Mean frequency and signal amplitude of the surface EMG of the quadriceps muscles increase with increasing torque--a study using the continuous wavelet transform

Integrative approach to pedobarography and pelvis-trunk motion for knee osteoarthritis detection and exploration of non-radiographic rehabilitation monitoring

Background

Osteoarthritis (OA) is a highly prevalent global musculoskeletal disorder, and knee OA (KOA) accounts for four-fifths of the cases worldwide. It is a degenerative disorder that greatly affects the quality of life. Thus, it is managed through different methods, such as weight loss, physical therapy, and knee arthroplasty. Physical therapy aims to strengthen the knee periarticular muscles to improve joint stability.

Methods

Pedobarographic data and pelvis and trunk motion of 56 adults are recorded. Among them, 28 subjects were healthy, and 28 subjects were suffering from varying degrees of KOA. Age, sex, BMI, and the recorded variables are used together to identify subjects with KOA using machine learning (ML) models, namely, logistic regression, SVM, decision tree, and random forest. Surface electromyography (sEMG) signals are also recorded bilaterally from two muscles, the rectus femoris and biceps femoris caput longus, bilaterally during various activities for two healthy and six KOA subjects. Cluster analysis is then performed using the principal components obtained from time-series features, frequency features, and time-frequency features.

Results

KOA is successfully identified using the pedobarographic data and the pelvis and trunk motion with the highest accuracy and sensitivity of 89.3% and 85.7%, respectively, using a decision tree classifier. In addition, sEMG data have been successfully used to cluster healthy subjects from KOA subjects, with wavelet analysis features providing the best performance for the standing activity under different conditions.

Conclusion

KOA is detected using gait variables not directly related to the knee, such as pedobarographic measurements and pelvis and trunk motion captured by pedobarography mats and wearable sensors, respectively. KOA subjects are also distinguished from healthy individuals through clustering analysis using sEMG data from knee periarticular muscles during walking and standing. Gait data and sEMG complement each other, aiding in KOA identification and rehabilitation monitoring. It is important because wearable sensors simplify data collection, require minimal sample preparation, and offer a non-radiographic, safe method suitable for both laboratory and real-world scenarios. The decision tree classifier, trained with stratified k-fold cross validation (SKCV) data, is observed to be the best for KOA identification using gait data.

Combined effect of contraction type and intensity on corticomuscular coherence during isokinetic plantar flexions

During isometric contractions, corticomuscular coherence (CMC) may be modulated along with the contraction intensity. Furthermore, CMC may also vary between contraction types due to the contribution of spinal inhibitory mechanisms. However, the interaction between the effect of the contraction intensity and of the contraction type on CMC remains hitherto unknown. Therefore, CMC and spinal excitability modulations were compared during submaximal isometric, shortening and lengthening contractions of plantar flexor muscles at 25, 50, and 70% of the maximal soleus (SOL) EMG activity. CMC was computed in the time-frequency domain between the Cz EEG electrode signal and the SOL or medial gastrocnemius (MG) EMG signals. The results indicated that beta-band CMC was decreased in the SOL only between 25 and 50-70% contractions for both isometric and anisometric contractions, but remained similar for all contraction intensities in the MG. Spinal excitability was similar for all contraction intensities in both muscles. Meanwhile a divergence of the EEG and the EMG signals mean frequency was observed only in the SOL and only between 25 and 50-70% contractions, independently from the contraction type. Collectively, these findings confirm an effect of the contraction intensity on beta-band CMC, although it was only measured in the SOL, between low-level and high-level contraction intensities. Furthermore, the current findings provide new evidence that the observed modulations of beta-band CMC with the contraction intensity does not depend on the contraction type or on spinal excitability variations.

Relationship between EMG features and force in orbicularis oris muscle

BACKGROUND

Lip incompetence resulting from mouth breathing is a common clinical manifestation, while there are no definite indicators of amplitude and intensity of muscle functional training in clinical practice, which leads to unsatisfactory training results.

OBJECTIVE

The aim was to quantify the relationship between electromyography (EMG) and force in orbicularis oris muscle, so that the indicators of muscle functional training can be evaluated using EMG signals, so as to improve the training effects.

METHODS

The EMG and the force signals of orbicularis oris muscle from 0% to 100% MVC within 5 s in twelve healthy subjects (six males and six females; age, 25 ± 2 years; mass, 60 ± 15 kg) were recorded simultaneously for three trials. Four EMG features consisting of RMS, WAMP, SampEn and FuzzyEn were analyzed. The regression analyses were performed using first-order and third-order polynomial model.

RESULTS

There were high correlations between the four EMG features and muscle force with the two models. The third-order model yielded a higher coefficient of determination (R2) than the linear model (p< 0.001) and the result of FuzzyEn (R2: 0.884 ± 0.059) was the highest in the four features.

CONCLUSION

The third-order model with FuzzyEn of EMG signals may be used to guide the muscle functional training.

