A Comparative Study of EMG Indices in Muscle Fatigue Evaluation Based on Grey Relational Analysis during All-Out Cycling Exercise

Influence of Pedal Interface During Pedaling With the Upper Versus Lower Limbs: A Pilot Analysis of Torque Performance and Muscle Synergies

Pedaling is a physical exercise practiced with either the upper or the lower limbs. Muscle coordination during these exercises has been previously studied using electromyography and synergy analysis, and three to four synergies have been identified for the lower and upper limbs. The question of synergy adaptabilities has not been investigated during pedaling with the upper limbs, and the impact of various modalities is yet not known. This study investigates the effect of pedal type (either clipped/gripped or flat) on the torque performance and the synergy in both upper and lower limbs. Torques applied by six participants while pedaling at 30% of their maximal power have been recorded for both upper and lower limbs. Electromyographic data of 11 muscles on the upper limbs and 11 muscles on the lower limbs have been recorded and synergies extracted and compared between pedal types. Results showed that the torques were not modified by the pedal types for the lower limbs while a deep adaptation is observable for the upper limbs. Participants indeed used the additional holding possibility by pulling the pedals on top of the pushing action. Synergies were accordingly modified for upper limbs while they remain stable for the lower limbs. In both limbs, the synergies showed a good reproducibility even if larger variabilities were observed for the upper limbs. This pilot study highlights the adaptability of muscle synergies according to the condition of movement execution, especially observed for the upper limbs, and can bring some new insights for the rehabilitation exercises.

A Multi-Day Wearable Surface EMG E-Tattoo for Fatigue Monitoring

Surface electromyography (sEMG) is a commonly used technique for the non-invasive measurement of muscle activity. However, the traditional electrodes used for sEMG often have limitations regarding their long-term wearability. This study explored the feasibility of a wearable platform using a tattoo-like epidermal electrode (e-tattoo) for multi-day sEMG monitoring. Our sEMG e-tattoo provided stable and reliable sEMG signals over three days of application comparable to conventional gel electrodes. In addition, the e-tattoo has great resistance to motion artifacts and, therefore, maintains a high signal-to-noise ratio (SNR) and signal-to-motion ratio (SMR) during dynamic activities such as cycling. This robust wearable platform opens up new avenues for developing future wearable sEMG devices and advancing dynamic muscle fatigue research.Clinical relevance- The proposed wearable sEMG system can provide continuous and non-invasive monitoring of muscle activity, providing insights for improving rehabilitation and EMG-based prosthesis development for patients.

Hip and Knee Joint Angles Determine Fatigue Onset during Quadriceps Neuromuscular Electrical Stimulation

Neuromuscular electrical stimulation (NMES) has been used to increase muscle strength and physical function. However, NMES induces rapid fatigue, limiting its application. To date, the effect of quadriceps femoris (QF) muscle length by knee and hip joint manipulation on NMES-induced contraction fatigability is not clear. We aimed to quantify the effects of different muscle lengths on NMES-induced contraction fatigability, fatigue index, and electromyographic (EMG) activity for QF muscle. QF maximum evoked contraction (QMEC) was applied in a 26 min protocol (10 s on; 120 s off; 12 contractions) in 20 healthy participants (24.0 ± 4.6 years old), over 4 sessions on different days to test different conditions. The tested conditions were as follows: supine with knee flexion of 60° (SUP60), seated with knee flexion of 60° (SIT60), supine with knee flexion of 20° (SUP20), and seated with knee flexion of 20° (SIT20). Contraction fatigability (torque decline assessed by maximal voluntary contraction [MVC] and during NMES), fatigue index (percentage reduction in MVC), and EMG activity (root mean square [RMS] and median frequency) of the superficial QF' constituents were assessed. After NMES, all positions except SUP20 had an absolute reduction in MVC (p < .001). Fatigue index was greater in SIT20 than in SIT60 (p < .001) and SUP20 (p = .01). There was significant torque reduction across the 12 QMEC in SUP60 and SIT60, up to 10.5% (p < .001–.005) and 9.49% (p < .001–.033), respectively. There was no torque reduction during NMES in SUP20 and SIT20. Fatigue was accompanied by an increase in RMS (p = .032) and a decrease in median frequency for SUP60 (p < .001). Median frequency increased only in the SUP20 condition (p = .021). We concluded that QF NMES-induced contraction fatigability is greater when the knee is flexed at 60° compared to 20°. In addition, a supine position promotes earlier fatigue for a 60° knee flexion, but it delays fatigue onset for a 20° knee flexion compared to the seated position. These results provide a rationale for lower limb positioning during NMES, which depends on training objectives, e.g., strengthening or task-specific functionality training.

