Neuromuscular Strategies during Cycling at Different Muscular Demands

The interaction between changes of muscle activation and cortical network dynamics during isometric elbow contraction: a sEMG and fNIRS study

Objective: The relationship between muscle activation during motor tasks and cerebral cortical activity remains poorly understood. The aim of this study was to investigate the correlation between brain network connectivity and the non-linear characteristics of muscle activation changes during different levels of isometric contractions. Methods: Twenty-one healthy subjects were recruited and were asked to perform isometric elbow contractions in both dominant and non-dominant sides. Blood oxygen concentrations in brain from functional Near-infrared Spectroscopy (fNIRS) and surface electromyography (sEMG) signals in the biceps brachii (BIC) and triceps brachii (TRI) muscles were recorded simultaneously and compared during 80% and 20% of maximum voluntary contraction (MVC). Functional connectivity, effective connectivity, and graph theory indicators were used to measure information interaction in brain activity during motor tasks. The non-linear characteristics of sEMG signals, fuzzy approximate entropy (fApEn), were used to evaluate the signal complexity changes in motor tasks. Pearson correlation analysis was used to examine the correlation between brain network characteristic values and sEMG parameters under different task conditions. Results: The effective connectivity between brain regions in motor tasks in dominant side was significantly higher than that in non-dominant side under different contractions (p < 0.05). The results of graph theory analysis showed that the clustering coefficient and node-local efficiency of the contralateral motor cortex were significantly varied under different contractions (p < 0.01). fApEn and co-contraction index (CCI) of sEMG under 80% MVC condition were significantly higher than that under 20% MVC condition (p < 0.05). There was a significant positive correlation between the fApEn and the blood oxygen value in the contralateral brain regions in both dominant or non-dominant sides (p < 0.001). The node-local efficiency of the contralateral motor cortex in the dominant side was positively correlated with the fApEn of the EMG signals (p < 0.05). Conclusion: In this study, the mapping relationship between brain network related indicators and non-linear characteristic of sEMG in different motor tasks was verified. These findings provide evidence for further exploration of the interaction between the brain activity and the execution of motor tasks, and the parameters might be useful in evaluation of rehabilitation intervention.

The repeatability of neuromuscular activation strategies recorded in recreationally active individuals during cycling

Purpose

The human neuro-motor system can select different intermuscular coordination patterns to complete any given task, such as pedalling a bicycle. This study assessed whether intermuscular coordination patterns are used consistently across visit days and cadence conditions in recreationally active individuals.

Methods

Seven participants completed a cycling exercise protocol across 2 days, consisting of pedalling at 150 Watts at cadences of 60, 80 and 100 rpm. Whilst cycling, surface electromyography was continuously recorded from ten leg muscles. For each participant, muscle coordination patterns were established using principal component (PC) analysis and the amount that each pattern was used was quantified by the PC loading scores. A sample entropy derived measure of the persistence of the loading scores across consecutive pedal cycles, entropic half-life (EnHL), was calculated. The median loading scores and EnHLs of the first three PCs were then compared across cadence conditions and visit days.

Results

No significant differences were found in the median loading scores across cadence conditions or visits, nor were there any significant differences in the EnHLs across visits. However, the EnHLs were significantly longer when participants were cycling at 60 rpm compared to 100 rpm.

Conclusion

These findings are based on a small sample size, but do suggest that, within individual participants, a consistent neuromuscular control strategy is used during cycling on different days. However, the underlying structure of muscle coordination is more persistent when pedalling at slower cadences with large differences between individuals.

EMG Signals Can Reveal Information Sharing between Consecutive Pedal Cycles

PURPOSE

Producing a steady cadence and power while cycling results in fairly consistent average pedal forces for every revolution, although small fluctuations about an average force do occur. This force can be generated by several combinations of muscles, each with slight fluctuations in excitation for every pedal cycle. Fluctuations such as these are commonly thought of as random variation about average values. However, research into fluctuations of stride length and stride time during walking shows information can be contained in the order of fluctuations. This order, or structure, is thought to reveal underlying motor control strategies. Previously, we found persistent structure in the fluctuations of EMG signals during cycling using entropic half-life analysis. These EMG signals contained fluctuations across multiple timescales, such as those within a burst of excitation, between the burst and quiescent period of a cycle, and across multiple cycles. It was not clear which sources of variation contributed to the persistent structure in the EMG.

