Point:Counterpoint: Spectral properties of the surface EMG can characterize/do not provide information about motor unit recruitment strategies and muscle fiber type

Dynamics of cardio-muscular networks in exercise and fatigue

A fundamental question in cardiovascular and muscle physiology is how the heart operates in synchrony with distinct muscles to regulate homeostasis, enable movement and adapt to exercise demands and fatigue. Here we investigate how autonomic regulation of cardiac function synchronizes and integrates as a network with the activity of distinct muscles during exercise. Further, we establish how the network of cardio-muscular interactions reorganizes with fatigue. Thirty healthy young adults performed two body weight squat tests until exhaustion. Simultaneous recordings were taken of a 3-lead electrocardiogram (EKG) along with electromyography (EMG) signals from the left and right vastus lateralis, and left and right erector spinae. We first obtained instantaneous heart rate (HR) derived from the EKG signal and decomposed the EMG recordings in 10 frequency bands (F1-F10). We next quantified pair-wise coupling (cross-correlation) between the time series for HR and all EMG spectral power frequency bands in each leg and back muscle. We uncovered the first profiles of cardio-muscular network interactions, which depend on the role muscles play during exercise and muscle fibre histochemical characteristics. Additionally, we observed a significant decline in the degree of cardio-muscular coupling with fatigue, characterized by complex transitions from synchronous to asynchronous behaviour across a range of timescales. The network approach we utilized introduces new avenues for the development of novel network-based markers, with the potential to characterize multilevel cardio-muscular interactions to assess global health, levels of fatigue, fitness status or the effectiveness of cardiovascular and muscle injury rehabilitation programmes. KEY POINTS: The heart operates in synchrony with muscles to regulate homeostasis, enable movement, and adapt to exercise demands and fatigue. However, the precise mechanisms regulating cardio-muscular coupling remain unknown. This study introduces a pioneering approach to assess cardio-muscular network interactions by examining the synchronization of cardiac function with muscle activity during exercise and fatigue. We uncover the first profiles of cardio-muscular interactions characterized by specific hierarchical organization of link strength. We observe a significant decline in the degree of cardio-muscular coupling with fatigue, marked by complex transitions from synchronous to asynchronous behaviour. This network approach offers new network-based markers to characterize multilevel cardio-muscular interactions to assess global health, levels of fatigue, fitness status or the effectiveness of cardiovascular and muscle injury rehabilitation programmes.

Surface electromyographic frequency characteristics of the quadriceps differ between continuous high- and low-torque isometric knee extension to momentary failure

Surface EMG (sEMG) has been used to compare loading conditions during exercise. Studies often explore mean/median frequencies. This potentially misses more nuanced electrophysiological differences between exercise tasks. Therefore, wavelet-based analysis was used to evaluate electrophysiological characteristics in the sEMG signal of the quadriceps under both higher- and lower-torque (70 % and 30 % of MVC, respectively) isometric knee extension performed to momentary failure. Ten recreationally active adult males with previous resistance training experience were recruited. Using a within-session, repeated-measures, randomised crossover design, participants performed isometric knee extension whilst sEMG was collected from the vastus medialis (VM), rectus femoris (RF) and vastus lateralis (VL). Mean signal frequency showed similar characteristics in each condition at momentary failure. However, individual wavelets revealed different frequency component changes between the conditions. All frequency components increased during the low-torque condition. But low-frequency components increased, and high-frequency components decreased, in intensity throughout the high-torque condition. This resulted in convergence of the low-torque and high-torque trial wavelet characteristics towards the end of the low-torque trial. Our results demonstrate a convergence of myoelectric signal properties between low- and high-torque efforts with fatigue via divergent signal adaptations. Further work should disentangle factors influencing frequency characteristics during exercise tasks.

Network of muscle fibers activation facilitates inter-muscular coordination, adapts to fatigue and reflects muscle function

Fundamental movement patterns require continuous skeletal muscle coordination, where muscle fibers with different timing of activation synchronize their dynamics across muscles with distinct functions. It is unknown how muscle fibers integrate as a network to generate and fine tune movements. We investigate how distinct muscle fiber types synchronize across arm and chest muscles, and respond to fatigue during maximal push-up exercise. We uncover that a complex inter-muscular network of muscle fiber cross-frequency interactions underlies push-up movements. The network exhibits hierarchical organization (sub-networks/modules) with specific links strength stratification profile, reflecting distinct functions of muscles involved in push-up movements. We find network reorganization with fatigue where network modules follow distinct phase-space trajectories reflecting their functional role and adaptation to fatigue. Consistent with earlier observations for squat movements under same protocol, our findings point to general principles of inter-muscular coordination for fundamental movements, and open a new area of research, Network Physiology of Exercise.

