EMG frequency spectrum, muscle structure, and fatigue during dynamic contractions in man

Influence of a fatiguing exercise on lower limb electromyographic activities and co-contraction in overweight females during running

BACKGROUND

This study investigates the effects of a fatiguing exercise on lower limb electro-myographic activities and co-contraction in overweight females compared with normal weight females during running.

METHODS

Forty-eight females were divided into two groups. The first group included individuals with a normal body-mass-index. The second group comprised individuals classified as overweight/obese based on body-mass-index. Electromyography data from the tibialis anterior, gastrocnemius medialis, vastus lateralis, vastus medialis, rectus femoris, biceps femoris, and semitendinosus muscles were collected during running at constant speed using a surface electromyography system before and after a running induced fatigue.

FINDINGS

The results indicated significant main effects of the "Group" on tibialis anterior muscle activities during the loading phase (P = 0.040). Furthermore, the results showed significant main effects of "Fatigue" on rectus femoris (P = 0.028) and semitendinosus (P = 0.007) muscle activities during the loading phase. Paired-wise comparison demonstrated significantly greater rectus femoris and semitendinosus activities during the loading phase after the fatigue protocol. The results demonstrated significant main effects of "Fatigue" for general knee muscular co-contraction during early stance phase (P < 0.001). Paired-wise comparison demonstrated significantly greater general knee muscular co-contraction during early stance phase at post-test compared with pre-test. No significant main effect of "Group" and group-by-fatigue interactions were found for general and direct knee co-contraction during early stance phase (P > 0.05).

INTERPRETATION

Overall, our findings indicate that both fatigue and being overweight result in running pattern differences, but these occur through different mechanisms at a neuromuscular level. Neuromuscular responses to fatigue during running in overweight adults and in normal weight adults can be evaluated together, in order to optimize the modality of treatment and rehabilitation processes in overweight adults to reduce and/or prevent the risk of running related injury.

Central and peripheral nervous system activity and muscle oxygenation in athletes during repeated-sprint exercise in normoxia and normobaric hypoxia

AIM

To investigate central and peripheral nervous system activity and muscle oxygenation in athletes during repeated-sprint exercise in normoxia and normobaric hypoxia.

METHODS

The effects on vastus lateralis muscle strength in a cross-over study were examined in 18 athletes (13 males, 5 females) completing 10 × 6-s cycle sprints. Immediately after and again 5 minutes post-exercise, electromyography (EMG), heart rate variability, maximal voluntary contraction (MVC), muscle oxygenation, peak power output, and arterial oxygen saturation were compared to 2 baseline sets named ("Baseline" and "Pre").

RESULTS

Post-exercise MVC was significantly lower (6.7 ± 10.0%) than Baseline, but root-mean-square amplitude during hypoxia (all-times) was significantly lower than normoxia (0.38 ± 0.19 vs 0.41 ± 0.17 mV). Comparative frequency analysis of the percentage change in pre- to post-exercise EMG area, at low 1-29 hz (type-1 fibre) and high 75-100 hz (type-2 fibre) areas, revealed a significant reduction in type-1 fibre activity relative to type-2, by 20-30% across time and by 10% in type-1 activity between conditions.

CONCLUSION

Exercise in hypoxia appeared to cause a temporary increase in central sympathetic nervous system activity and greater recruitment of type-2 muscle fibres, with accompanying reduction in type-1. Acute hypoxia may stimulate type-2 fibre conditioning.

Association between skin sympathetic nerve activity and electrocardiogram alterations after subarachnoid hemorrhage

While autonomic dysregulation and repolarization abnormalities are observed in subarachnoid hemorrhage (SAH), their relationship remains unclear. We aimed to measure skin sympathetic nerve activity (SKNA), a novel method to estimate stellate ganglion nerve activity, and investigate its association with electrocardiogram (ECG) alterations after SAH. We recorded a total of 179 SKNA data from SAH patients at three distinct phases and compared them with 20 data from controls. Compared with control data, in the acute phase data (days 1-3 of SAH), T peak-to-end (Tp-e) interval was significantly prolonged (81 [interquartile range {IQR}: 71-93] vs. 58 [IQR: 54-64] ms, p < 0.001), non-burst amplitude of SKNA was significantly increased (2.4 [IQR: 1.3-4.1] vs. 0.7 [IQR: 0.5-1.7] μV, p < 0.001), and the ratio of low frequency to high frequency (HF) was significantly decreased (0.8 [IQR: 0.5-1.1] vs. 1.1 [IQR: 0.7-1.3], p = 0.028). Linear mixed model revealed a relationship between Tp-e interval and SKNA. Although these abnormalities gradually normalized, delayed cerebral ischemia episodes were associated with increased HF oscillation. Transient sympathetic dysregulation contributes to repolarization impairment after SAH. SKNA may have the potential to monitor adverse outcomes.

Muscle-Fiber Typology Is Associated With Sprint-Cycling Characteristics in World-Class and Elite Track Cyclists

PURPOSE

Identifying the determinants of performance is fundamental to talent identification and individualizing training prescription. Consequently, the aim of this study was to determine whether estimated muscle typology is associated with the key mechanical characteristics of track sprint cycling.

METHODS

Sixteen world-class and elite track cyclists (n = 7 female) completed a laboratory session wherein torque-cadence and power-cadence profiles were constructed to determine maximal power output (Pmax), optimal cadence (Fopt), and maximal cadence (Fmax), and fatigue rate per pedal stroke was determined during a 15-second maximal sprint at Fopt. Muscle typology was estimated by measuring carnosine content via proton magnetic resonance spectroscopy in the gastrocnemius and soleus.

RESULTS

Using partial correlation analysis to account for sex, greater muscle carnosine content (ie, greater estimated proportion of type II fibers) was associated with a greater Pmax (r = .68, P = .007), Fmax (r = .77, P = .0014), Fopt (r = .61, P = .0196), and absolute fatigue rate (W·stroke-1; r = -.55, P = .0418) but not relative fatigue rate (%peak power·stroke-1; r = -.33, P = .246).

CONCLUSIONS

The findings from this study substantiate the mechanical differences in muscle-fiber types derived from single muscle-fiber studies and highlight the importance of estimated muscle typology for sprint cycling performance.

Revisiting the stretch-induced force deficit: A systematic review with multilevel meta-analysis of acute effects

BACKGROUND

When recommending avoidance of static stretching prior to athletic performance, authors and practitioners commonly refer to available systematic reviews. However, effect sizes (ES) in previous reviews were extracted in major part from studies lacking control conditions and/or pre-post testing designs. Also, currently available reviews conducted calculations without accounting for multiple study outcomes, with ES: -0.03 to 0.10, which would commonly be classified as trivial.

METHODS

Since new meta-analytical software and controlled research articles have appeared since 2013, we revisited the available literatures and performed a multilevel meta-analysis using robust variance estimation of controlled pre-post trials to provide updated evidence. Furthermore, previous research described reduced electromyography activity-also attributable to fatiguing training routines-as being responsible for decreased subsequent performance. The second part of this study opposed stretching and alternative interventions sufficient to induce general fatigue to examine whether static stretching induces higher performance losses compared to other exercise routines.

RESULTS

Including 83 studies with more than 400 ES from 2012 participants, our results indicate a significant, small ES for a static stretch-induced maximal strength loss (ES = -0.21, p = 0.003), with high magnitude ES (ES = -0.84, p = 0.004) for stretching durations ≥60 s per bout when compared to passive controls. When opposed to active controls, the maximal strength loss ranges between ES: -0.17 to -0.28, p < 0.001 and 0.040 with mostly no to small heterogeneity. However, stretching did not negatively influence athletic performance in general (when compared to both passive and active controls); in fact, a positive effect on subsequent jumping performance (ES = 0.15, p = 0.006) was found in adults.