Neuromuscular Fatigue Responses of Endurance- and Strength-Trained Athletes during Incremental Cycling Exercise

This study explored the development of neuromuscular fatigue responses during progressive cycling exercise. The sample comprised 32 participants aged 22.0 ± 0.54 years who were assigned into three groups: endurance-trained group (END, triathletes, n = 10), strength-trained group (STR, bodybuilders, n = 10) and control group (CG, recreationally active students, n = 12). The incremental cycling exercise was performed using a progressive protocol starting with a 3 min resting measurement and then 50 W workload with subsequent constant increments of 50 W every 3 min until 200 W. Surface electromyography (SEMG) of rectus femoris muscles was recorded during the final 30 s of each of the four workloads. During the final 15 s of each workload, participants rated their overall perception of effort using the 20-point rating of the perceived exertion (RPE) scale. Post hoc Tukey’s HSD testing showed significant differences between the END and STR groups in median frequency and mean power frequency across all workloads (p < 0.001 and p < 0.01, respectively). Athletes from the END group had significantly lower electromyogram amplitude responses than those from the STR (p = 0.0093) and CG groups (p = 0.0006). Increasing RPE points from 50 to 200 W were significantly higher in the STR than in the END group (p < 0.001). In conclusion, there is a significant variation in the neuromuscular fatigue profiles between athletes with different training backgrounds when a cycling exercise is applied. The approximately linear trends of the SEMG and RPE values of both groups of athletes with increasing workload support the increased skeletal muscle recruitment with perceived exertion or fatiguing effect.

[Fatigue analysis of upper limb rehabilitation based on surface electromyography signal and motion capture]

At present, fatigue state monitoring of upper limb movement generally relies solely on surface electromyographic signal (sEMG) to identify and classify fatigue, resulting in unstable results and certain limitations. This paper introduces the sEMG signal recognition and motion capture technology into the fatigue state monitoring process and proposes a fatigue analysis method combining an improved EMG fatigue threshold algorithm and biomechanical analysis. In this study, the right upper limb load elbow flexion test was used to simultaneously collect the biceps brachii sEMG signal and upper limb motion capture data, and at the same time the Borg Fatigue Subjective and Self-awareness Scale were used to record the fatigue feelings of the subjects. Then, the fatigue analysis method combining the EMG fatigue threshold algorithm and the biomechanical analysis was combined with four single types: mean power frequency (MPF), spectral moments ratio (SMR), fuzzy approximate entropy (fApEn) and Lempel-Ziv complexity (LZC). The test results of the evaluation index fatigue evaluation method were compared. The test results show that the method in this paper has a recognition rate of 98.6% for the overall fatigue state and 97%, 100%, and 99% for the three states of ease, transition and fatigue, which are more advantageous than other methods. The research results of this paper prove that the method in this paper can effectively prevent secondary injury caused by overtraining during upper limb exercises, and is of great significance for fatigue monitoring.

A Study on the Relationship between RPE and sEMG in Dynamic Contraction Based on the GPR Method

The rating of perceived exertion (RPE) and surface electromyography (sEMG) describe exercise intensity subjectively and objectively, while there has been a lack of research on the relationship between them during dynamic contractions to predict exercise intensity, comprehensively. The purpose of this study was to establish a model of the relationship between sEMG and RPE during dynamic exercises. Therefore, 20 healthy male subjects were organized to perform an incremental load test on a cycle ergometer, and the subjects’ RPEs (Borg Scale 6–20) were collected every minute. Additionally, the sEMGs of the subjects’ eight lower limb muscles were collected. The sEMG features based on time domain, frequency domain and time–frequency domain methods were extracted, and the relationship model was established using Gaussian process regression (GPR). The results show that the sEMG and RPE of the selected lower limb muscles are significantly correlated (p < 0.05) but that they have different monotonic correlation degrees. The model that was established with all three domain features displayed optimal performance and when the RPE was 13, the prediction error was the smallest. The study is significant for lower limb muscle training strategy and quantification of training intensity from both subjective and objective aspects, and lays a foundation for sEMG further applications in rehabilitation medicine and sports training.