Energy metabolism and muscle activation heterogeneity explain V ̇ O 2 ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}}$ slow component and muscle fatigue of cycling at different intensities

NEW FINDINGS

What is the central question of this study? What are the physiological mechanisms underlying muscle fatigue and the increase in the O2 cost per unit of work during high-intensity exercise? What is the main finding and its importance? Muscle fatigue happens before, and does not explain, theV ̇ O 2 ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}}$ slow component (V ̇ O 2 sc ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}{\rm{sc}}}$ ), but they share the same origin. Muscle activation heterogeneity is associated with muscle fatigue andV ̇ O 2 sc ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}{\rm{sc}}}$ . Knowing this may improve training prescriptions for healthy people leading to improved public health outcomes.

ABSTRACT

This study aimed to explain theV ̇ O 2 ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}}$ slow component (V ̇ O 2 sc ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}{\rm{sc}}}$ ) and muscle fatigue during cycling at different intensities. The muscle fatigue of 16 participants was determined through maximal isokinetic effort lasting 3 s during constant work rate bouts of moderate (MOD), heavy (HVY) and very heavy intensity (VHI) exercise. Breath-by-breathV ̇ O 2 ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}}$ , near-infrared spectroscopy signals and EMG activity were analysed (thigh muscles).V ̇ O 2 sc ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}{\rm{sc}}}$ was higher during VHI exercise (∼70% vs. ∼28% ofV ̇ O 2 ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}}$ reserve in HVY). The deoxygenated haemoglobin final value during VHI exercise was higher than during HVY and MOD exercise (∼90% of HHb physiological normalization, vs. ∼82% HVY and ∼45% MOD). The muscle fatigue was greater after VHI exercise (∼22% vs. HVY ∼5%). There was no muscle fatigue after MOD exercise. The greatest magnitude of muscle fatigue occurred within 2 min (VHI ∼17%; HVY ∼9%), after which it stabilized. No significant relationship betweenV ̇ O 2 sc ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}{\rm{sc}}}$ and muscle force production was observed. The τ of muscleV ̇ O 2 ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}}$ was significantly related (R2  = 0.47) with torque decrease for VHI. Type I and II muscle fibre recruitment mainly in the rectus femoris moderately explained the muscle fatigue (R2  = 0.30 and 0.31, respectively) and theV ̇ O 2 sc ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}{\rm{sc}}}$ (R2  = 0.39 and 0.27, respectively). TheV ̇ O 2 sc ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}{\rm{sc}}}$ is also partially explained by blood lactate accumulation (R2  = 0.42). In conclusion muscle fatigue and O2 cost seem to share the same physiological cause linked with a decrease in the muscleV ̇ O 2 ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}}$ and a change in lactate accumulation. Muscle fatigue andV ̇ O 2 sc ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}{\rm{sc}}}$ are associated with muscle activation heterogeneity and metabolism of different muscles activated during cycling.

Inter-muscular networks of synchronous muscle fiber activation

Skeletal muscles continuously coordinate to facilitate a wide range of movements. Muscle fiber composition and timing of activation account for distinct muscle functions and dynamics necessary to fine tune muscle coordination and generate movements. Here we address the fundamental question of how distinct muscle fiber types dynamically synchronize and integrate as a network across muscles with different functions. We uncover that physiological states are characterized by unique inter-muscular network of muscle fiber cross-frequency interactions with hierarchical organization of distinct sub-networks and modules, and a stratification profile of links strength specific for each state. We establish how this network reorganizes with transition from rest to exercise and fatigue-a complex process where network modules follow distinct phase-space trajectories reflecting their functional role in movements and adaptation to fatigue. This opens a new area of research, Network Physiology of Exercise, leading to novel network-based biomarkers of health, fitness and clinical conditions.

Characteristics of rectus femoris activation and rectus femoris-hamstrings coactivation during force-matching isometric knee extension in subacute stroke