CONCLUSION

Regarding strength testing of isolated muscles (e.g., leg extensions or calf raises), our results confirm previous findings. Nevertheless, since no (or even positive) effects could be found for athletic performance, our results do not support previous recommendations to exclude static stretching from warm-up routines prior to, for example, jumping or sprinting.

Are Surface Electromyography Parameters Indicative of Post-Activation Potentiation/Post-Activation Performance Enhancement, in Terms of Twitch Potentiation and Voluntary Performance? A Systematic Review

The aim was to identify if surface electromyography (sEMG) parameters are indicative of post-activation potentiation (PAP)/post-activation performance enhancement (PAPE), in terms of twitch potentiation and voluntary performance. Three databases were used in April 2024, with the following inclusion criteria: (a) original research, assessed in healthy human adults, and (b) sEMG parameters were measured. The exclusion criteria were (a) studies with no PAP/PAPE protocol and (b) non-randomized control trials. The following data were extracted: study characteristics/demographics, PAP/PAPE protocols, sEMG parameters, twitch/performance outcomes, and study findings. A modified physiotherapy evidence database (PEDro) scale was used for quality assessment. Fifteen randomized controlled trials (RCTs), with a total of 199 subjects, were included. The M-wave amplitude (combined with a twitch torque outcome) was shown to generally be indicative of PAP. The sEMG amplitudes (in some muscles) were found to be indicative of PAPE during ballistic movements, while a small decrease in the MdF (in certain muscles) was shown to reflect PAPE. Changes in the Hmax/Mmax ratio were found to contribute (temporally) to PAP, while the H-reflex amplitude was shown to be neither indicative of PAP nor PAPE. This review provides preliminary findings suggesting that certain sEMG parameters could be indicative of PAP/PAPE. However, due to limited studies, future research is warranted.

Boys-men mean-power-frequency differences in progressive exercise to exhaustion, confounded by variability and adiposity

BACKGROUND

Only scant research has compared children's mean power frequency (MPF) to adults', with a clear overview still lacking. A significant obstacle has been MPF's high variability, which this study aimed to overcome by elucidating the MPF characteristics distinguishing boys from men in progressive exhaustive exercise.

METHODS

Electromyographic (EMG) data of 20 men (23.5 ± 2.5yrs) and 17 boys (10.2 ± 1.0 yrs), who performed progressively exhausting, intermittent isometric knee extensions, were subjected to secondary MPF analysis. Participants' vastus lateralis MPF data series were transformed to third-order polynomial regressions and expressed as percentages of the peak polynomial MPF values (%MPFpeak). The resulting curves were compared at 5-% time-to-exhaustion (TTE) intervals, using repeated-measures ANOVA. Raw MPFpeak values were adiposity corrected to 0% fat and used to convert the %MPFpeak data back to absolute MPF values (Hz) for estimating muscle-level MPF.

RESULTS

No overall interaction or group effects could be shown between the %MPFpeak plots, but pairwise comparisons revealed significantly higher men's values at 50-70%TTE and lower at 100%TTE, i.e. boys' shallower MPF rise and decline. The adiposity-corrected boys' and men's composite MPF values peaked at 125.7 ± 2.5 and 166.0 ± 2.4 Hz, respectively (110.7 ± 1.7 and 122.5 ± 2.1 Hz, uncorrected), with a significant group effect (p < 0.05) and pairwise differences at all %TTE points.

CONCLUSIONS

The boys were lower than the men in both the observed and, more so, in the adiposity-corrected MPF values that presumably estimate muscle-level MPF. The boys' shallower MPF rise and decline conform to children's claimed type-II motor-unit activation and/or compositional deficits and their related known advantage in muscular endurance.

The role of clinical neurophysiology in the definition and assessment of fatigue and fatigability

Though a common symptom, fatigue is difficult to define and investigate, occurs in a wide variety of neurological and systemic disorders, with differing pathological causes. It is also often accompanied by a psychological component. As a symptom of long-term COVID-19 it has gained more attention. In this review, we begin by differentiating fatigue, a perception, from fatigability, quantifiable through biomarkers. Central and peripheral nervous system and muscle disorders associated with these are summarised. We provide a comprehensive and objective framework to help identify potential causes of fatigue and fatigability in a given disease condition. It also considers the effectiveness of neurophysiological tests as objective biomarkers for its assessment. Among these, twitch interpolation, motor cortex stimulation, electroencephalography and magnetencephalography, and readiness potentials will be described for the assessment of central fatigability, and surface and needle electromyography (EMG), single fibre EMG and nerve conduction studies for the assessment of peripheral fatigability. The purpose of this review is to guide clinicians in how to approach fatigue, and fatigability, and to suggest that neurophysiological tests may allow an understanding of their origin and interactions. In this way, their differing types and origins, and hence their possible differing treatments, may also be defined more clearly.

The History and Future of Neuromusculoskeletal Biomechanics

The Executive Council of the International Society of Biomechanics has initiated and overseen the commemorations of the Society's 50th Anniversary in 2023. This included multiple series of lectures at the ninth World Congress of Biomechanics in 2022 and XXIXth Congress of the International Society of Biomechanics in 2023, all linked to special issues of International Society of Biomechanics' affiliated journals. This special issue of the Journal of Applied Biomechanics is dedicated to the biomechanics of the neuromusculoskeletal system. The reader is encouraged to explore this special issue which comprises 6 papers exploring the current state-of the-art, and future directions and roles for neuromusculoskeletal biomechanics. This editorial presents a very brief history of the science of the neuromusculoskeletal system's 4 main components: the central nervous system, musculotendon units, the musculoskeletal system, and joints, and how they biomechanically integrate to enable an understanding of the generation and control of human movement. This also entails a quick exploration of contemporary neuromusculoskeletal biomechanics and its future with new fields of application.

Pattern Matching for Real-Time Extraction of Fast and Slow Spectral Components From sEMG Signals

Previous studies have demonstrated the potential of surface electromyography (sEMG) spectral decomposition in evaluating muscle performance, motor learning, and early diagnosis of muscle conditions. However, decomposition techniques require large data sets and are computationally demanding, making their implementation in real-life scenarios challenging. Based on the hypothesis that spectral components will present low inter-subject variability, the present paper proposes the foundational principles for developing a real-time system for their extraction by utilizing a pre-defined library of components derived from an extensive data set to match new measurements. The model library was tailored to fulfill specific requirements for real-time system application and the challenges encountered during implementation are discussed in the paper. For system validation, four distinct data sets comprising isotonic and isometric muscle activations were utilized. The extracted during validation showed low inter-subject variability, suggesting that a wide range of physiological variations can be described with them. The adoption of the proposed system for muscle analysis could provide a deeper understanding of the underlying mechanisms governing different motor conditions and neuromuscular disorders, as it allows for the measurement of these components in various daily-life scenarios.

Non-Parametric Functional Muscle Network as a Robust Biomarker of Fatigue

Characterization of fatigue using surface electromyography (sEMG) data has been motivated for rehabilitation and injury-preventative technologies. Current sEMG-based models of fatigue are limited due to (a) linear and parametric assumptions, (b) lack of a holistic neurophysiological view, and (c) complex and heterogeneous responses. This paper proposes and validates a data-driven non-parametric functional muscle network analysis to reliably characterize fatigue-related changes in synergistic muscle coordination and distribution of neural drive at the peripheral level. The proposed approach was tested on data collected in this study from the lower extremities of 26 asymptomatic volunteers (13 subjects were assigned to the fatigue intervention group, and 13 age/gender-matched subjects were assigned to the control group). Volitional fatigue was induced in the intervention group by moderate-intensity unilateral leg press exercises. The proposed non-parametric functional muscle network demonstrated a consistent decrease in connectivity after the fatigue intervention, as indicated by network degree, weighted clustering coefficient (WCC), and global efficiency. The graph metrics displayed consistent and significant decreases at the group level, individual subject level, and individual muscle level. For the first time, this paper proposed a non-parametric functional muscle network and highlighted the corresponding potential as a sensitive biomarker of fatigue with superior performance to conventional spectrotemporal measures.