Sex differences in kinematics and quadriceps activity for fast isokinetic knee extension

BACKGROUND: The quantitative recruitment of motor units depends on specific demands, including movement velocity. DNA microarrays differ according to sex, and these sex-related differences affect the fiber type composition. OBJECTIVE: The aim of this study is to demonstrate inter-sex differences in the isokinetic parameters, isokinetic phases, and muscle activities and to investigate the correlation between muscle activity and isokinetic data. METHODS: A total of 41 healthy adults (20 male, 21 female) performed concentric knee extension at angular velocities of 60∘/s, 180∘/s, and 240∘/s. The outcome measures consisted of the isokinetic peak moment (PM), normalized PM (PM/BW), total work, and power, alongside the acceleration, iso-speed and deceleration, sub-phases. Muscle activity was recorded from the rectus femoris, vastus lateralis, and vastus medialis using surface EMG. RESULTS: There were significant two-factor main effect and interaction between sex and angular velocity on the power of knee extension and isokinetic phase (p< 0.05). As the velocity increased, the increase in power of males was greater than that of females. In contrast, with the increase in velocity, PM, PM/BW, and total work decreased, but no significant interaction was observed between velocity and sex. At high velocity, males showed higher acceleration ability than females. CONCLUSION: The sex-dependent responses to velocity were more affected by differences in total movement time than force production. Fast isokinetic exercise should consider the acceleration ability rather than the ability to produce force.

Electromyography Signal Analysis and Classification using Time-Frequency Representations and Deep Learning

Analysis and classification of electromyography (EMG) signals are crucial for rehabilitation and motor control. This study investigates electromyogram (EMG) time-frequency representations and then creates conventional and deep learning models for EMG signal classification. Firstly, a dataset of single-channel surface EMG signals has been recorded for four subjects to differentiate between forearm flexion and extension. Then, different time-frequency EMG representations have been used to build conventional and deep learning models for EMG classification. We compared the performance of pre-trained convolutional neural network models, namely GoogLeNet, SqueezeNet and AlexNet, and achieved accuracies of 92.71%, 90.63% and 87.5%, respectively. Also, data augmentation techniques on the levels of raw EMG signals and their time- frequency representations helped improve the accuracy of GoogLeNet to 96.88%. Furthermore, our approach demonstrated superior performance on another publicly available 10-class EMG dataset, and also using traditional classifiers trained on hand-crafted features.

Laser-generated focused ultrasound transducer using a perforated photoacoustic lens for tissue characterization

We demonstrate a laser-generated focused ultrasound (LGFU) transducer using a perforated-photoacoustic (PA) lens and a piezoelectric probe hydrophone suitable for high-frequency ultrasound tissue characterization. The perforated-PA lens employed a centrally located hydrophone to achieve a maximum directional response at 0° from the axial direction of the lens. Under pulsed laser irradiation, the lens produced LGFU pulses with a frequency bandwidth of 6-30 MHz and high-peak pressure amplitudes of up to 46.5 MPa at a 70-µm lateral focal width. Since the hydrophone capable of covering the transmitter frequency range (∼20 MHz) was integrated with the lens, this hybrid transducer differentiated tissue elasticity by generating and detecting high-frequency ultrasound signals. Backscattered (BS) waves from excised tissues (bone, skin, muscle, and fat) were measured and also confirmed by laser-flash shadowgraphy. We characterized the LGFU-BS signals in terms of mean frequency and spectral energy in the frequency domain, enabling to clearly differentiate tissue types. Tissue characterization was also performed with respect to the LGFU penetration depth (from the surface, 1-, and 2-mm depth). Despite acoustic attenuation over the penetration depth, LGFU-BS characterization shows consistent results that can differentiate the elastic properties of tissues. We expect that the proposed transducer can be utilized for other tissue types and also for non-destructive evaluation based on the elasticity of unknown materials.

Development of Sign Language Motion Recognition System for Hearing-Impaired People Using Electromyography Signal

Sign languages are developed around the world for hearing-impaired people to communicate with others who understand them. Different grammar and alphabets limit the usage of sign languages between different sign language users. Furthermore, training is required for hearing-intact people to communicate with them. Therefore, in this paper, a real-time motion recognition system based on an electromyography signal is proposed for recognizing actual American Sign Language (ASL) hand motions for helping hearing-impaired people communicate with others and training normal people to understand the sign languages. A bilinear model is applied to deal with the on electromyography (EMG) data for decreasing the individual difference among different people. A long short-term memory neural network is used in this paper as the classifier. Twenty sign language motions in the ASL library are selected for recognition in order to increase the practicability of the system. The results indicate that this system can recognize these twenty motions with high accuracy among twenty participants. Therefore, this system has the potential to be widely applied to help hearing-impaired people for daily communication and normal people to understand the sign languages.