The spectral properties of surface electromyographic (EMG) signal in the rectus femoris (RF) and the coactivation in the medial hamstrings (MH) were investigated in 45 stroke subjects (22 ± 12 days post-onset) and 30 age-matched healthy controls who performed unilateral knee extensions at maximum effort (100% MVC) and during 5-s force-matching tasks (10, 30, 50% MVC). The spectral properties were obtained through a power spectrum analysis based on Fast Fourier Transform. The coactivation was measured as the MH amplitude (%max) and MH/RF amplitude ratio. Force variability was expressed as the coefficient of variation. Both knee extensors and flexors were weaker in the paretic leg than the non-paretic and control legs (p < 0.001). A significantly higher relative power in the 5-13 and 13-30 Hz bands was found in the paretic than the non-paretic leg across all force levels (p ≤ 0.001) without changes in the 30-60 and 60-100 Hz bands or the mean and median frequencies. Regarding the antagonist coactivation, MH amplitude in the paretic leg was higher than in the non-paretic leg (submaximal levels, p < 0.0001) and the control leg (all force levels, p = 0.0005) with no differences between legs in the MH/RF ratio. The steadiness of the knee extension force was not related to the spectral properties of the agonist EMG or antagonistic coactivation. Greater coactivation was associated with weaker paretic knee flexors (p ≤ 0.0002). The overall results suggest variably altered agonist activation and antagonistic coactivation over the range of isometric knee extension contractions in subacute stroke.

Characteristics of Lower Limb Muscle Activity in Elderly Persons After Ergometric Exercise

This study examined the characteristics of lower limb muscle activity in elderly persons after ergometric pedaling exercise for 1 month. To determine the effect of the exercise, surface electromyography (SEMG) of lower limb muscles was subjected to Daubechies-4 wavelet transformation, and mean wavelet coefficients were compared with the pre-exercise coefficients and the post-exercise coefficients in each wavelet level. The characteristics of muscle activity after pedaling exercise were also compared between the elderly subjects and young subjects. For the elderly subjects, the mean wavelet coefficients were significantly decreased in the tibialis anterior and the gastrocnemius medialis at wavelet levels of 3, 4, and 5 (125–62.5, 62.5–31.25, and 31.25–15.625 Hz, respectively), by pedaling exercise. However, the mean power of wavelet levels of 2 and 3 (250–125 and 125–62.5 Hz) within the rectus femoris and the biceps femoris were significantly increased in the young subjects. The effect of pedaling exercise is different from the effects of heavy-resistance training. It was suggested that the muscle coordination, motor unit (MU) firing frequency, and firing fiber type of lower limb muscles are changed with the different characteristics between elderly and young persons by pedaling exercise for 1 month.

Why do we transition from walking to running? Energy cost and lower leg muscle activity before and after gait transition under body weight support

BACKGROUND

Minimization of the energetic cost of transport (CoT) has been suggested for the walk-run transition in human locomotion. More recent literature argues that lower leg muscle activities are the potential triggers of the walk-run transition. We examined both metabolic and muscular aspects for explaining walk-run transition under body weight support (BWS; supported 30% of body weight) and normal walking (NW), because the BWS can reduce both leg muscle activity and metabolic rate.

METHODS

Thirteen healthy young males participated in this study. The energetically optimal transition speed (EOTS) was determined as the intersection between linear CoT and speed relationship in running and quadratic CoT-speed relationship in walking under BWS and NW conditions. Preferred transition speed (PTS) was determined during constant acceleration protocol (velocity ramp protocol at 0.00463 m·s-2 = 1 km·h-1 per min) starting from 1.11 m·s-1. Muscle activities and mean power frequency (MPF) were measured using electromyography of the primary ankle dorsiflexor (tibialis anterior; TA) and synergetic plantar flexors (calf muscles including soleus) before and after the walk-run transition.

RESULTS

The EOTS was significantly faster than the PTS under both conditions, and both were faster under BWS than in NW. In both conditions, MPF decreased after the walk-run transition in the dorsiflexor and the combined plantar flexor activities, especially the soleus.

DISCUSSION

The walk-run transition is not triggered solely by the minimization of whole-body energy expenditure. Walk-run transition is associated with reduced TA and soleus activities with evidence of greater slow twitch fiber recruitment, perhaps to avoid early onset of localized muscle fatigue.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Lessons from Popper for science, paradigm shifts, scientific revolutions and exercise physiology

A connection has been made to the possible role of the central governor model (CGM) to be a paradigm shift within the exercise sciences. Unfortunately, very little evidence was presented to support this notion, and a narrow view of scientific philosophy was used to reflect on the role of the CGM in understanding exercise physiology and the pursuit of a more ideal scientific method. When contrasting the scientific philosophies of Kuhn to Popper, and applying the tenant of falsification to the research and commentary on the CGM, it is probable that the scholarship pertaining to the CGM adheres more to pseudoscience than science. To improve the scientific contributions of research on the CGM, fellow scientists need to adopt a more critical platform where questions are raised and research designs are employed in efforts to refute the theory. The inability to falsify a theory is the most meaningful way to prove that it is likely to be correct. To support this development, the CGM needs to be more carefully worded to form a theory that clearly reveals key features that can be researched and potentially falsified. In addition, the wording of the CGM needs to allow scientists to make predictions that can then be tested in controlled experimental research studies. Until this happens for the CGM and all other pertinent paradigms within exercise physiology, the discipline will never rise out of the abyss of normal science to extraordinary science involving paradigm shifts and scientific revolutions.