Generation and analysis of synthetic surface electromyography signals under varied muscle fiber type proportions and validation using recorded signals

The magnitude and duration of muscle force production are influenced by the fiber type proportion. In this work, surface electromyography (sEMG) signals of muscles with varied fiber type proportions, are generated. For this, relevant components of existing models reported in various literature have been adopted. Also, a method to calculate the motor unit size factor is proposed. sEMG signals of adductor pollicis (AP) and triceps brachii (TB) muscles are simulated from the onset of force production to muscle fatigue state at various percentages of maximal voluntary contraction (MVC) values. The model is validated using signals recorded from these muscles using well-defined isometric exercise protocols. Root mean square and mean power spectral density values extracted from the simulated and recorded signals are found to increase for TB and decrease for AP with time. A linear variation of the features with %MVC values is obtained for simulated and experimental results. The Bland-Altman plot is used to analyze the agreement between simulated and experimental feature values. Good agreement is obtained for the feature values at various %MVCs. The mean endurance time calculated using the model is found to be comparable to that of the experimental value. This method can be used to generate sEMG signals of different muscles with varying fiber type ratios under various neuromuscular conditions.

Effect of exercise devised to reduce arm tremor in the sighting phase of archery

BACKGROUND

In archery training, side bridges are performed in a posture similar to archery shooting for training the muscles around the shoulder joint and the shoulder girdle of the pusher.

AIM

The purpose of this study was to determine whether a low-tremor side-bridge exercise for 4 weeks improves bow tremor during archery movements.

METHODS

Participants were 20 male college students. First, we measured the tremor during side bridges performed with trunk inclinations of 25°, 40°, 55°, and 70° using an accelerometer attached to the elbow joint and identified low-tremor side bridges. The participants were then randomly divided into intervention and non-intervention groups, and the low-tremor side bridges were performed for 4 weeks.

RESULTS

The effect of the intervention was determined by measuring the total tremor value using an accelerometer attached to the bow and changes in the median power frequency (MdPF) of the middle deltoid, upper trapezius, and lower trapezius. This intervention reduced the bow tremor and the median power frequency of the middle deltoid (p < 0.05).

CONCLUSIONS

The findings suggested that the tremor during the archery sighting phase could be reduced by performing side bridges with a specific trunk angle for a certain period of time. This intervention was also shown to reduce the intermediate frequency of the middle deltoid. The reduced tremor can shorten the sighting phase, which can facilitate injury prevention.

Non-invasive assessment of fatigue and recovery of inspiratory rib cage muscles during endurance test in healthy individuals

INTRODUCTION

Fatigue is defined as loss of capacity to develop muscle force and/or velocity that is reversible at rest. We assessed non-invasively the fatigue and recovery of inspiratory rib cage muscles during two respiratory endurance tests in healthy individuals.

METHODS

The sniff nasal inspiratory pressure (SNIP) was assessed before and after two respiratory endurance tests: normocapnic hyperpnea (NH) and inspiratory pressure threshold loading (IPTL). Contractile (maximum rate of pressure development and time to peak pressure) and relaxation parameters (maximum relaxation rate [MRR], time constant of pressure decay [τ], and half relaxation time) obtained from sniff curves and shortening velocity and mechanical power estimated using optoelectronic plethysmography were analyzed during SNIP maneuvers. Respiratory muscle activity (electromyography) and tissue oxygenation (near-infrared spectroscopy-NIRS) were obtained during endurance tests and SNIP maneuvers. Fatigue development of inspiratory rib cage muscles was assessed according to the slope of decay of median frequency.

RESULTS

Peak pressure during SNIP decreased after both protocols (p <0.05). MRR, shortening velocity, and mechanical power decreased (p <0.05), whereas τ increased after IPTL (p <0.05). The median frequency of inspiratory rib cage muscles (i.e., sum of sternocleidomastoid, scalene, and parasternal) decreased linearly during IPTL and exponentially during NH, mainly due to the sternocleidomastoid.

CONCLUSION

Fatigue development behaved differently between protocols and relaxation properties (MRR and τ), shortening velocity, and mechanical power changed only in the IPTL.

The human neck is part of the musculoskeletal core: cervical muscles help stabilize the pelvis during running and jumping

During locomotion, cervical muscles must be active to stabilize the head as the body accelerates and decelerates. We hypothesized that cervical muscles are also part of the linked chain of axial muscles that provide core stabilization against torques applied to the hip joint by the extrinsic muscles of the legs. To test whether specific cervical muscles play a role in postural stabilization of the head and/or core stabilization of the pelvic girdle, we used surface electromyography to measure changes in muscle activity in response to force manipulations during constant speed running and maximum effort counter-movement jumps. We found that doubling the mass of the head during both running and maximum effort jumping had little or no effect on (1) acceleration of the body and (2) cervical muscle activity. Application of horizontal forward and rearward directed forces at the pelvis during running tripled mean fore and aft accelerations, thereby increasing both the pitching moments on the head and flexion and extension torques applied to the hip. These manipulations primarily resulted in increases in cervical muscle activity that is appropriate for core stabilization of the pelvis. Additionally, when subjects jumped maximally with an applied downward directed force that reduced acceleration and therefore need for cervical muscles to stabilize the head, cervical muscle activity did not decrease. These results suggest that during locomotion, rather than acting to stabilize the head against the effects of inertia, the superficial muscles of the neck monitored in this study help to stabilize the pelvis against torques imposed by the extrinsic muscles of the legs at the hip joint. We suggest that a division of labor may exist between deep cervical muscles that presumably provide postural stabilization of the head versus superficial cervical muscles that provide core stabilization against torques applied to the pelvic and pectoral girdles by the extrinsic appendicular muscles.

A Dynamic Submaximal Fatigue Protocol Alters Wrist Biomechanical Properties and Proprioception

Fatigue is a temporary condition that arises as a result of intense and/or prolonged use of muscles and can affect skilled human performance. Therefore, the quantitative analysis of these effects is a topic of crucial interest in both ergonomics and clinical settings. This study introduced a novel protocol, based on robotic techniques, to quantitatively assess the effects of fatigue on the human wrist joint. A wrist manipulandum was used for two concurrent purposes: (1) implementing the fatigue task and (2) assessing the functional changes both before and at four time points after the end of the fatigue task. Fourteen participants completed the experimental protocol, which included the fatigue task and assessment sessions over 2 days. Specifically, the assessments performed are related to the following indicators: (1) isometric forces, (2) biomechanical properties of the wrist, (3) position sense, and (4) stretch reflexes of the muscles involved. The proposed fatigue task was a short-term, submaximal and dynamic wrist flexion/extension task designed with a torque opposing wrist flexion. A novel task termination criterion was employed and based on a percentage decrease in the mean frequency of muscles measured using surface electromyography. The muscle fatigue analysis demonstrated a change in mean frequency for both the wrist flexors and extensors, however, only the isometric flexion force decreased 4 min after the end of the task. At the same time point, wrist position sense was significantly improved and stiffness was the lowest. Viscosity presented different behaviors depending on the direction evaluated. At the end of the experiment (about 12 min after the end of the fatigue task), wrist position sense recovered to pre-fatigue values, while biomechanical properties did not return to their pre-fatigue values. Due to the wide variety of fatigue tasks proposed in the literature, it has been difficult to define a complete framework that presents the dynamic of fatigue-related changes in different components associated with wrist function. This work enables us to discuss the possible causes and the mutual relationship of the changes detected after the same task.

Skin Sympathetic Nerve Activity and Ventricular Arrhythmias in Acute Coronary Syndrome

BACKGROUND

Acute coronary syndrome (ACS) is major cause of ventricular arrhythmias (VA) and sudden death. neuECG is a non-invasive method to simultaneously measure skin sympathetic nerve activity (SKNA) and electrocardiogram (ECG).