Grey Relational Analysis of Lower Limb Muscle Fatigue and Pedalling Performance Decline of Elite Athletes during a 30-Second All-Out Sprint Cycling Exercise

The 30-second all-out sprint cycling exercise is a classical sport capacity evaluation method, which may cause severe lower limb muscle fatigue. However, the relationship between lower limb muscle fatigue and the decline in exercise performance during 30-second sprint cycling remains unclear. In this study, ten cyclists volunteered to participate in a 30-second all-out sprint cycling while power, cadence, and surface electromyographic (EMG) signals of eight lower limb muscles were recorded during the exercise. EMG mean frequency (MNF) of each lower limb muscle group was computed for every 3-second epoch based on wavelet packet transformation. Grey relational grades between pedalling performance and the EMG MNF of each lower limb muscle group during the whole process were calculated. The results demonstrated that EMG MNF of the rectus femoris (RF), vastus (VAS), gastrocnemius (GAS), and tibialis anterior (TA) progressively tired during a 30-second all-out sprint cycling exercise. Of the muscles evaluated, the degree of fatigue of TA showed the greatest association with exercise performance decline, whereas the muscle fatigue of RF, VAS, and GAS also significantly impacted exercise performance during a 30-second all-out sprint cycling exercise.

Diagnosis of Muscle Fatigue Using Surface Electromyography and Analysis of Associated Factors in Type 2 Diabetic Patients with Neuropathy: A Preliminary Study

Diabetic neuropathy (DN) is a major complication associated with diabetes mellitus (DM) and results in fatigue. We investigated whether type 2 diabetic patients with or without neuropathy experienced muscle fatigue and determined the most influencing factor on muscle fatigue. Overall, 15 out of 25 patients with type 2 DM were diagnosed with DN using a nerve conduction study in the upper and lower extremities, and the composite score (CS) was calculated. We obtained the duration of DM and body mass index (BMI) from subjects, and they underwent a series of laboratory tests including HbA1c, fasting plasma glucose, triglycerides, and high- and low-density lipoprotein. To qualify muscle fatigue, this study used surface electromyography (sEMG). Anode and cathode electrodes were attached to the medial gastrocnemius. After 100% isometric maximal voluntary contracture of plantarflexion, the root mean square, median frequency (MDF), and mean power frequency (MNF) were obtained. We showed a correlation among laboratory results, duration of DM, BMI, CS, and parameters of muscle fatigue. The duration of DM was related to fatigue of the muscle and CS (p < 0.05). However, CS was not related to fatigue. The MDF and MNF of muscle parameters were positively correlated with HbA1c and fasting plasma glucose (p < 0.05). In conclusion, we suggest that the duration of DM and glycemic control play important roles in muscle fatigue in patients with DN. Additionally, sEMG is useful for diagnosing muscle fatigue in patients with DN.

Overuse-Related Injuries of the Musculoskeletal System: Systematic Review and Quantitative Synthesis of Injuries, Locations, Risk Factors and Assessment Techniques

Overuse-related musculoskeletal injuries mostly affect athletes, especially if involved in preseason conditioning, and military populations; they may also occur, however, when pathological or biological conditions render the musculoskeletal system inadequate to cope with a mechanical load, even if moderate. Within the MOVIDA (Motor function and Vitamin D: toolkit for risk Assessment and prediction) Project, funded by the Italian Ministry of Defence, a systematic review of the literature was conducted to support the development of a transportable toolkit (instrumentation, protocols and reference/risk thresholds) to help characterize the risk of overuse-related musculoskeletal injury. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) approach was used to analyze Review papers indexed in PubMed and published in the period 2010 to 2020. The search focused on stress (overuse) fracture or injuries, and muscle fatigue in the lower limbs in association with functional (biomechanical) or biological biomarkers. A total of 225 Review papers were retrieved: 115 were found eligible for full text analysis and led to another 141 research papers derived from a second-level search. A total of 183 papers were finally chosen for analysis: 74 were classified as introductory to the topics, 109 were analyzed in depth. Qualitative and, wherever possible, quantitative syntheses were carried out with respect to the literature review process and quality, injury epidemiology (type and location of injuries, and investigated populations), risk factors, assessment techniques and assessment protocols.

Chen B. A Data-Driven Approach to Predict Fatigue in Exercise Based on Motion Data from Wearable Sensors or Force Plate