Associations between motor unit action potential parameters and surface EMG features

The surface interference EMG signal provides some information on the neural drive to muscles. However, the association between neural drive to muscle and muscle activation has long been debated with controversial indications due to the unavailability of motor unit population data. In this study, we clarify the potential and limitations of interference EMG analysis to infer motor unit recruitment strategies with an experimental investigation of several concurrently active motor units and of the associated features of the surface EMG. For this purpose, we recorded high-density surface EMG signals during linearly increasing force contractions of the tibialis anterior muscle, up to 70% of maximal force. The recruitment threshold (RT), conduction velocity (MUCV), median frequency (MDF_MU), and amplitude (RMS_MU) of action potentials of 587 motor units from 13 individuals were assessed and associated with features of the interference EMG. MUCV was positively associated with RT (R² = 0.64 ± 0.14), whereas MDF_MU and RMS_MU showed a weaker relation with RT (R² = 0.11 ± 0.11 and 0.39 ± 0.24, respectively). Moreover, the changes in average conduction velocity estimated from the interference EMG predicted well the changes in MUCV (R² = 0.71), with a strong association to ankle dorsiflexion force (R² = 0.81 ± 0.12). Conversely, both the average EMG MDF and RMS were poorly associated with motor unit recruitment. These results clarify the limitations of EMG spectral and amplitude analysis in inferring the neural strategies of muscle control and indicate that, conversely, the average conduction velocity could provide relevant information on these strategies.NEW & NOTEWORTHY The surface EMG provides information on the neural drive to muscles. However, the associations between EMG features and neural drive have been long debated due to unavailability of motor unit population data. Here, by using novel highly accurate decomposition of the EMG, we related motor unit population behavior to a wide range of voluntary forces. The results fully clarify the potential and limitation of the surface EMG to provide estimates of the neural drive to muscles.

Muscle coordination limits efficiency and power output of human limb movement under a wide range of mechanical demands

This study investigated the influence of cycle frequency and workload on muscle coordination and the ensuing relationship with mechanical efficiency and power output of human limb movement. Eleven trained cyclists completed an array of cycle frequency (cadence)-power output conditions while excitation from 10 leg muscles and power output were recorded. Mechanical efficiency was maximized at increasing cadences for increasing power outputs and corresponded to muscle coordination and muscle fiber type recruitment that minimized both the total muscle excitation across all muscles and the ineffective pedal forces. Also, maximum efficiency was characterized by muscle coordination at the top and bottom of the pedal cycle and progressive excitation through the uniarticulate knee, hip, and ankle muscles. Inefficiencies were characterized by excessive excitation of biarticulate muscles and larger duty cycles. Power output and efficiency were limited by the duration of muscle excitation beyond a critical cadence (120-140 rpm), with larger duty cycles and disproportionate increases in muscle excitation suggesting deteriorating muscle coordination and limitations of the activation-deactivation capabilities. Most muscles displayed systematic phase shifts of the muscle excitation relative to the pedal cycle that were dependent on cadence and, to a lesser extent, power output. Phase shifts were different for each muscle, thereby altering their mechanical contribution to the pedaling action. This study shows that muscle coordination is a key determinant of mechanical efficiency and power output of limb movement across a wide range of mechanical demands and that the excitation and coordination of the muscles is limited at very high cycle frequencies.

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

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

McArdle disease does not affect skeletal muscle fibre type profiles in humans

Patients suffering from glycogen storage disease V (McArdle disease) were shown to have higher surface electrical activity in their skeletal muscles when exercising at the same intensity as their healthy counterparts, indicating more muscle fibre recruitment. To explain this phenomenon, this study investigated whether muscle fibre type is shifted towards a predominance in type I fibres as a consequence of the disease. Muscle biopsies from the Biceps brachii (BB) (n = 9) or Vastus lateralis (VL) (n = 8) were collected over a 13-year period from male and female patients diagnosed with McArdle disease, analysed for myosin heavy chain (MHC) isoform content using SDS-PAGE, and compared to healthy controls (BB: n = 3; VL: n = 10). All three isoforms were expressed and no difference in isoform expression in VL was found between the McArdle patients and healthy controls (MHC I: 33±19% vs. 43±7%; MHC IIa: 52±9% vs. 40±7%; MHC IIx: 15±18% vs. 17±9%). Similarly, the BB isoform content was also not different between the two groups (MHC I: 33±14% vs. 30±11%; MHC IIa: 46±17% vs. 39±5%; MHC IIx: 21±13% vs. 31±14%). In conclusion, fibre type distribution does not seem to explain the higher surface EMG in McArdle patients. Future studies need to investigate muscle fibre size and contractility of McArdle patients.

