the contribution of amplitude cancellation which influences the rectified EMG spectrum when extracting common oscillatory inputs. Therefore, the degree of amplitude cancellation has an impact on the effectiveness of EMG rectification in extracting input spectral peaks. The theoretical predictions were exactly confirmed by realistic simulations of a pool of motor neurons innervating a muscle in a cylindrical volume conductor of EMG generation and by experiments conducted on the first dorsal interosseous and the abductor pollicis brevis muscles of seven healthy subjects during pinching. It was concluded that when the contraction level is relatively low, EMG rectification may be preferable for identifying common inputs to motor neurons, especially when the energy of the action potentials in the low frequency range is low. Nonetheless, different levels of cancellation across conditions influence the relative estimates of the degree of linear transmission of oscillatory inputs to motor neurons when using the rectified EMG.

The resonant component of human physiological hand tremor is altered by slow voluntary movements

Limb resonance imparts a characteristic spectrum to hand tremor. Movement will alter the resonance. We have examined the consequences of this change. Rectified forearm extensor muscle EMG and physiological hand tremor were recorded. In postural conditions the EMG spectrum is relatively flat whereas the acceleration spectrum is sharply peaked. Consequently, the gain between EMG and acceleration is maximal at the frequency where the tremor is largest (∼8 Hz). The shape of the gain curve implies mechanical resonance. Substantial alterations in posture do not significantly change the characteristics of the tremor or the shape or size of the gain curve. By contrast, slow or moderately paced voluntary wrist flexion–extension movements dramatically increase the hand tremor size and lower its peak frequency. These changes in size and frequency of the tremor cannot be attributed to changes in the EMG. Instead they reflect a very large change in the size and shape of the gain curve relating EMG to acceleration. The gain becomes larger and the peak moves to a lower frequency (∼6 Hz). We suggest that a movement-related (thixotropic) alteration in resonant properties of the wrist provides a simple explanation for these changes. The mechanism is illustrated by a model. Our new findings confirm that resonance plays a major role in wrist tremor. We also demonstrate that muscles operate very differently under postural and dynamic conditions. The different coupling between EMG and movement in posture and when moving must pose a considerable challenge for neural predictive control of skeletal muscles.

Accurate Real-Time Feedback of Surface EMG During fMRI

Real-time acquisition of EMG during functional MRI (fMRI) provides a novel method of controlling motor experiments in the scanner using feedback of EMG. Because of the redundancy in the human muscle system, this is not possible from recordings of joint torque and kinematics alone, because these provide no information about individual muscle activation. This is particularly critical during brain imaging because brain activations are not only related to joint torques and kinematics but are also related to individual muscle activation. However, EMG collected during imaging is corrupted by large artifacts induced by the varying magnetic fields and radio frequency (RF) pulses in the scanner. Methods proposed in literature for artifact removal are complex, computationally expensive, and difficult to implement for real-time noise removal. We describe an acquisition system and algorithm that enables real-time acquisition for the first time. The algorithm removes particular frequencies from the EMG spectrum in which the noise is concentrated. Although this decreases the power content of the EMG, this method provides excellent estimates of EMG with good resolution. Comparisons show that the cleaned EMG obtained with the algorithm is, like actual EMG, very well correlated with joint torque and can thus be used for real-time visual feedback during functional studies.

Muscular effort in multiple sclerosis patients during powered wheelchair manoeuvres