OBJECTIVE

To test the hypotheses that (1) ACS increases the average SKNA (aSKNA), (2) the magnitude of aSKNA elevation is associated with VA during ACS and (3) there is a gender difference of aSKNA in patients without and with ACS.

METHODS

We prospectively studied 128 ACS and 165 control participants. The neuECG was recorded with electrocardiogram (ECG) Lead I configuration at baseline, during mental math stress and during recovery (5-min each). All recordings were done in the morning.

RESULTS

In control group, women have higher aSKNA (μV) than men at baseline (0.82±0.25 vs 0.73±0.20, p=0.009) but not during mental stress (1.21±0.36 vs 1.16±0.36, p=0.394), suggesting women had lower sympathetic reserve. In comparison, ACS is associated with equally elevated aSKNA (μV) in women vs men at baseline (1.14±0.33 vs 1.04±0.35, p=0.531), during mental stress (1.46±0.32 vs 1.33 ±0.37, p=0.113) and during recovery (1.30±0.33 1.11±0.30, p=0.075). After adjusting for age and gender, the adjusted odds ratio for VA including ventricular tachycardia and fibrillation is 1.23 (95% confidence interval 1.05-1.44) for each 0.1 μV elevation of aSKNA. The aSKNA is positively correlated with plasma norepinephrine level.

CONCLUSIONS

ACS is associated with elevated aSKNA and the magnitude of aSKNA elevation is associated with occurrences of VA. Women have higher aSKNA and lower SKNA reserve than men in control but not in ACS patients.

Changes in ankle work, foot work, and tibialis anterior activation throughout a long run

BACKGROUND

The ankle and foot together contribute to over half of the positive and negative work performed by the lower limbs during running. Yet, little is known about how foot kinetics change throughout a run. The amount of negative foot work may decrease as tibialis anterior (TA) electromyography (EMG) changes throughout longer-duration runs. Therefore, we examined ankle and foot work as well as TA EMG changes throughout a changing-speed run.

METHODS

Fourteen heel-striking subjects ran on a treadmill for 58 min. We collected ground reaction forces, motion capture, and EMG. Subjects ran at 110%, 100%, and 90% of their 10-km running speed and 2.8 m/s multiple times throughout the run. Foot work was evaluated using the distal rearfoot work, which provides a net estimate of all work contributors within the foot.

RESULTS

Positive foot work increased and positive ankle work decreased throughout the run at all speeds. At the 110% 10-km running speed, negative foot work decreased and TA EMG frequency shifted lower throughout the run. The increase in positive foot work may be attributed to increased foot joint work performed by intrinsic foot muscles. Changes in negative foot work and TA EMG frequency may indicate that the TA plays a role in negative foot work in the early stance of a run.

CONCLUSION

This study is the first to examine how the kinetic contributions of the foot change throughout a run. Future studies should investigate how increases in foot work affect running performance.

The Pre-Exhaustion Method Does Not Increase Muscle Activity in Target Muscle During Strength Training in Untrained Individuals

This study investigated the effects of the pre-exhaustion method on electromyographic activity (root mean square and median frequency) at different interval sets. Twenty adults with little or no experience in strength training performed the seated row exercise until muscular failure, with or without completing a previous pre-exhaustion set in a pullover exercise. Surface electrodes were placed over the latissimus dorsi, teres major, biceps brachii, and posterior deltoid muscles of the dominant side. The results showed no effect of pre-exhaustion on EMG activity of latissimus dorsi target muscle for any interval sets. Regarding median frequency, our results showed a consistent decrease throughout the sets (p>0.05). Also, our results revealed a decrease in posterior deltoid median frequency with pre-exhaustion (p=0.001). We conclude that the pre-exhaustion method seems ineffective in increasing the EMG activity of the desired muscle throughout all repetitions of strength training. Furthermore, pre-exhaustion seems to be a good way to increase fatigue in the posterior deltoid muscle.

An EMG-Based Constitutive Law for Force Generation in Skeletal Muscle - Part II: Model Validation On the Ankle Joint Complex

This study evaluates the predictive ability of the skeletal muscle force model derived previously within the ankle joint complex. The model is founded in dimensional analysis, using electromyography and the muscle force-length, force-velocity, and force-frequency curves as inputs. Seventeen subjects (8 males, 9 females) performed five different exercises that activated the primary muscles crossing the ankle joint. Motion capture, force plate, and electromyography data were collected during these exercises. A constant, Km, was calculated for each muscle of each subject using four of the five exercises. The fifth exercise was used to validate the results by treating the moments due to muscle forces as known and all other components in Euler's second law as unknown. While muscle forces cannot be directly validated in vivo, methods can be developed to test these values with reasonable confidence. This study compared moments about the ankle joint due to the calculated muscle forces to the sum of the moments due to all other sources and the kinematic terms in the second Newton-Euler equation of rigid body motion. Average percent errors for each subject ranged from 4.2% to 15.5% with an average percent error across all subjects of 8.2% while maximum percent errors for each subject ranged from 33.3% to 78.0% with an overall average maximum of 52.4%. Future work will examine sensitivity analyses to identify potential simplifications to the model and solution process and will validate the model on a more complex joint.

Effects of a thorstensson fatiguing protocol on isometric and isokinetic performance

OBJECTIVE: Having participants perform 50 maximal isokinetic contractions, as introduced by Thorstensson and Karlsson (1976), is to this day one of the most commonly used fatigue protocols. Purpose: To determine to what extent a Thorstensson fatiguing protocol affects isokinetic and isometric performance characteristics. METHODS: Twenty-five college-aged men performed an isokinetic fatigue protocol consisting of 50 maximal elbow flexions at a moderate speed (180∘⋅s-1). Pre- and post-tests were used to calculate fatigue indices (FI%) for the following variables: isometric and isokinetic peak torque (PT), isometric rate of torque development (RTD), and maximum acceleration (ACCmax). RESULTS: Each of the four dependent variables significantly decreased with fatigue (each demonstrated p< 0.001), but not of the same magnitude. Isometric PT FI (-18.7%) was significantly less than isokinetic PT FI (-45.1%, p⩽ 0.001) and ACCmax FI (-26.3%) was significantly less than isometric RTD FI (-54.9%, p⩽ 0.001). There was a significant positive relationship between isometric and isokinetic PT FI% (r= 0.60, p< 0.002) as well as between isometric PT FI% and RTD FI% (r= 0.40, p< 0.046). There was no significant relationship observed between RTD FI% and ACCmax FI% nor between isokinetic PT FI% and ACCmax FI%. CONCLUSIONS: This investigation observed different patterns of response in maximal strength between isometric and isokinetic assessments following a isokinetic fatigue protocol. Additionally, the ability to rapidly generate strength and velocity had significantly different responses to fatigue between isometric and dynamic assessments. Due to these different responses, we recommend that assessments of fatigue at least include the same testing modality as the modality of the fatigue protocol.

Frequency Shifts in Muscle Activation during Static Strength Elements on the Rings before and after an Eccentric Training Intervention in Male Gymnasts

During ring performance in men's gymnastics, static strength elements require a high level of maximal muscular strength. The aim of the study was to analyze the effect of a four-week eccentric-isokinetic training intervention in the frequency spectra of the wavelet-transformed electromyogram (EMG) during the two static strength elements, the swallow and support scale, in different time intervals during the performance. The gymnasts performed an instrumented movement analysis on the rings, once before the intervention and twice after. For both elements, the results showed a lower congruence in the correlation of the frequency spectra between the first and the last 0.5 s interval than between the first and second 0.5 s intervals, which was indicated by a shift toward the predominant frequency around the wavelet with a center frequency of 62 Hz (Wavelet W10). Furthermore, in both elements, there was a significant increase in the congruence of the frequency spectra after the intervention between the first and second 0.5 s intervals, but not between the first and last ones. In conclusion, the EMG wavelet spectra presented changes corresponding to the performance gain with the eccentric training intervention, and showed the frequency shift toward a predominant frequency due to acute muscular fatigue.