The extraction of neural strategies from the surface EMG: an update

A surface EMG signal represents the linear transformation of motor neuron discharge times by the compound action potentials of the innervated muscle fibers and is often used as a source of information about neural activation of muscle. However, retrieving the embedded neural code from a surface EMG signal is extremely challenging. Most studies use indirect approaches in which selected features of the signal are interpreted as indicating certain characteristics of the neural code. These indirect associations are constrained by limitations that have been detailed previously (Farina D, Merletti R, Enoka RM. J Appl Physiol 96: 1486-1495, 2004) and are generally difficult to overcome. In an update on these issues, the current review extends the discussion to EMG-based coherence methods for assessing neural connectivity. We focus first on EMG amplitude cancellation, which intrinsically limits the association between EMG amplitude and the intensity of the neural activation and then discuss the limitations of coherence methods (EEG-EMG, EMG-EMG) as a way to assess the strength of the transmission of synaptic inputs into trains of motor unit action potentials. The debated influence of rectification on EMG spectral analysis and coherence measures is also discussed. Alternatively, there have been a number of attempts to identify the neural information directly by decomposing surface EMG signals into the discharge times of motor unit action potentials. The application of this approach is extremely powerful, but validation remains a central issue.

Task-oriented control of muscle coordination during cycling

PURPOSE

This study investigated the effects of different biomechanical constraints on the variability of muscle activation during cycling.

METHODS

Fifteen male athletes cycled at a power of 150 and 300 W. Surface EMG was recorded from seven lower limb muscles. Wavelet transformed EMG signals of all muscles were subjected to a principal component analysis to study the variability of the EMG. The full vector space was reduced to the first principal components that explained 90% of the variance. The input data of each cycle revolution were projected onto these principal component vectors. Means and SD of the projections were calculated across all cycles and summed across all time points. The relative variability (RV) was expressed as the ratio between the SD and the mean of the summed projections. The principal angle was calculated between the principal components used for the 150-W condition and those used for the 300-W condition.

RESULTS

The RV could be split into low- and high-variability components. The variability was smaller for the lower ordered eigenvectors compared with the higher ordered ones (P < 0.001) independent of the loading condition. Overall, the 300-W condition showed lower RV compared with the 150-W condition (P < 0.01). The average principal angle between the 150- and 300-W subspaces was 0.4, respectively.

CONCLUSIONS

Structured aspects of variability were found in the muscle activation of lower leg muscles during cycling. In the context of the minimum intervention principal, this might be interpreted as a transition into a regime that requires specific necessary muscles where the increased constraints of the task specify the muscle coordination pattern in a more precise way.

Assessment of the upper body contribution to multiple-sprint cycling in men and women

The aim of this study was to investigate the effect of repeated cycling sprints on power profiles while assessing upper body muscle contraction. Eighteen physically active participants performed 8 × 10 s repeated sprints while muscle activity was recorded via surface electromyography (sEMG) from the brachioradialis (BR), biceps brachii (BB), triceps brachii (TB) and upper trapezius (UT). Measurements were obtained at rest, during a functional maximum contraction (FMC) while participants were positioned in a seated position on the cycle ergometer and during the repeated sprint protocol. Results suggest that mainly type I muscle fibres (MFs) are being recruited within the upper body musculature due to the submaximal and intermittent nature of the contractions. Subsequently, there is no evidence of upper body fatigue across the sprints, which is reflected in the lack of changes in the median frequency of the power spectrum (P<0·05).

Effects of diverting activity on strength, electromyographic, and mechanomyographic signals