Automated Channel Selection in High-Density sEMG for Improved Force Estimation

Accurate and real-time estimation of force from surface electromyogram (EMG) signals enables a variety of applications. We developed and validated new approaches for selecting subsets of high-density (HD) EMG channels for improved and lower-dimensionality force estimation. First, a large dataset was recorded from a number of participants performing isometric contractions in different postures, while simultaneously recording HD-EMG channels and ground-truth force. The EMG signals were acquired from three linear surface electrode arrays, each with eight monopolar channels, and were placed on the long head and short head of the biceps brachii and brachioradialis. After data collection and pre-processing, fast orthogonal search (FOS) was employed for force estimation. To select a subset of channels, principal component analysis (PCA) in the frequency domain and a novel index called the power-correlation ratio (PCR), which maximizes the spectral power while minimizing similarity to other channels, were used. These approaches were compared to channel selection using time-domain PCA. We selected one, two, and three channels per muscle from the original seven differential channels to reduce the redundancy and correlation in the dataset. In the best case, we achieved an approximate improvement of 30% for force estimation while reducing the dimensionality by 57% for a subset of three channels.

Muscle function assessed by the non-invasive method acoustic myography (AMG) in a Danish group of healthy adults

Acoustic myography (AMG) is a non-invasive method to assess muscle function during daily activities. AMG has great scope for assessment of musculoskeletal problems. The aim of this study was to create an AMG data set for general clinical use and relate these findings to age and gender. 10 healthy subjects (5 men/5 women), in each decade from 20 to 69 years of age (n = 50), were assessed. Their clinical health was tested. AMG measurements were carried out on muscles involved in defined movements of the upper and lower extremities. Muscle performance was measured using efficiency (E-score) and fibre recruitment (temporal (T-score) and spatial (S-score) summation). AMG-measurements showed good reproducibility. In each age group, it was found that for all those daily living skills measured, there was no gender difference. A walking and stair climbing test revealed that both legs are used equally and in a balanced way in healthy subjects. Moreover, there was no change in this function with increasing age up to 69 years. However, a cycling test with loading revealed that in elderly subjects the coordination of muscle use is impaired compared to that of the younger adults. Finally, a flexion test of the arm revealed an age-related decrease in the efficiency/coordination of m.Biceps alone, and a keyboard writing test suggests no effect on m.Trapezius. This reference data set now illustrates the reproducibility and ease of use of acoustic myography in the clinic and provides a means of assessing individuals with musculoskeletal problems.

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Acoustic myography is a non-invasive, real-time and repeatable tool for assessing musculoskeletal problems in the clinic.

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A walking and stair climbing test revealed both legs to be used in a balanced way in healthy subjects, with no age effect.

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A cycling test with loading showed that coordination of muscle use was impaired with increasing age.

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A flexion test of the arm revealed an age-related decrease in the efficiency/coordination of m.Biceps alone.

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This reference data set illustrates the ease of use of this technique in the clinic for musculoskeletal problems.

EMG median frequency shifts without change in muscle oxygenation following novel locomotor training in individuals with incomplete spinal cord injury

Objectives: To examine the effect of muscle fiber recruitment patterns on muscle oxygen utilization during treadmill walking in a group of individuals who have incomplete spinal cord injury.Methods: 5 participants with motor incomplete spinal cord injury (Age; 42.2 ± 18.8 years, Male; n = 4) completed an over ground locomotor training program. Muscle utilization/oxygenation and activation of the medial gastrocnemius were measured by near infrared spectroscopy and surface electromyography pre- and post-over ground locomotor training during two separate treadmill walking bouts at self-selected speeds. Outcomes were changes in deoxygenation hemoglobin/myoglobin concentrations, and the change in median power of the power spectrum of the electromyography after training.Results: A significant increase in median power of the power spectrum of the electromyography signal was observed during both bouts of treadmill walking, 6-minute walking bout and longer fatiguing bout (49% p = 0.047 and 48% p = 0.035, respectively) post-over ground locomotor training. There was no significant change in muscle utilization/oxygenation post-over ground locomotor training. There was no significant effect of median power of the power spectrum on deoxygenation hemoglobin/myoglobin during either of the walking bouts.Conclusions: The main finding of the current study was that median power of the power spectrum significantly increased following 12 weeks of over ground locomotor training, with no significant change in deoxygenation hemoglobin/myoglobin. The recruitment of more and/or larger motor units was seen in conjunction with no changes in muscle oxygen utilization for the same walking task.Implications for RehabilitationThe reduction of skeletal muscle innervation in Spinal Cord Injury may adversely affect the orderly recruitment of motor units, which could in turn blunt the oxidative metabolic response during physical activity.Over-ground locomotor could be a useful tool in the rehabilitative process following an incomplete spinal cord injury.