Shoulder electromyography-based indicators to assess manifestation of muscle fatigue during laboratory-simulated manual handling task

Muscle fatigue is a risk factor for developing shoulder musculoskeletal disorders. The aim of this study was to identify shoulder electromyographic indicators that are most indicative of muscle fatigue during a laboratory simulated manual handling task. Thirty-two participants were equipped with electromyographic electrodes on 10 shoulder muscles and moved boxes for 45-minutes. The modified rate of perceived exertion (mRPE) was assessed every 5-minutes and multivariate linear regressions were performed between myoelectric manifestation of fatigue (MMF) and the mRPE scores. During a manual handling task representative of industry working conditions, spectral entropy, median frequency, and mobility were the electromyographic indicators that explained the largest percentage of the mRPE. Overall, the deltoids, biceps and upper trapezius were the muscles that most often showed significant changes over time in their electromyographic indicators. The combination of these three indicators may improve the accuracy for the assessment of MMF during manual handling. Practitioner Summary: To date, muscle fatigue has primarily been assessed during tasks done to exhaustion, which are not representative of typical working conditions. During a manual handling task representative of industry working conditions, EMG-derived spectral entropy, and median frequency, both extracted from time-frequency analysis, and mobility extracted from time domain, were the best indicators of the manifestation of muscle fatigue.

Immediate effects of elongation training using an elastic band on the hip abductor muscles

[Purpose] This study investigated the effects of elongation training on the hip abductor muscles in comparison with the effects of general hip abductor training. [Participants and Methods] This study included 39 healthy male university students. The participants were divided into elongation training and general-weighted hip abduction training groups. An elastic band was used for elongation training, and hip abduction exercises were performed with instructions to extend the foot as far as possible to stretch the band. Measurements were taken before and after training, and the surface electromyographic data of the gluteus medius and the tensor fasciae latae were measured during isometric contraction of the hip abductor muscles. The surface electromyogram data were used to calculate integral values and median power frequencies to compare the effects of training. [Results] In comparison with general hip abductor training, elongation training yielded a larger change in the ratio of muscle integral values (gluteus medius/tensor fasciae latae). [Conclusion] Elongation training of the hip abductor muscles was more useful than general training in increasing the activity of the gluteus medius while suppressing the activity of the tensor fasciae latae.

Effects of Various Physical Interventions on Reducing Neuromuscular Fatigue Assessed by Electromyography: A Systematic Review and Meta-Analysis

Introduction: Various interventions have been applied to improve recovery from muscle fatigue based on evidence from subjective outcomes, such as perceived fatigue and soreness, which may partly contribute to conflicting results of reducing muscle fatigue. There is a need to assess the effectiveness of various intervention on reducing neuromuscular fatigue assessed by a quantitative outcome, such as electromyography (EMG). The objective of this review and meta-analysis was to evaluate the effectiveness of different interventions and intervention timing for reducing fatigue rates during exercise. Methods: The literature was searched from the earliest record to March 2021. Eighteen studies with a total of 87 data points involving 281 participants and seven types of interventions [i.e., active recovery (AR), compression, cooling, electrical stimulation (ES), light-emitting diode therapy (LEDT), massage, and stretching] were included in this meta-analysis. Results: The results showed that compression (SMD = 0.28; 95% CI = -0.00 to 0.56; p = 0.05; I ² = 58%) and LEDT (SMD = 0.49; 95% CI = 0.11 to 0.88; p = 0.01; I ² = 52%) have a significant recovery effect on reducing muscle fatigue. Additionally, compression, AR, and cooling have a significant effect on reducing muscle fatigue when conducted during exercise, whereas a non-effective trend when applied after exercise. Discussion: This meta-analysis suggests that compression and LEDT have a significant effect on reducing muscle fatigue. The results also suggest that there is a significant effect or an effective trend on reducing muscle fatigue when compression, AR, cooling, and ES are applied during exercise, but not after exercise.

Recovery and Fatigue Behavior of Forearm Muscles during a Repetitive Power Grip Gesture in Racing Motorcycle Riders

Despite a reduction in the maximal voluntary isometric contraction (MVC_isom) observed systematically in intermittent fatigue protocols (IFP), decrements of the median frequency, assessed by surface electromyography (sEMG), has not been consistently verified. This study aimed to determine whether recovery periods of 60 s were too long to induce a reduction in the normalized median frequency (MF_EMG) of the flexor digitorum superficialis and carpi radialis muscles. Twenty-one road racing motorcycle riders performed an IFP that simulated the posture and braking gesture on a motorcycle. The MVC_isom was reduced by 53% (p < 0.001). A positive and significant relationship (p < 0.005) was found between MF_EMG and duration of the fatiguing task when 5 s contractions at 30% MVC_isom were interspersed by 5 s recovery in both muscles. In contrast, no relationship was found (p > 0.133) when 10 s contractions at 50% MVC were interspersed by 1 min recovery. Comparative analysis of variance (ANOVA) confirmed a decrement of MF_EMG in the IFP at 30% MVC_isom including short recovery periods with a duty cycle of 100% (5 s/5 s = 1), whereas no differences were observed in the IFP at 50% MVC_isom and longer recovery periods, with a duty cycle of 16%. These findings show that recovery periods during IFP are more relevant than the intensity of MVC_isom. Thus, we recommend the use of short recovery periods between 5 and 10 s after submaximal muscle contractions for specific forearm muscle training and testing purposes in motorcycle riders.

Muscle Fatigue When Riding a Motorcycle: A Case Study

This case study was conducted to assess muscle pattern, as measured by surface electromyography (sEMG), and its changes during a controlled superbike closed-road track training session. The sEMG signals were recorded unilaterally from biceps brachii (BB), triceps brachii (TB), anterior and posterior part of the deltoid (DA and DP respectively), flexor digitorum superficialis (FS), extensor carpi radialis (CR), extensor digitorum communis (ED) and pectoralis major (PM) during three rounds of 30 min. sEMG signals selected for analysis came from the beginning of the braking action to the way-out of the curves of interest. Considering the laps and rounds as a whole and focusing on the forearm muscles, ED was more systematically (84%) assigned to a state of fatigue than FS (44%) and CR (39%). On the opposite, the TB and DP muscles showed a predominant state of force increase (72%). Whereas the BB showed alternatively a state of fatigue or force increase depending on the side of the curve, when taking into account only the sharpest curves, it showed a predominant state of force increase. In conclusion, the fact that forearm muscles must endure a long-lasting maintenance of considerable activity levels explains why they easily got into a state of fatigue. Moreover, TB and DA are particularly relevant when cornering.

Muscle Fiber Conduction Velocity Correlates With the Age at Onset in Mild FSHD Cases

A majority of patients with facioscapulohumeral muscular dystrophy (FSHD) report severe fatigue. The aim of this study was to explore whether fatigability during a performance task is related to the main clinical features of the disease in mildly affected patients. A total of 19 individuals with a molecular genetic-based diagnosis of FSHD (median D4Z4 deletion length of 27 kb) performed two isometric flexions of the dominant biceps brachii at 20% of their maximal voluntary contraction (MVC) for 2 min, and then at 60% MVC until exhaustion. Fatigability indices (average rectified value, mean frequency, conduction velocity, and fractal dimension) were extracted from the surface electromyogram (sEMG) signal, and their correlations with age, age at onset, disease duration, D4Z4 contraction length, perceived fatigability, and clinical disability score were analyzed. The conduction velocity during the low level contraction showed a significant negative correlation with the age at onset (p < 0.05). This finding suggest the assessment of conduction velocity at low isometric contraction intensities, as a potential useful tool to highlight differences in muscle involvement in FSHD patients.