Fatigue increases the risk of injury during sports training and rehabilitation. Early detection of fatigue during exercises would help adapt the training in order to prevent over-training and injury. This study lays the foundation for a data-driven model to automatically predict the onset of fatigue and quantify consequent fatigue changes using a force plate (FP) or inertial measurement units (IMUs). The force plate and body-worn IMUs were used to capture movements associated with exercises (squats, high knee jacks, and corkscrew toe-touch) to estimate participant-specific fatigue levels in a continuous fashion using random forest (RF) regression and convolutional neural network (CNN) based regression models. Analysis of unseen data showed high correlation (up to 89%, 93%, and 94% for the squat, jack, and corkscrew exercises, respectively) between the predicted fatigue levels and self-reported fatigue levels. Predictions using force plate data achieved similar performance as those with IMU data; the best results in both cases were achieved with a convolutional neural network. The displacement of the center of pressure (COP) was found to be correlated with fatigue compared to other commonly used features of the force plate. Bland-Altman analysis also confirmed that the predicted fatigue levels were close to the true values. These results contribute to the field of human motion recognition by proposing a deep neural network model that can detect fairly small changes of motion data in a continuous process and quantify the movement. Based on the successful findings with three different exercises, the general nature of the methodology is potentially applicable to a variety of other forms of exercises, thereby contributing to the future adaptation of exercise programs and prevention of over-training and injury as a result of excessive fatigue.

Sustained fatigue assessment during isometric exercises with time-domain near infrared spectroscopy and surface electromyography signals

The effect of sustained fatigue during an upper limb isometric exercise is presented to investigate a group of healthy subjects with simultaneous time-domain (TD) NIRS and surface electromyography (sEMG) recordings on the deltoid lateralis muscle. The aim of the work was to understand which TD-NIRS parameters can be used as descriptors for sustained muscular fatigue, focusing on the slow phase of this process and using median frequency (MF) computed from sEMG as gold standard measure. It was found that oxygen saturation and deoxy-hemoglobin are slightly better descriptors of sustained fatigue, than oxy-hemoglobin, since they showed a higher correlation with MF, while total-hemoglobin correlation with MF was lower.

Rehabilitation Effects of Fatigue-Controlled Treadmill Training After Stroke: A Rat Model Study

Background: Traditional rehabilitation with uniformed intensity would ignore individual tolerance and introduce the second injury to stroke survivors due to overloaded training. However, effective control of the training intensity of different stroke survivors is still lacking. The purpose of the study was to investigate the rehabilitative effects of electromyography (EMG)-based fatigue-controlled treadmill training on rat stroke model. Methods: Sprague-Dawley rats after intracerebral hemorrhage and EMG electrode implantation surgeries were randomly distributed into three groups: the control group (CTRL, n = 11), forced training group (FOR-T, n = 11), and fatigue-controlled training group (FAT-C, n = 11). The rehabilitation interventions were delivered every day from day 2 to day 14 post-stroke. No training was delivered to the CTRL group. The rats in the FOR-T group were forced to run on the treadmill without rest. The fatigue level was monitored in the FAT-C group through the drop rate of EMG mean power frequency, and rest was applied to the rats when the fatigue level exceeded the moderate fatigue threshold. The speed and accumulated running duration were comparable in the FAT-C and the FOR-T groups. Daily evaluation of the motor functions was performed using the modified Neurological Severity Score. Running symmetry was investigated by the symmetry index of EMG bursts collected from both hind limbs during training. The expression level of neurofilament-light in the striatum was measured to evaluate the neuroplasticity. Results: The FAT-C group showed significantly lower modified Neurological Severity Score compared with the FOR-T (P ≤ 0.003) and CTRL (P ≤ 0.003) groups. The FAT-C group showed a significant increase in the symmetry of hind limbs since day 7 (P = 0.000), whereas the FOR-T group did not (P = 0.349). The FAT-C group showed a higher concentration of neurofilament-light compared to the CTRL group (P = 0.005) in the unaffected striatum and the FOR-T group (P = 0.021) in the affected striatum. Conclusion: The treadmill training with moderate fatigue level controlled was more effective in motor restoration than forced training. The fatigue-controlled physical training also demonstrated positive effects in the striatum neuroplasticity. This study indicated that protocol with individual fatigue-controlled training should be considered in both animal and clinical studies for better stroke rehabilitation.

Pedaling Performance Changing of Elite Cyclists Is Mainly Determined by the Fatigue of Hamstring and Vastus Muscles during Repeated Sprint Cycling Exercise

Repeated sprint cycling is an effective training method in promoting athletic performance of cyclists, which may induce severe fatigue of lower limb muscles. However, the relationship between the fatigue of each lower limb muscles and the changing of exercise performance remains unclear. In this study, ten cyclist volunteers performed a series of 6-second sprints with 24-s recovery for five times. Power, cadence, and EMG mean frequency (MNF) of each lower limb muscle group for every 2-second epoch, as well as the grey relational grade between exercise performance and MNF of each lower limb muscle group during the whole process were calculated. It has been found that MNF of Rectus femoris (RF), Vastus (VAS), Gastrocnemius (GAS), and the hamstring muscle group (HAM) showed significant negative correlation with the increase in both sprint number and intrasprint duration time, while the grey relational grade of HAM and VAS was higher than that of other muscles. The results demonstrated that the exercise performance of both power and cadence were most closing related to the fatigue degree of HAM and VAS during repeated sprint cycling exercise.