Current Trends and Confounding Factors in Myoelectric Control: Limb Position and Contraction Intensity

This manuscript presents a hybrid study of a comprehensive review and a systematic(research) analysis. Myoelectric control is the cornerstone ofmany assistive technologies used in clinicalpractice, such as prosthetics and orthoses, and human-computer interaction, such as virtual reality control.Although the classification accuracy of such devices exceeds 90% in a controlled laboratory setting,myoelectric devices still face challenges in robustness to variability of daily living conditions.The intrinsic physiological mechanisms limiting practical implementations of myoelectric deviceswere explored: the limb position effect and the contraction intensity effect. The degradationof electromyography (EMG) pattern recognition in the presence of these factors was demonstratedon six datasets, where classification performance was 13% and 20% lower than the controlledsetting for the limb position and contraction intensity effect, respectively. The experimental designsof limb position and contraction intensity literature were surveyed. Current state-of-the-art trainingstrategies and robust algorithms for both effects were compiled and presented. Recommendationsfor future limb position effect studies include: the collection protocol providing exemplars of at least 6positions (four limb positions and three forearm orientations), three-dimensional space experimentaldesigns, transfer learning approaches, and multi-modal sensor configurations. Recommendationsfor future contraction intensity effect studies include: the collection of dynamic contractions, nonlinearcomplexity features, and proportional control.

Muscle assessment using multi-frequency bioimpedance in a healthy Danish population aged 20-69 years: a powerful non-invasive tool in sports and in the clinic

The condition of active muscles determines an individual's ability to carry out daily activities and has implications for an athlete's performance. Multi-frequency bioimpedance (mfBIA) is a non-invasive, well-known, validated, and much used method to assess muscle condition. However, it is rarely used to its full potential. Our aim was to apply mfBIA fully in the assessment of an adult healthy population, to compare muscle condition in different functional rested muscle groups, with age, and between men and women, and establish a control data set. Fifty healthy subjects (25 men/25 women) aged 20-69 years, participated. mfBIA measurements at a frequency range of 4-1000 kHz were taken from muscles of the lower and the upper extremities, the upper back, and the hand. Data were analyzed using ImpediMed software, giving Impedance, Resistance, Reactance, Phase Angle, Center Frequency, external and internal Resistance, and Membrane Capacitance. Differences between means were tested for statistical significance. A P value >0.05 was considered nonsignificant. While no difference in the mfBIA parameters was seen with age, a highly significant gender difference was seen. At rest, women's muscles cf men's showed a significantly higher center frequency and intra- and extra-cellular resistance, while the membrane capacitance was lower. A set of values for mfBIA parameters for healthy adult individuals are given for some of the main muscles which are frequently part of muscle assessment. The documented gender difference in muscle condition at rest has important implications in work situations, during physical rehabilitation and when training for competitive sports.

Protective myoelectric activity at performing upper limb neurodynamic test 1 in breast cancer survivors. A cross-sectional observational study

Myoelectric activity and range of motion during ULNT1 were recorded in 62 breast cancer (BC) survivors who had axillary lymph node dissection (n = 30) or sentinel lymph node biopsy (n = 32) within the previous 18 months, and 63 age-matched healthy women. BC survivors' symptoms were reproduced by ULNT1 and exhibited greater myoelectric activity in the biceps brachii than healthy women (MD (95% CI): 21,26 (10,83-31,70)). No differences between the axillary lymph node dissection and sentinel lymph node biopsy groups (MD (95% CI): 8,47 (-7,84-24,79)) were found. Myoelectric activity in the triceps brachii was greater in the sentinel lymph node biopsy group (MD (95% CI): 2,70 (-2,06-7,60)). BC survivors exhibited less shoulder and elbow range of motion during ULNT1 than healthy women. Increased upper limb nerve mechanosensitivity in BC survivors was associated with a greater protective muscle response during ULNT1.

A wavelet based time frequency analysis of electromyograms to group steps of runners into clusters that contain similar muscle activation patterns

PURPOSE

To wavelet transform the electromyograms of the vastii muscles and generate wavelet intensity patterns (WIP) of runners. Test the hypotheses: 1) The WIP of the vastus medialis (VM) and vastus lateralis (VL) of one step are more similar than the WIPs of these two muscles, offset by one step. 2) The WIPs within one muscle differ by having maximal intensities in specific frequency bands and these intensities are not always occurring at the same time after heel strike. 3) The WIPs that were recorded form one muscle for all steps while running can be grouped into clusters with similar WIPs. It is expected that clusters might have distinctly different, cluster specific mean WIPs.

METHODS

The EMG of the vastii muscles from at least 1000 steps from twelve runners were recorded using a bipolar current amplifier and yielded WIPs. Based on the weights obtained after a principal component analysis the dissimilarities (1-correlation) between the WIPs were computed. The dissimilarities were submitted to a hierarchical cluster analysis to search for groups of steps with similar WIPs. The clusters formed by random surrogate WIPs were used to determine whether the groups were likely to be created in a non-random manner.

RESULTS

The steps were grouped in clusters showing similar WIPs. The grouping was based on the frequency bands and their timing showing that they represented defining parts of the WIPs. The correlations between the WIPs of the vastii muscles that were recorded during the same step were higher than the correlations of WPIs that were recorded during consecutive steps, indicating the non-randomness of the WIPs.

CONCLUSIONS

The spectral power of EMGs while running varies during the stance phase in time and frequency, therefore a time averaged power spectrum cannot reflect the timing of events that occur while running. It seems likely that there might be a set of predefined patterns that are used upon demand to stabilize the movement.