Changes in electromyographic activity, mechanical power, and relaxation rates following inspiratory ribcage muscle fatigue

Muscle fatigue is a complex phenomenon enclosing various mechanisms. Despite technological advances, these mechanisms are still not fully understood in vivo. Here, simultaneous measurements of pressure, volume, and ribcage inspiratory muscle activity were performed non-invasively during fatigue (inspiratory threshold valve set at 70% of maximal inspiratory pressure) and recovery to verify if inspiratory ribcage muscle fatigue (1) leads to slowing of contraction and relaxation properties of ribcage muscles and (2) alters median frequency and high-to-low frequency ratio (H/L). During the fatigue protocol, sternocleidomastoid showed the fastest decrease in median frequency and slowest decrease in H/L. Fatigue was also characterized by a reduction in the relative power of the high-frequency and increase of the low-frequency. During recovery, changes in mechanical power were due to changes in shortening velocity with long-lasting reduction in pressure generation, and slowing of relaxation [i.e., tau (τ), half-relaxation time (½RT), and maximum relaxation rate (MRR)] was observed with no significant changes in contractile properties. Recovery of median frequency was faster than H/L, and relaxation rates correlated with shortening velocity and mechanical power of inspiratory ribcage muscles; however, with different time courses. Time constant of the inspiratory ribcage muscles during fatigue and recovery is not uniform (i.e., different inspiratory muscles may have different underlying mechanisms of fatigue), and MRR, ½RT, and τ are not only useful predictors of inspiratory ribcage muscle recovery but may also share common underlying mechanisms with shortening velocity.

Hand motion strength forecasting using Extreme Learning Machine for post-stroke rehabilitation

Stroke or Cerebrovascular accident (CVA) can cause weakness in one side of the body, including the upper limbs such as the hand. Rehabilitation is needed to restore the function of the hand. Rehabilitation should also measure the strength of the movements carried out. This article aims to forecast the strength of movement based on Electromyography (EMG) signals using the Extreme Learning Machine (ELM). This study collected EMG signal data and movement strength, carried out data pre-processing and data extraction using various extraction features, applied ELM for forecasting strength based on EMG signals, and applied created models in stroke therapy robots. The forecasting model is evaluated by measuring the Mean Squared Error (MSE). The average value of the best MSE in offline testing is 1.77, while the real-time testing is 0.79. A small MSE value indicates that the model is good enough. The resulted value of strength can be applied to make the stroke therapy robots actuating properly.

Fatigue induces altered spatial myoelectric activation patterns in the medial gastrocnemius during locomotion

This research investigates the effects of muscle fatigue on spatial myoelectric patterns in the lower limb during locomotion. Both spatial and frequency aspects of neuromuscular recruitment in the medial gastrocnemius change in response to fatigue, resulting in altered myoelectric patterns during walking and running. These data may help us better understand the adaptations that occur in lower limb muscles to avoid overuse injuries caused by fatigue.

Systematic Review of Fatigue in Individuals With Cerebral Palsy

In this systematic review, we collected and analyzed literature works comparing self-reported fatigue and objectively-measured fatigue in individuals with cerebral palsy (CP) and in age-matched typically developing/typically developed (TD) controls (Healthy). The search was conducted on four electronic databases/platforms (PubMed, Web of Science, Cochrane Library, and Scopus) using the key words “cerebral palsy” combined with “fatig^*,” where the asterisk was used as a wildcard. As a critical appraisal tool, the Joanna Briggs Institute Critical Appraisal Checklist for Quasi-Experimental Studies (2017) was used. A total of 22 studies passed the critical appraisal rating and were included in both narrative and quantitative analyses. The overall evidence quality of the findings was considered very good. Data of objectively-measured fatigue in performing maximal fatiguing tasks indicated lower fatigue levels in participants with CP, possibly due to their pathological inability to recruit highly fatigable muscle fibers. Highly trained individuals with CP and TD controls performing maximal fatiguing tasks seem to be an exception to this, as they exhibited similar levels of fatigue. In submaximal fatiguing tasks, including daily physical activities, either objectively-measured or self-reported fatigue was higher in participants with CP than in TD controls, indicating a lower ability for development of neurophysiological compensation for fatigue among participants with CP. Further studies on fatigue are needed to gain an insight into the multifold mechanisms of fatigue in individuals with CP. Understanding fatigue mechanisms could help in setting up strategies for effective intervention programs, with benefits in healthcare and improved quality of life of individuals with CP.

Systematic Review Registration: [PROSPERO 2019], identifier [CRD42019143524].

Increased resistance towards fatigability in patients with facioscapulohumeral muscular dystrophy

PURPOSE

In facioscapulohumeral muscular dystrophy (FSHD) fatigue is a major complaint. We aimed to investigate whether during isometric sustained elbow flexions, performance fatigability indexes differ in patients with FSHD with respect to healthy controls.

METHODS

Seventeen patients with FSHD and seventeen healthy controls performed two isometric flexions of the dominant biceps brachii at 20% of their maximal voluntary contraction (MVC) for 2 min and then at 60% MVC until exhaustion. Muscle weakness was characterized as a percentage of predicted values. Maximal voluntary strength, endurance time and performance fatigability indices (mean frequency of the power spectrum (MNF), muscle fiber conduction velocity (CV) and fractal dimension (FD)), extracted from the surface electromyogram signal (sEMG) were compared between the two groups.

RESULTS

In patients with FSHD, maximal voluntary strength was 68.7% of predicted value (p < 0.01). Compared to healthy controls, FSHD patients showed reduced MVC (p < 0.001; r = 0.62) and lower levels of performance fatigability, characterized by reduced rate of changes in MNF (p < 0.01; r = 0.56), CV (p < 0.05; 0.37) and FD (p < 0.001; r = 0.51) and increased endurance time (p < 0.001; r = 0.63), during the isometric contraction at 60% MVC.

CONCLUSION

A decreased reduction in the slopes of all the considered sEMG parameters during sustained isometric elbow flexions suggests that patients with FSHD experience lower levels of performance fatigability compared to healthy controls.

Next-Generation Wearable Biosensors Developed with Flexible Bio-Chips

The development of biosensors that measure various biosignals from our body is an indispensable research field for health monitoring. In recent years, as the demand to monitor the health conditions of individuals in real time have increased, wearable-type biosensors have received more attention as an alternative to laboratory equipment. These biosensors have been embedded into smart watches, clothes, and accessories to collect various biosignals in real time. Although wearable biosensors attached to the human body can conveniently collect biosignals, there are reliability issues due to noise generated in data collection. In order for wearable biosensors to be more widely used, the reliability of collected data should be improved. Research on flexible bio-chips in the field of material science and engineering might help develop new types of biosensors that resolve the issues of conventional wearable biosensors. Flexible bio-chips with higher precision can be used to collect various human data in academic research and in our daily lives. In this review, we present various types of conventional biosensors that have been used and discuss associated issues such as noise and inaccuracy. We then introduce recent studies on flexible bio-chips as a solution to these issues.

Future Directions and Considerations for Talent Identification in Australian Football

As the focus on the elite Australian Football League competition becomes greater so too does the demand for success. Clubs are heavily scrutinized for their draft selections and as such are taking more interest in the younger levels of competition in an attempt to identify and monitor talent. Based on contemporary talent identification knowledge, this review examines the current talent identification process in Australian football, with a focus on areas to potentially improve or inform future developments. Currently, a significant gap exists between static and isolated assessment procedures used to identify talent in Australian football and the dynamic nature of match play. Future assessments should consider factors such as maturation, fatigue and ecological dynamics. The addition of a valid and reliable technical skill assessment (e.g., a small-sided game) to the current Australian Football League draft combine was recommended.