The purpose of this study was to investigate the effects of different recovery interventions on peak torque, electromyographic (EMG), and mechanomyographic (MMG) measures. Ten (23.40 ± 1.00 years; 178.40 ± 5.03 cm; 84.80 ± 15.85 kg) recreationally trained college men performed 4 experimental visits consisting of 2 bouts of 50 maximal isokinetic leg extensions at 180°·s(-1). Between each bout of maximal exercise, 2 minutes of recovery involving one of the 4 interventions (passive, active, passive diverting, and active diverting) was completed. Electromyographic and MMG measures were collected during the preintervention and postintervention maximal isokinetic strength tests. Peak torque declined to a significantly greater degree during the postintervention test in the passive condition than the other interventions. Electromyographic amplitude decreased on the postintervention test but did not differ between conditions. There was a significant 2-way interaction for EMG mean power frequency (MPF) between time and repetitions. There was a significant decrease in EMG MPF from the first 3 to the last 3 repetitions for both the preintervention and postintervention tests. The decrease in EMG MPF from the initial to final repetitions was greater for the preintervention test than the postintervention test. Mechanomyographic amplitude significantly decreased from the initial to final repetitions regardless of time or condition. These findings suggest that active, passive diverting, and active diverting strategies provide the same extent of recovery between maximal, fatiguing isokinetic leg extension tasks, and that these strategies can be used by coaches and exercise professionals to select the most effective interset recovery strategy.

Early deactivation of slower muscle fibres at high movement frequencies

Animals produce rapid movements using fast cyclical muscle contractions. These types of movements are better suited to faster muscle fibres within muscles of mixed fibre types as they can shorten at faster velocities and achieve higher activation-deactivation rates than their slower counterparts. Preferential recruitment of faster muscle fibres has previously been shown during high velocity contractions. Additionally, muscle deactivation takes longer than activation and therefore may pose a limitation to fast cyclical contractions. It has been speculated that slower fibres maybe deactivated before faster fibres to accommodate their longer deactivation time. This study aimed to test whether shifts in muscle fibre recruitment occur with derecruitment of slow fibres before the faster fibres at high cycle frequencies. Electromyographic (EMG) signals were collected from the medial gastrocnemius at an extreme range of cycle frequencies and workloads. Wavelets were used to resolve the EMG signals into time and frequency space and the primary sources of variability within the EMG frequency spectra were identified through principal component analysis. A general early derecruitment of slower fibres was evident at the end of muscle excitation for the higher cycle frequencies, and additional slower fibre recruitment was present at the highest cycle frequency. The duration of muscle excitation reached a minimum of about 150 ms and did not change for the three highest cycle frequencies suggesting a duration limit for the medial gastrocnemius. This study provides further evidence of modifications of muscle fibre recruitment strategies to meet the mechanical demands of movement.

Motor unit

Movement is accomplished by the controlled activation of motor unit populations. Our understanding of motor unit physiology has been derived from experimental work on the properties of single motor units and from computational studies that have integrated the experimental observations into the function of motor unit populations. The article provides brief descriptions of motor unit anatomy and muscle unit properties, with more substantial reviews of motoneuron properties, motor unit recruitment and rate modulation when humans perform voluntary contractions, and the function of an entire motor unit pool. The article emphasizes the advances in knowledge on the cellular and molecular mechanisms underlying the neuromodulation of motoneuron activity and attempts to explain the discharge characteristics of human motor units in terms of these principles. A major finding from this work has been the critical role of descending pathways from the brainstem in modulating the properties and activity of spinal motoneurons. Progress has been substantial, but significant gaps in knowledge remain.

Dissociation of increases in PGC-1α and its regulators from exercise intensity and muscle activation following acute exercise

Muscle activation as well as changes in peroxisome proliferator-activated receptor gamma coactivator 1 alpha (PGC-1α) following high-intensity interval exercise (HIIE) were examined in young healthy men (n  = 8; age, 21.9±2.2 yrs; VO2peak, 53.1±6.4 ml/min/kg; peak work rate, 317±23.5 watts). On each of 3 visits HIIE was performed on a cycle ergometer at a target intensity of 73, 100, or 133% of peak work rate. Muscle biopsies were taken at rest and three hours after each exercise condition. Total work was not different between conditions (∼730 kJ) while average power output (73%, 237±21; 100%, 323±26; 133%, 384±35 watts) and EMG derived muscle activation (73%, 1262±605; 100%, 2089±737; 133%, 3029±1206 total integrated EMG per interval) increased in an intensity dependent fashion. PGC-1α mRNA was elevated after all three conditions (p<0.05), with a greater increase observed following the 100% condition (∼9 fold, p<0.05) compared to both the 73 and 133% conditions (∼4 fold). When expressed relative to muscle activation, the increase in PGC-1α mRNA for the 133% condition was less than that for the 73 and 100% conditions (p<0.05). SIRT1 mRNA was also elevated after all three conditions (∼1.4 fold, p<0.05), with no difference between conditions. These findings suggest that intensity-dependent increases in PGC-1α mRNA following submaximal exercise are largely due to increases in muscle recruitment. As well, the blunted response of PGC-1α mRNA expression following supramaximal exercise may indicate that signalling mediated activation of PGC-1α may also be blunted. We also indentify that increases in PDK4, SIRT1, and RIP140 mRNA following acute exercise are dissociated from exercise intensity and muscle activation, while increases in EGR1 are augmented with supramaximal HIIE (p<0.05).