METHODS

In this study, we manipulated variation at different timescales in EMG intensity signals to identify the sources of structure observed during cycling. Nine participants cycled at a constant power and cadence for 30 min while EMG was collected from six muscles of the leg.

RESULTS

We found persistent structure across multiple pedal cycles of average EMG intensities, as well as average pedal forces and durations. In addition, we found the entropic half-life did not quantify fluctuations within a burst of EMG intensity; instead, it detected unstructured variation between the burst and quiescent period within a cycle.

CONCLUSIONS

The persistent structure in average EMG intensities suggests that fluctuations in muscle excitation are regulated from cycle to cycle.

Physiological complexity: influence of ageing, disease and neuromuscular fatigue on muscle force and torque fluctuations

NEW FINDINGS

What is the topic of this review? Physiological complexity in muscle force and torque fluctuations, specifically the quantification of complexity, how neuromuscular complexityis altered by perturbations and the potential mechanism underlying changes in neuromuscular complexity. What advances does it highlight? The necessity to calculate both magnitude- and complexity-based measures for the thorough evaluation of force/torque fluctuations. Also the need for further research on neuromuscular complexity, particularly how it relates to the performance of functional activities (e.g. manual dexterity, balance, locomotion).

ABSTRACT

Physiological time series produce inherently complex fluctuations. In the last 30 years, methods have been developed to characterise these fluctuations, and have revealed that they contain information about the function of the system producing them. Two broad classes of metrics are used: (1) those which quantify the regularity of the signal (e.g. entropy metrics); and (2) those which quantify the fractal properties of the signal (e.g. detrended fluctuation analysis). Using these techniques, it has been demonstrated that ageing results in a loss of complexity in the time series of a multitude of signals, including heart rate, respiration, gait and, crucially, muscle force or torque output. This suggests that as the body ages, physiological systems become less adaptable (i.e. the systems' ability to respond rapidly to a changing external environment is diminished). More recently, it has been shown that neuromuscular fatigue causes a substantial loss of muscle torque complexity, a process that can be observed in a few minutes, rather than the decades it requires for the same system to degrade with ageing. The loss of torque complexity with neuromuscular fatigue appears to occur exclusively above the critical torque (at least for tasks lasting up to 30 min). The loss of torque complexity can be exacerbated with previous exercise of the same limb, and reduced by the administration of caffeine, suggesting both peripheral and central mechanisms contribute to this loss. The mechanisms underpinning the loss of complexity are not known but may be related to altered motor unit behaviour as the muscle fatigues.

Effects of Future Information and Trajectory Complexity on Kinematic Signal and Muscle Activation during Visual-Motor Tracking

Visual-motor tracking movement is a common and essential behavior in daily life. However, the contribution of future information to visual-motor tracking performance is not well understood in current research. In this study, the visual-motor tracking performance with and without future-trajectories was compared. Meanwhile, three task demands were designed to investigate their impact. Eighteen healthy young participants were recruited and instructed to track a target on a screen by stretching/flexing their elbow joint. The kinematic signals (elbow joint angle) and surface electromyographic (EMG) signals of biceps and triceps were recorded. The normalized integrated jerk (NIJ) and fuzzy approximate entropy (fApEn) of the joint trajectories, as well as the multiscale fuzzy approximate entropy (MSfApEn) values of the EMG signals, were calculated. Accordingly, the NIJ values with the future-trajectory were significantly lower than those without future-trajectory (p-value < 0.01). The smoother movement with future-trajectories might be related to the increasing reliance of feedforward control. When the task demands increased, the fApEn values of joint trajectories increased significantly, as well as the MSfApEn of EMG signals (p-value < 0.05). These findings enrich our understanding about visual-motor control with future information.