Does Heel Height Cause Imbalance during Sit-to-Stand Task: Surface EMG Perspective

The purpose of this study was to determine whether electromyography (EMG) muscle activities around the knee differ during sit-to-stand (STS) and returning task for females wearing shoes with different heel heights. Sixteen healthy young women (age = 25.2 ± 3.9 years, body mass index = 20.8 ± 2.7 kg/m²) participated in this study. Electromyography signals were recorded from the two muscles, vastus medialis (VM) and vastus lateralis (VL) that involve in the extension of knee. The participants wore shoes with five different heights, including 4, 6, 8, 10, and 12 cm. Surface electromyography (sEMG) data were acquired during STS and stand-to-sit-returning (STSR) tasks. The data was filtered using a fourth order Butterworth (band pass) filter of 20–450 Hz frequency range. For each heel height, we extracted median frequency (MDF) and root mean square (RMS) features to measure sEMG activities between VM and VL muscles. The experimental results (based on MDF and RMS-values) indicated that there is imbalance between vasti muscles for more elevated heels. The results are also quantified with statistical measures. The study findings suggest that there would be an increased likelihood of knee imbalance and fatigue with regular usage of high heel shoes (HHS) in women.

ESTIMATING MUSCLE FORCES AND KNEE JOINT TORQUE USING SURFACE ELECTROMYOGRAPHY: A MUSCULOSKELETAL BIOMECHANICAL MODEL

Surface electromyography (sEMG) is a useful tool for revealing the underlying musculoskeletal dynamic properties in the human body movement. In this paper, a musculoskeletal biomechanical model which relates the sEMG and knee joint torque is proposed. First, the dynamic model relating sEMG to skeletal muscle activation considering frequency and amplitude is built. Second, a muscle contraction model based on sliding-filament theory is developed to reflect the physiological structure and micro mechanical properties of the muscle. The muscle force and displacement vectors are determined and the transformation from muscle force to knee joint moment is realized, and finally a genetic algorithm-based calibration method for the Newton–Euler dynamics and overall musculoskeletal biomechanical model is put forward. Following the model calibration, the flexion/extension (FE) knee joint torque of eight subjects under different walking speeds was predicted. Results show that the forward biomechanical model can capture the general shape and timing of the joint torque, with normalized mean residual error (NMRE) of [Formula: see text]10.01%, normalized root mean square error (NRMSE) of [Formula: see text]12.39% and cross-correlation coefficient of [Formula: see text]0.926. The musculoskeletal biomechanical model proposed and validated in this work could facilitate the study of neural control and how muscle forces generate and contribute to the knee joint torque during human movement.

EMG-Torque Relation in Chronic Stroke: A Novel EMG Complexity Representation With a Linear Electrode Array

This study examines the electromyogram (EMG)-torque relation for chronic stroke survivors using a novel EMG complexity representation. Ten stroke subjects performed a series of submaximal isometric elbow flexion tasks using their affected and contralateral arms, respectively, while a 20-channel linear electrode array was used to record surface EMG from the biceps brachii muscles. The sample entropy (SampEn) of surface EMG signals was calculated with both global and local tolerance schemes. A regression analysis was performed between SampEn of each channel's surface EMG and elbow flexion torque. It was found that a linear regression can be used to well describe the relation between surface EMG SampEn and the torque. Each channel's root mean square (RMS) amplitude of surface EMG signal in the different torque level was computed to determine the channel with the highest EMG amplitude. The slope of the regression (observed from the channel with the highest EMG amplitude) was smaller on the impaired side than on the nonimpaired side in 8 of the 10 subjects, regardless of the tolerance scheme (global or local) and the range of torques (full or matched range) used for comparison. The surface EMG signals from the channels above the estimated muscle innervation zones demonstrated significantly lower levels of complexity compared with other channels between innervation zones and muscle tendons. The study provides a novel point of view of the EMG-torque relation in the complexity domain, and reveals its alterations post stroke, which are associated with complex neural and muscular changes post stroke. The slope difference between channels with regard to innervation zones also confirms the relevance of electrode position in surface EMG analysis.

The Assessment of Muscular Effort, Fatigue, and Physiological Adaptation Using EMG and Wavelet Analysis

Peroxisome proliferator-activated receptor gamma coactivator 1 alpha (PGC-1α) is a transcription factor co-activator that helps coordinate mitochondrial biogenesis within skeletal muscle following exercise. While evidence gleaned from submaximal exercise suggests that intracellular pathways associated with the activation of PGC-1α, as well as the expression of PGC-1α itself are activated to a greater extent following higher intensities of exercise, we have recently shown that this effect does not extend to supramaximal exercise, despite corresponding increases in muscle activation amplitude measured with electromyography (EMG). Spectral analyses of EMG data may provide a more in-depth assessment of changes in muscle electrophysiology occurring across different exercise intensities, and therefore the goal of the present study was to apply continuous wavelet transforms (CWTs) to our previous data to comprehensively evaluate: 1) differences in muscle electrophysiological properties at different exercise intensities (i.e. 73%, 100%, and 133% of peak aerobic power), and 2) muscular effort and fatigue across a single interval of exercise at each intensity, in an attempt to shed mechanistic insight into our previous observations that the increase in PGC-1α is dissociated from exercise intensity following supramaximal exercise. In general, the CWTs revealed that localized muscle fatigue was only greater than the 73% condition in the 133% exercise intensity condition, which directly matched the work rate results. Specifically, there were greater drop-offs in frequency, larger changes in burst power, as well as greater changes in burst area under this intensity, which were already observable during the first interval. As a whole, the results from the present study suggest that supramaximal exercise causes extreme localized muscular fatigue, and it is possible that the blunted PGC-1α effects observed in our previous study are the result of fatigue-associated increases in muscle acidosis. This should be explored in future research using further combinations of EMG and muscle biochemistry and histology.