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

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

Shoulder muscles recruitment during a power backward giant swing on high bar: a wavelet-EMG-analysis

This study aimed at determining the upper limb muscles coordination during a power backward giant swing (PBGS) and the recruitment pattern of motor units (MU) of co-activated muscles. The wavelet transformation (WT) was applied to the surface electromyographic (EMG) signal of eight shoulder muscles. Total gymnast's body energy and wavelet synergies extracted from the WT-EMG by using a non-negative matrix factorization were analyzed as a function of the body position angle of the gymnast. A cross-correlation analysis of the EMG patterns allowed determining two main groups of co-activated muscles. Two wavelet synergies representing the main spectral features (82% of the variance accounted for) discriminated the recruitment of MU. Although no task-group of MU was found among the muscles, it appeared that a higher proportion of fast MU was recruited within the muscles of the first group during the upper part of the PBGS. The last increase of total body energy before bar release was induced by the recruitment of the muscles of the second group but did not necessitate the recruitment of a higher proportion of fast MU. Such muscle coordination agreed with previous simulations of elements on high bar as well as the findings related to the recruitment of MU.

Effect of the upper limbs muscles activity on the mechanical energy gain in pole vaulting

The shoulder muscles are highly solicited in pole vaulting and may afford energy gain. The objective of this study was to determine the bilateral muscle activity of the upper-limbs to explain the actions performed by the vaulter to bend the pole and store elastic energy. Seven experienced athletes performed 5-10 vaults which were recorded using two video cameras (50Hz). The mechanical energy of the centre of gravity (CG) was computed, while surface electromyographic (EMG) profiles were recorded from 5 muscles bilateral: deltoideus, infraspinatus, biceps brachii, triceps, and latissimus dorsi muscles. The level of intensity from EMG profile was retained in four sub phases between take-off (TO1) and complete pole straightening (PS). The athletes had a mean mechanical energy gain of 22% throughout the pole vault, while the intensities of deltoideus, biceps brachii, and latissimus dorsi muscles were sub phases-dependent (p<0.05). Stabilizing the glenohumeral joint (increase of deltoideus and biceps brachii activity) and applying a pole bending torque (increase of latissimus dorsi activity) required specific muscle activation. The gain in mechanical energy of the vaulter could be linked to an increase in muscle activation, especially from latissimusdorsi muscles.

Surface electromyographic activity of five residual limb muscles recorded during isometric contraction in transfemoral amputees with osseointegrated prostheses

BACKGROUND

Femoral osseointegrated implants represent a new development in amputee rehabilitation, eliminating socket pressure discomfort, improving hip range of movement and facilitating prosthetic limb attachment. A clinical aspect that has not previously been reported on is the function of muscles in the residuum with implications concerning energy expenditure, hip-hiking and viability of the electrogram as a myoprocessor. Typically, amputees fitted with osseointegrated fixation have shorter residuums and weaker attachment of cleaved muscles. Function of muscle can be assessed by surface electromyography through changes in amplitude and median frequency of the signal.

METHODS

Five male transfemoral amputees with osseointegrated fixations participated together with a control group comprised of ten adult males. Electrodes recorded surface electromyographic activity of five residual limb muscles or left lower limb muscles of control subjects. Isometric contractions were performed against resistance. The increase in mean rectified amplitude from resting to maximally contracting was calculated and median frequencies estimated.

FINDINGS

The amputees were unable to maintain a maximum voluntary contraction of constant amplitude. Amplitude increase was lowest for rectus femoris and adductor magnus. The median frequency of adductor magnus was significantly greater (P=0.02) for the amputees than intact subjects and there was a significant difference (P<0.01) between gluteus maximus and adductor magnus for amputee subjects.

INTERPRETATION

High electromyographic amplitude variability suggests that using residuum muscles singly as a myoprocessor might be challenging. Adductor magnus displayed a different sEMG profile compared to intact subjects indicating decreased function and neuromuscular changes. Further work into optimal muscle anchorage is required to ensure maximal mechanical performance.

Skeletal muscle fatigue precedes the slow component of oxygen uptake kinetics during exercise in humans

The mechanisms determining exercise intolerance are poorly understood. A reduction in work efficiency in the form of an additional energy cost and oxygen requirement occurs during high-intensity exercise and contributes to exercise limitation. Muscle fatigue and subsequent recruitment of poorly efficient muscle fibres has been proposed to mediate this decline. These data demonstrate in humans, that muscle fatigue, generated in the initial minutes of exercise, is correlated with the increasing energy demands of high-intensity exercise. Surprisingly, however, while muscle fatigue reached a plateau, oxygen uptake continued to increase throughout 8 min of exercise. This suggests that additional recruitment of inefficient muscle fibres may not be the sole mechanism contributing to the decline in work efficiency during high-intensity exercise.