Functional evaluation of triceps surae during heel rise test: from EMG frequency analysis to machine learning approach

Soleus muscle flap as coverage tissue is a possible surgical solution adopted to cover the wounds due to open fractures. Despite this procedure presents many clinical advantages, relatively poor information is available about the loss of functionality of triceps surae of the treated leg. In this study, a group of patients who underwent a soleus muscle flap surgical procedure has been analyzed through the heel rise test (HRT), in order to explore the triceps surae residual functionalities. A frequency band analysis was performed in order to assess whether the residual heads of triceps surae exhibit different characteristics with respect to both the non-treated lower limb and an age-matched control group. Then, an in-depth analysis based on a machine learning approach was proposed for discriminating between groups by generalizing across new unseen subjects. Experimental results showed the reliability of the proposed analyses for discriminating between-group at a specific time epoch and the high interpretability of the proposed machine learning algorithm allowed the temporal localization of the most discriminative frequency bands. Findings of this study highlighted that significant differences can be recognized in the myoelectric spectral characteristics between the treated and contralateral leg in patients who underwent soleus flap surgery. These experimental results may support the clinical decision-making for assessing triceps surae performance and for supporting the choice of treatment in plastic and reconstructive surgery. Graphical Abstract The Graphical abstract presents the scope of the proposed analysis of myoelectric signals of soleus and gastrocnemius muscles of patiens groups during Hell Rise Test, highlighting the applied methods and the obtained results.

Parylene-Based Flexible Microelectrode Arrays for the Electrical Recording of Muscles and the Effect of Electrode Size

Miniaturized flexible microelectrode arrays are desirable for small-area surface electromyography (sEMG) to detect the electrical activity generated by muscles in a specific area of the body. Here, we present a flexible 8-channel microelectrode array with electrodes of diameter 150–300 μm for small-area sEMG recordings. The microelectrode arrays based on a flexible Parylene C substrate recorded the sEMG signals from a curved skin surface with a maximum signal-to-noise ratio (SNR) of 21.4 dB. The sEMG signals recorded from a small area of 17671–59325 μm2 showed a clear distinction between the signal and noise. Further, the sEMG data were analyzed in the frequency domain by converting the signals via fast Fourier transform (FFT), and it was verified that the proposed microelectrode could reliably record multichannel sEMGs over a small area. Moreover, a maximum voluntary contraction (MVC) experiment was performed to confirm the recording capability of the microelectrode array, which showed consistency with the previous reports. Finally, we demonstrated the effects of the electrode size by comparing the results for two different electrode sizes. When the electrode size was increased 3.37 times, the root-mean-square value of the amplitude (Vrms) increased 2.64 times, consequently increasing the SNR from 16.9 to 21.4 dB. This study demonstrates the expanded utility of Parylene-based flexible microelectrode arrays.

EMG-Centered Multisensory Based Technologies for Pattern Recognition in Rehabilitation: State of the Art and Challenges

In the field of rehabilitation, the electromyography (EMG) signal plays an important role in interpreting patients' intentions and physical conditions. Nevertheless, utilizing merely the EMG signal suffers from difficulty in recognizing slight body movements, and the detection accuracy is strongly influenced by environmental factors. To address the above issues, multisensory integration-based EMG pattern recognition (PR) techniques have been developed in recent years, and fruitful results have been demonstrated in diverse rehabilitation scenarios, such as achieving high locomotion detection and prosthesis control accuracy. Owing to the importance and rapid development of the EMG centered multisensory fusion technologies in rehabilitation, this paper reviews both theories and applications in this emerging field. The principle of EMG signal generation and the current pattern recognition process are explained in detail, including signal preprocessing, feature extraction, classification algorithms, etc. Mechanisms of collaborations between two important multisensory fusion strategies (kinetic and kinematics) and EMG information are thoroughly explained; corresponding applications are studied, and the pros and cons are discussed. Finally, the main challenges in EMG centered multisensory pattern recognition are discussed, and a future research direction of this area is prospected.

Driving Drowsiness Detection with EEG Using a Modified Hierarchical Extreme Learning Machine Algorithm with Particle Swarm Optimization: A Pilot Study

Driving fatigue accounts for a large number of traffic accidents in modern life nowadays. It is therefore of great importance to reduce this risky factor by detecting the driver’s drowsiness condition. This study aimed to detect drivers’ drowsiness using an advanced electroencephalography (EEG)-based classification technique. We first collected EEG data from six healthy adults under two different awareness conditions (wakefulness and drowsiness) in a virtual driving experiment. Five different machine learning techniques, including the K-nearest neighbor (KNN), support vector machine (SVM), extreme learning machine (ELM), hierarchical extreme learning machine (H-ELM), and the proposed modified hierarchical extreme learning machine algorithm with particle swarm optimization (PSO-H-ELM), were applied to classify the subject’s drowsiness based on the power spectral density (PSD) feature extracted from the EEG data. The mean accuracies of the five classifiers were 79.31%, 79.31%, 74.08%, 81.67%, and 83.12%, respectively, demonstrating the superior performance of our new PSO-H-ELM algorithm in detecting drivers’ drowsiness, compared to the other techniques.

Complexity Analysis of Surface Electromyography for Assessing the Myoelectric Manifestation of Muscle Fatigue: A Review

The surface electromyography (sEMG) records the electrical activity of muscle fibers during contraction: one of its uses is to assess changes taking place within muscles in the course of a fatiguing contraction to provide insights into our understanding of muscle fatigue in training protocols and rehabilitation medicine. Until recently, these myoelectric manifestations of muscle fatigue (MMF) have been assessed essentially by linear sEMG analyses. However, sEMG shows a complex behavior, due to many concurrent factors. Therefore, in the last years, complexity-based methods have been tentatively applied to the sEMG signal to better individuate the MMF onset during sustained contractions. In this review, after describing concisely the traditional linear methods employed to assess MMF we present the complexity methods used for sEMG analysis based on an extensive literature search. We show that some of these indices, like those derived from recurrence plots, from entropy or fractal analysis, can detect MMF efficiently. However, we also show that more work remains to be done to compare the complexity indices in terms of reliability and sensibility; to optimize the choice of embedding dimension, time delay and threshold distance in reconstructing the phase space; and to elucidate the relationship between complexity estimators and the physiologic phenomena underlying the onset of MMF in exercising muscles.

A Smart Terrain Identification Technique Based on Electromyography, Ground Reaction Force, and Machine Learning for Lower Limb Rehabilitation

Automatic terrain classification in lower limb rehabilitation systems has gained worldwide attention. In this field, a simple system architecture and high classification accuracy are two desired attributes. In this article, a smart neuromuscular–mechanical fusion and machine learning-based terrain classification technique utilizing only two electromyography (EMG) sensors and two ground reaction force (GRF) sensors is reported for classifying three different terrains (downhill, level, and uphill). The EMG and GRF signals from ten healthy subjects were collected, preprocessed and segmented to obtain the EMG and GRF profiles in each stride, based on which twenty-one statistical features, including 9 GRF features and 12 EMG features, were extracted. A support vector machine (SVM) machine learning model is established and trained by the extracted EMG features, GRF features and the fusion of them, respectively. Several methods or statistical metrics were used to evaluate the goodness of the proposed technique, including a paired-t-test and Kruskal–Wallis test for correlation analysis of the selected features and ten-fold cross-validation accuracy, confusion matrix, sensitivity and specificity for the performance of the SVM model. The results show that the extracted features are highly correlated with the terrain changes and the fusion of the EMG and GRF features produces the highest accuracy of 96.8%. The presented technique allows simple system construction to achieve the precise detection of outcomes, potentially advancing the development of terrain classification techniques for rehabilitation.