Muscular fatigue detection using sEMG in dynamic contractions

In this work we have studied different indicators of muscle fatigue from the electrical signal produced by the muscles when contract (sEMG or EMG: surface electromyography): Mean Frequency of the power spectrum (MNF), Median Frequency (Fmed), Dimitrov Spectral Index (FInsm5), Root Mean Square (RMS), and Zerocrossing (ZC). The most reliable features are selected to develop a detection algorithm that estimates muscle fatigue. The approach used in the algorithm is probabilistic and is based on the technique of Gaussian Mixture Model (GMM). The system is divided into two stages: training and validation. During training, the algorithm learns the distribution of data regarding fatigue evolution; after that, the algorithm is validated with data that have not been used to train. Therefore, two experimental sessions have been performed with 6 healthy subjects for biceps.

The influence of electromyographic recording methods and the innervation zone on the mean power frequency-torque relationships

This study examined the effects of electromyographic (EMG) recording methods and innervation zone (IZ) on the mean power frequency (MPF)-torque relationships. Nine subjects performed isometric ramp muscle actions of the leg extensors from 5% to 100% of maximal voluntary contraction with an eight channel linear electrode array over the IZ of the vastus lateralis. The slopes were calculated from the log-transformed monopolar and bipolar EMG MPF-torque relationships for each channel and subject and 95% confidence intervals (CI) were constructed around the slopes for each relationship and the composite of the slopes. Twenty-two to 55% of the subjects exhibited 95% CIs that did not include a slope of zero for the monopolar EMG MPF-torque relationships while 25-75% of the subjects exhibited 95% CIs that did not include a slope of zero for the bipolar EMG MPF-torque relationships. The composite of the slopes from the EMG MPF-torque relationships were not significantly different from zero for any method or channel, however, the method and IZ location slightly influenced the number of significant slopes on a subject-by-subject basis. The log-transform model indicated that EMG MPF-torque patterns were nonlinear regardless of recording method or distance from the IZ.

The progression of muscle fatigue during exercise estimation with the aid of high-frequency component parameters derived from ensemble empirical mode decomposition

Muscle fatigue is often monitored via the median frequency derived from the surface electromyography (sEMG) power spectrum during isometric contractions. The power spectrum of sEMG shifting toward lower frequencies can be used to quantify the electromanifestation of muscle fatigue. The dynamic sEMG belongs to a nonstationary signal, which will be affected by the electrode moving, the shift of the muscle, and the change of innervation zone. The goal of this study is to find a more sensitive and stable method in order to sense the progression of muscle fatigue in the local muscle during exercise in healthy people. Five male and five female volunteers participated. Each subject was asked to run on a multifunctional pedaled elliptical trainer for about 30 min, twice a week, and was recorded a total of six times. Three decomposed methods, discrete wavelet transform (DWT), empirical mode decomposition (EMD), and ensemble EMD (EEMD), were used to sense the progression of muscle fatigue. They compared with each other. Although the highest frequency components of sEMG by DWT, EMD, and EEMD have the better performance to sense the progression of muscle fatigue than the raw sEMG, the EEMD has the best performance to reduce nonstationary characteristics and noise of the dynamic sEMG.

Monopolar electromyographic signals recorded by a current amplifier in air and under water without insulation

It was recently proposed that one could use signal current instead of voltage to collect surface electromyography (EMG). With EMG-current, the electrodes remain at the ground potential, thereby eliminating lateral currents. The purpose of this study was to determine whether EMG-currents can be recorded in Tap and Salt water, as well as in air, without electrically shielding the electrodes. It was hypothesized that signals would display consistent information between experimental conditions regarding muscle responses to changes in contraction effort. EMG-currents were recorded from the flexor digitorum muscles as participant's squeezed a pre-inflated blood pressure cuff bladder in each experimental condition at standardized efforts. EMG-current measurements performed underwater showed no loss of signal amplitude when compared to measurements made in air, although some differences in amplitude and spectral components were observed between conditions. However, signal amplitudes and frequencies displayed consistent behavior across contraction effort levels, irrespective of the experimental condition. This new method demonstrates that information regarding muscle activity is comparable between wet and dry conditions when using EMG-current. Considering the difficulties imposed by the need to waterproof traditional bipolar EMG electrodes when underwater, this new methodology is tremendously promising for assessments of muscular function in aquatic environments.