An efficient approach for physical actions classification using surface EMG signals

Physical actions classification of surface electromyography (sEMG) signal is required in applications like prosthesis, and robotic control etc. In this paper, tunable-Q factor wavelet transform (TQWT) based algorithm is proposed for the classification of physical actions such as clapping, hugging, bowing, handshaking, standing, running, jumping, waving, seating, and walking. sEMG signal is decomposed into sub-bands by TQWT. Various features are extracted from each different band and statistical analysis is performed. These features are fed into multi-class least squares support vector machine classifier using two non-linear kernel functions, morlet wavelet function, and radial basis function. The proposed method is an attempt for classifying physical actions using TQWT and its performance and results are promising and have high classification accuracy of 97.74% for sub-band eight with morlet kernel function.

Illumination/Darkness-Induced Changes in Leaf Surface Potential Linked With Kinetics of Ion Fluxes

A highly reproducible plant electrical signal-light-induced bioelectrogenesis (LIB) was obtained by means of periodic illumination/darkness stimulation of broad bean (Vicia faba L.) leaves. By stimulating the same position of the same leaf with different concentrations of NaCl, we observed that the amplitude and waveform of the LIB was correlated with the intensity of stimulation. This method allowed us to link dynamic ion fluxes induced by periodic illumination/darkness to salt stress. The self-referencing ion electrode technique was used to explore the ionic mechanisms of the LIB. Fluxes of H+, Ca2+, K+, and Cl- showed periodic changes under periodic illumination/darkness before and after 50 mM NaCl stimulation. Gray relational analysis was used to analyze correlations between each of these ions and LIB. The results showed that different ions are involved in surface potential changes at different stages under periodic illumination/darkness. The gray relational grade reflected the contribution of each ion to the change in surface potential at a certain time period. The ion fluxes data obtained under periodic illumination/darkness stimulation will contribute to the future development of a dynamic model for interpretation of electrophysiological events in plant cells.

NIRS-EMG for Clinical Applications: A Systematic Review

In this review, we present an overview of the applications and computed parameters of electromyography (EMG) and near-infrared spectroscopy (NIRS) methods on patients in clinical practice. The eligible studies were those where both techniques were combined in order to assess muscle characteristics from the electrical and hemodynamic points of view. With this aim, a comprehensive screening of the literature based on related keywords in the most-used scientific data bases allowed us to identify 17 papers which met the research criteria. We also present a brief overview of the devices designed specifically for muscular applications with EMG and NIRS sensors (a total of eight papers). A critical analysis of the results of the review suggests that the combined use of EMG and NIRS on muscle has been only partially exploited for assessment and evaluation in clinical practice and, thus, this field shows promises for future developments.

How Physical Activities Affect Mental Fatigue Based on EEG Energy, Connectivity, and Complexity

Many studies have verified that there is an interaction between physical activities and mental fatigue. However, few studies are focused on the effect of physical activities on mental fatigue. This study was to analyze the states of mental fatigue based on electroencephalography (EEG) and investigate how physical activities affect mental fatigue. Fourteen healthy participants participated in an experiment including a 2-back mental task (the control) and the same mental task with cycling simultaneously (physical-mental task). Each experiment consisted of three 20 min fatigue-inducing sessions repeatedly (mental fatigue for mental tasks or mental fatigue plus physical activities for physical-mental tasks). During the evaluation sessions (before and after the fatigue-inducing sessions), the states of the participants were assessed by EEG parameters. Wavelet Packet Energy (WPE), Spectral Coherence Value (SCV), and Lempel-Ziv Complexity (LZC) were used to indicate mental fatigue from the perspectives of activation, functional connectivity, and complexity of the brain. The indices are the beta band energy E_β, the energy ratio E_α/β, inter-hemispheric SCV of beta band SCV_β and LZC. The statistical analysis shows that mental fatigue was detected by E_β, E_α/β, SCV_β, and LZC in physical-mental task. The slopes of the linear fit on these indices verified that the mental fatigue increased more fast during physical-mental task. It is concluded form the result that physical activities can enhance the mental fatigue and speed up the fatigue process based on brain activation, functional connection, and complexity. This result differs from the traditional opinion that physical activities have no influence on mental fatigue, and finds that physical activities can increase mental fatigue. This finding helps fatigue management through exercise instruction.