Selecting the appropriate input variables in a regression approach to estimate actively generated muscle moments around L5/S1 for exoskeleton control

Back support exoskeletons are designed to prevent work-related low-back pain by reducing mechanical loading. For actuated exoskeletons, support based on moments actively produced by the trunk muscles appears a viable approach. The moment can be estimated by a biomechanical model. However, one of the main challenges here is the feasibility of recording the required input variables (kinematics, EMG data, ground reaction forces) to run the model. The aim of this study was to evaluate how accurate different selections of input variables can estimate actively generated moments around L5/S1. Different multivariate regression analyses were performed using a dataset consisting of spinal load, body kinematics and trunk muscle activation levels during different lifting conditions with and without an exoskeleton. The accuracy of the resulting models depended on the number and type of input variables and the regression model order. The current study suggests that third-order polynomial regression of EMG signals of one or two bilateral back muscle pairs together with exoskeleton trunk and hip angle suffices to accurately estimate the actively generated muscle moment around L5/S1, and thereby design a proper control system for back support exoskeletons.

Upper and lower limb performance fatigability in people with multiple sclerosis investigated through surface electromyography: a pilot study

OBJECTIVE

Fatigue experienced by people with multiple sclerosis (pwMS) is multidimensional, consisting of different components, such as perceived, physical and cognitive fatigue and performance fatigability. At present, there is no gold standard to assess performance fatigability in pwMS; therefore, we aimed to determine whether, during a fatiguing task, average rectified value (ARV), mean frequency of the power spectrum (MNF), muscle fiber conduction velocity (CV) and fractal dimension (FD) of surface electromyography (sEMG) may be used as indirect indices of performance fatigability. Moreover, we analyzed whether a three-week rehabilitation program impacts on performance fatigability in pwMS, and whether a relationship between sEMG parameters and trait levels of perceived fatigability, before and after rehabilitation, does exist.

APPROACH

Twenty-one pwMS performed a 20% maximal voluntary contraction (MVC) of 1 min, and afterwards a 60% MVC held until exhaustion. sEMG signals were detected from the biceps brachii, vastus medialis and vastus lateralis. Performance fatigability was determined at entry to (t ₀) and discharge from (t ₁) rehabilitation. Perceived fatigability was measured at t ₀ and t ₂, one month after rehabilitation.

MAIN RESULTS

ARV, MNF, CV and FD rates of change showed significant changes at t ₀ and t ₁ (p  <  0.05) during the high-level contraction in the BB, but rather limited in the vastii muscles. Moreover, rehabilitation did not induce any reductions in either perceived or performance fatigability. No significant correlations between ARV, MNF, CV and FD rates of change during the 60% MVC and perceived fatigability, at t ₀ and t ₂, were found.

SIGNIFICANCE

Our findings suggest that the sEMG parameters are useful for indirectly assessing performance fatigability in pwMS during sub-maximal fatiguing contractions, particularly in the biceps brachii.

Muscle fiber typology substantially influences time to recover from high-intensity exercise

Human fast-twitch muscle fibers generate high power in a short amount of time but are easily fatigued, whereas slow-twitch fibers are more fatigue resistant. The transfer of this knowledge to coaching is hampered by the invasive nature of the current evaluation of muscle typology by biopsies. Therefore, a noninvasive method was developed to estimate muscle typology through proton magnetic resonance spectroscopy in the gastrocnemius. The aim of this study was to investigate whether male subjects with an a priori-determined fast typology (FT) are characterized by a more pronounced Wingate exercise-induced fatigue and delayed recovery compared with subjects with a slow typology (ST). Ten subjects with an estimated higher percentage of fast-twitch fibers and 10 subjects with an estimated higher percentage of slow-twitch fibers underwent the test protocol, consisting of three 30-s all-out Wingate tests. Recovery of knee extension torque was evaluated by maximal voluntary contraction combined with electrical stimulation up to 5 h after the Wingate tests. Although both groups delivered the same mean power across all Wingates, the power drop was higher in the FT group (−61%) compared with the ST group (−41%). The torque at maximal voluntary contraction had fully recovered in the ST group after 20 min, whereas the FT group had not yet recovered 5 h into recovery. This noninvasive estimation of muscle typology can predict the extent of fatigue and time to recover following repeated all-out exercise and may have applications as a tool to individualize training and recovery cycles.

NEW & NOTEWORTHY A one-fits-all training regime is present in most sports, though the same training implies different stimuli in athletes with a distinct muscle typology. Individualization of training based on this muscle typology might be important to optimize performance and to lower the risk for accumulated fatigue and potentially injury. When conducting research, one should keep in mind that the muscle typology of participants influences the severity of fatigue and might therefore impact the results.

Muscle endurance time estimation during isometric training using electromyogram and supervised learning

Constant-force isometric muscle training is useful for increasing the maximal strength , rehabilitation and work-fatigue assessment. Earlier studies have shown that muscle fatigue characteristics can be used for evaluating muscle endurance limit.

STUDY OBJECTIVE

To predict muscle endurance time during isometric task using frequency spectrum characteristics of surface electromyography signals along with analysis of frequency spectrum shape and scale during fatigue accumulation.

METHOD

Thirteen subjects performed isometric lateral raise at 60% MVC of deltoid (lateral) till endurance limit. Time windowed sEMG frequency spectrum was modelled using 2-parameter distributions namely Gamma and Weibull for spectrum analysis and endurance prediction.

RESULTS

Gamma distribution provided better spectrum fitting (P < 0.001) than Weibull distribution. Spectrum Distribution demonstrated no change in shape but shifted towards lower frequency with increase of magnitude at characteristic mode frequency. Support Vector Regression based algorithm was developed for endurance time estimation using features derived from fitted frequency spectrum. Time taken till endurance limit for acquired dataset 38.53 ± 17.33 s (Mean ± Standard Deviation) was predicted with error of 0.029 ± 4.19 s . R-square: 0.956, training and test sets RMSE was calculated as 3.96 and 4.29 s respectively. The application of the algorithm suggested that model required 70% of sEMG signal from maximum time of endurance for high prediction accuracy.

CONCLUSION

Endurance Limit prediction algorithm was developed for quantification of endurance time for optimizing isometric training and rehabilitation. Our method could help personalize and change conventional training method of same weight and duration for all subjects with optimized training parameters, based upon individual sEMG activity.

Study on the Recognition of Exercise Intensity and Fatigue on Runners Based on Subjective and Objective Information

A running exhaustion experiment was used to explore the correlations between the time-frequency domain indexes extracted from the surface electromyography (EMG) signals of targeted muscles, heart rate and exercise intensity, and subjective fatigue. The study made further inquiry into the feasibility of reflecting and evaluating the exercise intensity and fatigue effectively during running using physiological indexes, thus providing individualized guidance for running fitness. Twelve healthy men participated in a running exhaustion experiment with an incremental and constant load. The percentage of heart rate reserve (%HRR), mean power frequency (MPF) and root mean square (RMS) from surface EMG (sEMG) signals of the rectus femoris (RF), biceps femoris (BF), tibialis anterior muscle (TA), and the lateral head of gastrocnemius (GAL) were obtained in real-time. The data were processed and analyzed with the rating of perceived exertion (RPE) scale. The experimental results show that the MPF on all the muscles increased with time, but there was no significant correlation between MPF and RPE in both experiments. Additionally, there was no significant correlation between RMS and RPE of GAL and BF, but there was a negative correlation between RMS and RPE of RF. The correlation coefficient was lower in the constant load mode, with the value of only −0.301. The correlation between RMS and RPE of TA was opposite in both experiments. There was a significant linear correlation between %HRR and exercise intensity (r = 0.943). In the experiment, %HRR was significantly correlated with subjective exercise fatigue (r = 0.954). Based on the above results, the MPF and RMS indicators on the four targeted muscles could not conclusively identify fatigue of lower extremities during running. The %HRR could be used to identify exercise intensity and human fatigue during running and could be used as an indicator of recognizing fatigue and exercise intensity in runners.