Wavelet based correlation and coherence analysis reveals frequency dependent motor unit conduction velocity of the abductor pollicis brevis muscle

The purpose of this study was to investigate the motorunit conduction velocity (CV) as a function of frequency. A wavelet based correlation and coherence analysis was introduced to measure CV as a function of frequency. Based on the most simple assumption that the power spectra of the motor unit action potential is shifted to higher frequencies with increasing CV, we hypothesized that there would be a monotonic or linear trend of increasing CV with frequency. This trend was only confirmed at higher frequencies. At lower frequencies the trend was often reversed leading to a decrease in CV with increasing frequency. Thus the CV was high at low frequencies, went through a minimum at about 170 Hz and increased at higher frequencies, as expected. The observed CV at low frequencies could not be fully explained by assuming non-propagating signals or variable groups of motor units. We concluded that spectra and CV contain partly independent information about the muscles and that the wavelet based method provides the tools to measure them both simultaneously.

Prediction of externally applied forces to human hands using frequency content of surface EMG signals

In this work, a new signal processing method was proposed in order to predict externally applied forces to human hands by deriving a relationship between the surface electromyographic (SEMG) signals and experimentally known forces. This relationship was investigated by analyzing the spectral features of the SEMG signals. SEMG signals were recorded from three subjects during isometric contraction and from another three subjects during anisometric contraction. In order to determine force-SEMG signal relationship, higher order frequency moments (HOFMs) of the signals were calculated and used as characterizing features of SEMG signals. Subsequently, artificial neural networks (ANN) with backpropagation algorithm were trained by using the HOFMs. Root mean square difference (RMSD) between the actual and predicted forces was calculated to evaluate force prediction performance of the ANN. In addition to RMSD, cross-correlation coefficients between actual and predicted force time histories were also calculated for anisometric experiment results. The RMSD values ranged from 0.34 and 0.02 in the isometric contraction experiments. In the anisometric contraction tests, RMSD results were between 0.23 and 0.09 and cross-correlation coefficients ranged from 0.91 to 0.98. In order to compare the performance of the HOFMs with a widely used EMG signal processing technique, root-mean-squared (RMS) values of the EMG signals were also calculated and used to train the ANN as another characterizing feature of the signal. Predicted forces using HOFMs technique were in general closer to the actual forces than those of obtained by using RMS values. The results indicated that the proposed signal processing method showed an encouraging performance for predicting the forces applied to the human hands, and the spectral features of the EMG signal might be used as input parameter for the myoelectric controlled prostheses.

Effects of a prior high-intensity knee-extension exercise on muscle recruitment and energy cost: a combined local and global investigation in humans

The effects of a priming exercise bout on both muscle energy production and the pattern of muscle fibre recruitment during a subsequent exercise bout are poorly understood. The purpose of the present study was to determine whether a prior exercise bout which is known to increase O(2) supply and to induce a residual acidosis could alter energy cost and muscle fibre recruitment during a subsequent heavy-intensity knee-extension exercise. Fifteen healthy subjects performed two 6 min bouts of heavy exercise separated by a 6 min resting period. Rates of oxidative and anaerobic ATP production, determined with (31)P-magnetic resonance spectroscopy, and breath-by-breath measurements of pulmonary oxygen uptake were obtained simultaneously. Changes in muscle oxygenation and muscle fibre recruitment occurring within the quadriceps were measured using near-infrared spectroscopy and surface electromyography. The priming heavy-intensity exercise increased motor unit recruitment (P < 0.05) in the early part of the subsequent exercise bout but did not alter muscle energy cost. We also observed a reduced deoxygenation time delay, whereas the deoxygenation amplitude was increased (P < 0.01). These changes were associated with an increased oxidative ATP cost after approximately 50 s (P < 0.05) and a slight reduction in the overall anaerobic rate of ATP production (0.11 +/- 0.04 mM min(-1) W(-1) for bout 1 and 0.06 +/- 0.11 mM min(-1) W(-1) for bout 2; P < 0.05). We showed that a priming bout of heavy exercise led to an increased recruitment of motor units in the early part of the second bout of heavy exercise. Considering the increased oxidative cost and the unaltered energy cost, one could suggest that our results illustrate a reduced metabolic strain per fibre.