Background. This study applied EMG analysis methods to identify muscle group activity profiles and potential overload risks in powered wheelchair use. Methods. We quantified muscle effort and fatigue using EMG analysis methods during powered wheelchair manoeuvres by 10 multiple sclerosis patients. Video recordings of the different sub-tasks were related to information on surface EMG amplitude (rectified EMG) and spectral information (Median frequency) from M. trapezius, M. deltoideus (pars medius), M. deltoideus (pars anterior), M. pectoralis, M. biceps, M. triceps, wrist extensors and flexors, using Joint Analysis of EMG Spectrum and Amplitude (JASA analysis). Findings. Task durations and subjective data indicated that tasks requiring finer motor control took longer and were perceived as more difficult. Kinesiological functions of all muscle groups identified forward steering to be associated with activation of M. deltoideus (pars anterior), M. pectoralis, M. trapezius and M. deltoideus (pars medius); backwards steering with predominant activation of M. deltoideus (pars medius), M. biceps brachii and wrist flexors; left steering with maximal activation of M. biceps and wrist flexors, and right steering with maximal activation of M. triceps and wrist extensors. These profiles were confirmed in analysis of the functional tasks. JASA analysis documented muscle fatigue in the wrist extensors, whereas increased activation was found in M. trapezius, M. deltoideus (pars anterior) and wrist flexors. Interpretation. EMG based kinesiological analysis gives insight in muscle activity and fatigue during powered wheelchair manoeuvres.

Evolution in impedance at the electrode-skin interface of two types of surface EMG electrodes during long-term recordings

The evolution in impedance at the electrode-skin interface of Beckman and Red Dot electrodes was assessed during long-term recordings. Impedance was measured between each pair of electrodes, arranged in a bipolar configuration on tibialis anterior ( n=13). A waveform constructed of sinusoids of known frequencies, evenly distributed on a log scale from 1–16,384 Hz, was applied through the electrodes, and the result recorded by a DAQ system. SEMG signals were recorded at 1000 Hz during isometric dorsiflexion contractions of 30 s, performed every 15 min for 2 h. Impedance data were acquired at 65,536 Hz immediately before and after SEMG recordings. Large individual differences in impedance levels were observed at low frequencies. At high frequencies, impedance values depended only on the electrode type. Impedance decreased steadily with time for Beckman electrodes ( p < 0.05), but did not decrease significantly for Red Dot electrodes. The magnitude of the reduction over time varied widely between individuals, and was related to the initial impedance values. The impedance-bandwidth product remained constant for each electrode type (95% confidence intervals 146.2–148.2 and 126.1–127.8 for Beckman and Red Dot electrodes respectively). When skin impedance is electrically modelled with a simple network containing a resistor and a capacitor, the capacitance varies with the properties of the electrode used, whereas resistance is dependent on the subject. Furthermore, the EMG spectrum is unaffected by impedance provided skin preparation is sufficient to reduce the impedance below 55 kΩ.

Methodologies for evaluating electromyographic field data in ergonomics

Surface electromyography (SEMG) is an important tool for work load assessment in ergonomics. Several different approaches using amplitude as well as frequency parameters give fruitful information depending on question at issue in the laboratory as well as in field studies. One basic factor determining the choice of analysis method is whether the SEMG is interpreted as an indicator of forces/torques or pure muscular activation. Two methods for occupational SEMG data reduction representing two different approaches to SEMG applications in ergonomics, Exposure Variation Analysis (EVA), and Joint Analysis of EMG Spectrum and Amplitude (JASA), applied on the same SEMG recording from three muscles during urology surgeon work, have been compared. The EVA method categorised the three muscle recordings as too static with no EMG gaps while the JASA method identifies fatigue in two of the three recordings. The practical relevance of these findings is discussed.

Surface EMG mapping of the human trapezius muscle: the topography of monopolar and bipolar surface EMG amplitude and spectrum parameters at varied forces and in fatigue