Electromyographic study in 5 muscles during an isometric fatiguing protocol

In this study, 12 healthy men aging 22.8 ± 2.2 years old were submitted to a protocol of isometric resistance to fatigue contemplating elbow flexion on three different angles: 45°, 90° and 135°. The objective was to study electromyographic median frequency (MDF) in the following muscles: i) Biceps Brachialis Long Head (BBL), Brachioradialis (BRD), Flexor Digitorum Superficialis (FDS), Triceps Brachialis Long Head (TBL), and Extensor Digitorum (ED). It was verified that, for all muscles, including the muscles that act in opposition to the contraction, fatigue presence was verified by the decrease of MDF value.

Muscle force estimation with surface EMG during dynamic muscle contractions: a wavelet and ANN based approach

Human muscle force estimation is important in biomechanics studies, sports and assistive devices fields. Therefore, it is essential to develop an efficient algorithm to estimate force exerted by muscles. The purpose of this study is to predict force/torque exerted by muscles under dynamic muscle contractions based on continuous wavelet transform (CWT) and artificial neural networks (ANN) approaches. Mean frequency (MF) of the surface electromyography (EMG) signals power spectrum was calculated from CWT. ANN models were trained to derive the MF-force relationships from the subset of EMG signals and the measured forces. Then we use the networks to predict the individual muscle forces for different muscle groups. Fourteen healthy subjects (10 males and 4 females) were voluntarily recruited in this study. EMG signals were collected from the biceps brachii, triceps, hamstring and quadriceps femoris muscles to evaluate the proposed method. Root mean square errors (RMSE) and correlation coefficients between the predicted forces and measured actual forces were calculated.

Contraction Intensity and Velocity on Vastus Lateralis Semg Power Spectrum and Amplitude

Effect of contraction intensity [100%, 75%, 50%, and 25% maximum voluntary contraction (MVC)] and movement velocity [0° (isometric)], 50°, 100°, 200°, and 400°/sec. [isovelocities]) on root mean square amplitude (SEMG–RMS) and median frequency power spectrum (SEMG–MNF) of vastus lateralis (VL) surface electromyography was investigated with ten healthy female university students. Peak torque (PT), mean torque (MT), SEMG–MNF, and SEMG–RMS, analyzed using separate repeated-measures analyses of variance ( p ≤ .05), indicated: (1) an inverse relation between PT and MT and movement velocity, (2) greater SEMG–MNF values during all isovelocity conditions compared with isometric conditions, with highest values occurring at 50°/sec. and at 100% and 75% MVC, and (3) at all contraction intensities SEMG–RMS values were higher during dynamic movements than isometric movements and highest at 200° / sec. Isovelocity contractions were inferred to facilitate a greater recruitment of fast-twitch fibers (via increased SEMG–MNF), which was intensified at 50°/sec, whereas greater overall muscle activation was found at 200° / sec.

The utility of electromyography and mechanomyography for assessing neuromuscular function: a noninvasive approach

This article introduces the utility of electromyography (EMG) and mechanomyography (MMG) for the assessment of neuromuscular function, and discusses the interpretation of the EMG and MMG signals for various exercise perturbations. The results of these studies suggest that the use of EMG and MMG to determine muscle fatigue is robust. Future studies with clinical populations are needed, however, to determine the optimal use of EMG and/or MMG for assessing muscle function in rehabilitative settings.

Specificity of a back muscle roman chair exercise in healthy and back pain subjects

PURPOSE

Roman chair exercises are popular for improving back muscle endurance but do not specifically target back muscles. This study aimed to determine whether an adaptation of the Roman chair exercise would induce more fatigue in back muscles than in hip extensors.

METHODS

For this study, 16 healthy subjects and 18 patients with nonspecific chronic low back pain performed trunk flexion-extension cycles until exhaustion in a Roman chair with hips flexed at 40°. Surface EMG signals were recorded bilaterally on four back muscles and two hip extensors (gluteus maximus and biceps femoris). Motion analysis of the trunk segments (pelvis, lumbar, and thoracic spines) was also carried out.

RESULTS

In both groups, EMG revealed clear evidence of muscle fatigue for the gluteus maximus, less clear evidence of fatigue for the lower back muscles, and motor unit recruitment (without fatigue) for the upper back muscles and biceps femoris. A change of muscle activation pattern was emphasized throughout the exercise bout, with some lower back muscles showing an increase followed by a decrease or leveling off of activation and with upper back muscles showing an increased activation at the end. Kinematic analyses revealed a progressive decrease (11°) in the lumbar range of motion (ROM) and a progressive increase in hip (2°) and thoracic (7°) ROM during the exercise bout.

CONCLUSIONS

Roman chairs allow more freedom to change the kinematics of the spine during the exercise (less lumbar and more thoracic motion) to delay lower back muscle fatigue by sharing the load between the lower and upper back muscles. Even with adaptations to reduce hip extensors fatigue, this may make this exercise not as specific as wanted for fatiguing lower back muscles.