Changes in muscle activity during the flexion and extension phases of arm cycling as an effect of power output are muscle-specific

Arm cycling is commonly used in rehabilitation settings for individuals with motor impairments in an attempt to facilitate neural plasticity, potentially leading to enhanced motor function in the affected limb(s). Studies examining the neural control of arm cycling, however, typically cycle using a set cadence and power output. Given the importance of motor output intensity, typically represented by the amplitude of electromyographic (EMG) activity, on neural excitability, surprisingly little is known about how arm muscle activity is modulated using relative workloads. Thus, the objective of this study was to characterize arm muscle activity during arm cycling at different relative workloads. Participants (n = 11) first completed a 10-second maximal arm ergometry sprint to determine peak power output (PPO) followed by 11 randomized trials of 20-second arm cycling bouts ranging from 5–50% of PPO (5% increments) and a standard 25 W workload. All submaximal trials were completed at 60 rpm. Integrated EMG amplitude (iEMG) was assessed from the biceps brachii, brachioradialis, triceps brachii, flexor carpi radialis, extensor carpi radialis and anterior deltoid of the dominant arm. Arm cycling was separated into two phases, flexion and extension, relative to the elbow joint for all comparisons. As expected, iEMG amplitude increased during both phases of cycling for all muscles examined. With the exception of the triceps brachii and extensor carpi radialis, iEMG amplitudes differed between the flexion and extension phases. Finally, there was a linear relationship between iEMG amplitude and the %PPO for all muscles during both elbow flexion and extension.

Caffeine increases motor output entropy and performance in 4 km cycling time trial

Caffeine improves cycling time trial performance through enhanced motor output and muscle recruitment. However, it is unknown if caffeine further increases power output entropy. To investigate the effects of caffeine effects on cycling time trial performance and motor output entropy (MOEn), nine cyclists (VO_2MAX of 55 ± 6.1 mL^.kg^.-1min^-1) performed a 4 km cycling time trial (TT_4km) after caffeine and placebo ingestion in a counterbalanced order. Power output data were sampled at a 2 Hz frequency, thereafter entropy was estimated on a sliding-window fashion to generate a power output time series. A number of mixed models compared performance and motor output entropy between caffeine and placebo every 25% of the total TT_4km distance. Caffeine ingestion improved power output by 8% (p = 0.003) and increased MOEn by 7% (p = 0.018). Cyclists adopted a U-shaped pacing strategy after caffeine ingestion. MOEn mirrored power output responses as an inverted U-shape MOEn during the time trial. Accordingly, a strong inverse correlation was observed between MOEn and power output responses over the last 25% of the TT_4km (p < 0.001), regardless of the ingestion, likely reflecting the end spurt during this period (p = 0.016). Caffeine ingestion improved TT_4km performance and motor output responses likely due to a greater power output entropy.

Processing Surface EMG Signals for Exoskeleton Motion Control

The surface electromyography (sEMG) signal has been used for volitional control of robotic assistive devices. There are still challenges in improving system performance accuracy and signal processing to remove systematic noise. This study presents procedures and a pilot validation of the EMG-driven speed-control of exoskeleton and integrated treadmill with a goal to provide better interaction between a user and the system. The gait cycle duration (GCD) was extracted from sEMG signals using the autocorrelation algorithm and Bayesian fusion algorithm. GCDs of various walking speeds were then programmed to control the motion speed of exoskeleton robotic system. The performance and efficiency of this sEMG-controlled robotic assistive ambulation system was tested and validated among 6 healthy volunteers. The results demonstrated that the autocorrelation algorithm extracted the GCD from individual muscle contraction. The GCDs of individual muscles had variability between different walking steps under a designated walking speed. Bayesian fusion algorithms processed the GCDs of multiple muscles yielding a final GCD with the least variance. The fused GCD effectively controlled the motion speeds of exoskeleton and treadmill. The higher amplitude of EMG signals with shorter GCD was found during a faster walking speed. The algorithms using fused GCDs and gait stride length yielded trajectory joint motion tracks in a shape of sine curve waveform. The joint angles of the exoskeleton measured by a decoder mounted on the hip turned out to be in sine waveforms. The hip joint motion track of the exoskeleton matched the angles projected by trajectory curve generated by computer algorithms based on the fused GCDs with high agreement. The EMG-driven speed-control provided the human-machine inter-limb coordination mechanisms for an intuitive speed control of the exoskeleton-treadmill system at the user's intents. Potentially the whole system can be used for gait rehabilitation of incomplete spinal cord hemispheric stroke patients as goal-directed and task-oriented training tool.