Objectives: To investigate the factors affecting the topography of trapezius muscle EMG, multichannel recordings were made at different forces of isometric shoulder elevation and during fatiguing exercise. Methods: Twenty-eight channels of monopolar EMG were recorded from an array of 4×7 electrodes placed on the upper trapezius muscle. From the monopolar EMG and the bipolar derivations the root mean square (RMS monopolar, RMS bipolar) and power spectrum median frequency (MF monopolar, MF bipolar) were calculated. Results: The maximum RMS monopolar was located above the middle part of the trapezius muscle, where a minimum was found for RMS bipolar. The cranial-caudal RMS distribution shifted upwards when the force was increased from 50 to 100% MVC and during fatigue. MF bipolar showed a peak above the endplate region, where the MF monopolar was low. During fatigue the normalized MF slope was independent of the cranial-caudal electrode position, but MF monopolar decreased most strongly at positions above the endplate region, where MF bipolar decreased less. Conclusions: While the changes in MF reflected metabolic properties and volume conduction phenomena in the muscle, changes in RMS reflected a compensation for the fatigue processes within the muscle. The RMS changes in fatigue can be explained by the direction of the fibres involved in shoulder elevation.

Eliminating ultrasonic interference from respiratory muscle EMG

Fine wire recordings of the respiratory muscle electromyogram are often employed to represent muscle activity, and recently ultrasound-sonomicrometry has become a common method of measuring length of respiratory muscles in both acute and chronic preparations. Although recording both EMG and sonomicrometry simultaneously has become standard practice, there has not been any consideration of the potential confounding influence of ultrasound noise upon the recorded EMG spectrum. Activation of the sonomicrometry-ultrasound tranducer introduces a high frequency, high amplitude voltage pulse plus harmonics, which can contaminate the EMG spectrum directly, as well as through aliasing when EMG is sampled directly digitally. We describe the use of a new, combined, wing stabilized sonomicrometry- and EMG measurement transducer to characterize exactly the influence of ultrasound upon the crural diaphragm EMG spectrum, and the development of digital filtering techniques which effectively eliminate the ultrasound interference. Two alternative methods of avoiding ultrasound-EMG interference are also considered. The isolation and elimination of ultrasound-sonomicrometry signal interference may be important in studies where EMG and length are measured together.

Comparison of different estimators of electromyographic spectral shifts during work when applied on short test contractions

EMG was recorded during short test contractions performed during occupational work. Mean power frequency (MPF) and median frequency (MF), calculated from EMG spectra, and zero crossing rate (ZC) of the EMG signal were compared as estimators of local muscular fatigue. The results show that there is a systematic difference between the three estimates. The difference can be explained by dividing the effect of muscle fatigue on EMG spectra into a motor unit action potential velocity effect and a firing statistics effect. Furthermore, it is shown that the phenomenon of increasing estimators of EMG spectrum shift is unlikely to be caused by motor unit action potential velocity increase. Successive recruitment of new motor units is suggested as a feasible explanation.

Autoregressive modeling of surface EMG and its spectrum with application to fatigue

The following is an investigation of the ability of the autoregressive (AR) model to describe the spectrum of the processes underlying the recorded surface EMG. Surface EMG (SEMG) spectrum is influenced by two major factors; one attributed to the motor units (MU) firing rate and the second, the higher frequency one, to the morphology of the action potentials (AP) traveling along the muscle fiber. In the present paper, SEMG measurements were carried out on the biceps brachii muscle with fixed surface electrodes arrangement and isotonic conditions. Sufficient averaging of 0.5s segments enabled the identification of the low-frequency peak related to the firing rates of the MUs. An AR model was calculated for the signal, since such a model is appropriate for signals with a peaky spectrum. The AR coefficients, the reflection coefficients, and the poles of the AR model were plotted to track their time dependence. Several criteria were used to choose the model's order. Between 2–7 parameters were needed, according to some criteria, for one segment of data which fitted the bell-shaped spectrum of the APs. However, close to 30 parameters were needed to track the low-frequency component of the MUs firing rate, when averaging the reconstructed spectra for 100 segments. (This order can be reduced using special methods.) With local muscular fatigue, the first AR parameter a 1, the first reflection coefficient k 1, and the normalized energy of the model error V p, all decline with time. There is then a decline of the similarity of the signal to white noise and it tends to a lower frequency band as observed in the past. During central fatigue—induced by severe sleep deprivation—no consistent changes were observed in the SEMG spectrum or the parameters of its AR model.