Spectral properties of electromyographic and mechanomyographic signals during isometric ramp and step contractions in biceps brachii

The purposes of this study were: (1) to apply wavelet and principal component analysis to quantify the spectral properties of the surface EMG and MMG signals from biceps brachii during isometric ramp and step muscle contractions when the motor units are recruited in an orderly manner, and (2) to compare the recruitment patterns of motor unit during isometric ramp and step muscle contractions. Twenty healthy participants (age = 34 ± 10.7 years) performed step and ramped isometric contractions. Surface EMG and MMG were recorded from biceps brachii. The EMGs and MMGs were decomposed into their intensities in time-frequency space using a wavelet technique. The EMG and MMG spectra were then compared using principal component analysis (PCA) and ANCOVA. Wavelet combined PCA offers a quantitative measure of the contribution of high and low frequency content within the EMG and MMG. The ANCOVA indicated that there was no significant difference in EMG total intensity, EMG(MPF), first and second principal component loading scores (PCI and PCII) between ramp and step contractions, whereas the MMG(MPF) and MMG PCI loading scores were significantly higher during ramp contractions than during step contractions. These findings suggested that EMG and MMG may offer complimentary information regarding the interactions between motor unit recruitment and firing rate that control muscle force production. In addition, our results support the hypothesis that different motor unit recruitment strategy was used by the muscle when contracting under different conditions.

An EMG-driven biomechanical model that accounts for the decrease in moment generation capacity during a dynamic fatigued condition

Although it is well known that fatigue can greatly reduce muscle forces, it is not generally included in biomechanical models. The aim of the present study was to develop an electromyographic-driven (EMG-driven) biomechanical model to estimate the contributions of flexor and extensor muscle groups to the net joint moment during a nonisokinetic functional movement (squat exercise) performed in nonfatigued and in fatigued conditions. A methodology that aims at balancing the decreased muscle moment production capacity following fatigue was developed. During an isometric fatigue session, a linear regression was created linking the decrease in force production capacity of the muscle (normalized force/EMG ratio) to the EMG mean frequency. Using the decrease in mean frequency estimated through wavelet transforms between dynamic squats performed before and after the fatigue session as input to the previous linear regression, a coefficient accounting for the presence of fatigue in the quadriceps group was computed. This coefficient was used to constrain the moment production capacity of the fatigued muscle group within an EMG-driven optimization model dedicated to estimate the contributions of the knee flexor and extensor muscle groups to the net joint moment. During squats, our results showed significant increases in the EMG amplitudes with fatigue (+23.27% in average) while the outputs of the EMG-driven model were similar. The modifications of the EMG amplitudes following fatigue were successfully taken into account while estimating the contributions of the flexor and extensor muscle groups to the net joint moment. These results demonstrated that the new procedure was able to estimate the decrease in moment production capacity of the fatigued muscle group.

Increased voluntary drive is associated with changes in common oscillations from 13 to 60 Hz of interference but not rectified electromyography

The purpose of this study was to compare the capability of interference and rectified electromyography (EMG) to detect changes in the beta (13-30-HZ) and Piper (30-60-HZ) bands when voluntary force is increased. Twenty adults exerted a constant force abduction of the index finger at 15% and 50% of maximum. The common oscillations at various frequency bands (0-500 HZ) were estimated from the first dorsal interosseous muscle using cross wavelets of interference and rectified EMG. For the interference EMG signals, normalized power significantly (P < 0.01) increased with force in the beta (9.0 +/- 0.9 vs. 15.5 +/- 2.1%) and Piper (13.6 +/- 0.9 vs. 21 +/- 1.7%) bands. For rectified EMG signals, however, the beta and Piper bands remained unchanged (P > 0.4). Although rectified EMG is used in many clinical studies to identify changes in the oscillatory drive to the muscle, our findings suggest that only interference EMG can accurately capture the increase in oscillatory drive from 13 to 60 HZ with voluntary force.

A comparison of muscle activation between a Smith machine and free weight bench press

The bench press exercise exists in multiple forms including the machine and free weight bench press. It is not clear though how each mode differs in its effect on muscle activation. The purpose of this study was to compare muscle activation of the anterior deltoid, medial deltoid, and pectoralis major during a Smith machine and free weight bench press at lower (70% 1 repetition maximum [1RM]) and higher (90% 1RM) intensities. Normalized electromyography amplitude values were used during the concentric phase of the bench press to compare muscle activity between a free weight and Smith machine bench press. Participants were classified as either experienced or inexperienced bench pressers. Two testing sessions were used, each of which entailed either all free weight or all Smith machine testing. In each testing session, each participant's 1RM was established followed by 2 repetitions at 70% of 1RM and 2 repetitions at 90% of 1RM. Results indicated greater activation of the medial deltoid on the free weight bench press than on the Smith machine bench press. Also, there was greater muscle activation at the 90% 1RM load than at the 70% 1RM load. The results of this study suggest that strength coaches should consider choosing the free weight bench press over the Smith machine bench press because of its potential for greater upper-body muscular development.