Intrinsic foot muscles act to stabilise the foot when greater fluctuations in centre of pressure movement result from increased postural balance challenge

BACKGROUND

Increased postural balance challenge is associated with more fluctuations in centre of pressure movement, indicating increased interference from the postural control system. The role of intrinsic foot muscles in balance control is relatively understudied and whether such control system interference occurs at the level of these muscles is unknown.

RESEARCH QUESTION

Do fewer fluctuations in intrinsic foot muscle excitation occur in response to increased postural balance challenge?

METHODS

Surface EMGs were recorded using a grid of 13 × 5 channels from the plantar surface of the foot of 17 participants, who completed three balance tasks: bipedal stance; single leg stance and bipedal tip-toe. Centre of pressure (CoP) movement was calculated from simultaneously recorded force plate signals. Fluctuations in CoP and EMGs for each task were quantified using a sample entropy based metric, Entropy Halflife (EnHL). Longer EnHL indicates fewer signal fluctuations.

RESULTS

The shortest EMG EnHL, 9.27 ± 3.34 ms (median ± interquartile range), occurred during bipedal stance and the longest during bipedal tip-toe 15.46 ± 11.16 ms, with 18.80 ± 8.00 ms recorded for single leg stance. Differences were statistically significant between bipedal stance and both bipedal tip-toe (p < 0.001) and single leg stance (p < 0.001). CoP EnHL for both anterior-posterior and medial-lateral movements also differed significantly between tasks (p < 0.001, both cases). However, anterior-posterior CoP EnHL was longest for bipedal stance 259.84±230.22 ms and shortest for bipedal tip-toe 146.25±73.35 ms. Medial-lateral CoP EnHL was also longest during bipedal stance 215.73±187.58 ms, but shortest for single leg stance 113.48±83.01 ms.

SIGNIFICANCE

Fewer fluctuations in intrinsic foot muscle excitation occur in response to increased postural balance challenge. Fluctuations in CoP movement during balance must be predominantly driven by excitation of muscles extrinsic to the foot. Intrinsic foot muscles therefore likely play a greater role in stabilisation of the foot than balance control during the postural tasks studied.

The kinematics of cyclic human movement

Literature mentions two types of models describing cyclic movement—theory and data driven. Theory driven models include anatomical and physiological aspects. They are principally suitable for answering questions about the reasons for movement characteristics, but they are complicated and substantial simplifications do not allow generally valid results. Data driven models allow answering specific questions, but lack the understanding of the general movement characteristic. With this paper we try a compromise without having to rely on anatomy, neurology and muscle function. We hypothesize a general kinematic description of cyclic human motion is possible without having to specify the movement generating processes, and still get the kinematics right. The model proposed consists of a superposition of six contributions–subject’s attractor, morphing, short time fluctuation, transient effect, control mechanism and sensor noise, while characterizing numbers and random contributions. We test the model with data from treadmill running and stationary biking. Applying the model in a simulation results in good agreement between measured data and simulation values. We find in all our cases the similarity analysis between measurement and simulation is best for the same subjects—δrunsamesub>55% and δbikesamesub>64%. All comparisons between different subjects are 51%>δrundifferentsub and 52%>δbikedifferentsub. This uniquely allows for the identification of each measurement for the associated simulation. However, even different subject comparisons show good agreement between measurement and simulation results of differences δ_run = 6.7±4.7% and δ_bike = 5.1±4.5%.

During Cycling What Limits Maximum Mechanical Power Output at Cadences above 120 rpm?

PURPOSE

A key determinant of muscle coordination and maximum power output during cycling is pedaling cadence. During cycling, the neuromuscular system may select from numerous solutions that solve the task demands while producing the same result. For more challenging tasks, fewer solutions will be available. Changes in the variability of individual muscle excitations (EMG) and multimuscle coordination, quantified by entropic half-life (EnHL), can reflect the number of solutions available at each system level. We, therefore, ask whether reduced variability in muscle coordination patterns occur at critical cadences and if they coincide with reduced variability in excitations of individual muscles.

METHODS

Eleven trained cyclists completed an array of cadence-power output conditions. The EnHL of EMG intensity recorded from 10 leg muscles and EnHL of principal components describing muscle coordination were calculated. Multivariate adaptive regressive splines were used to determine the relationships between each EnHL and cycling condition or excitation characteristics (duration, duty cycle).

RESULTS

Muscle coordination became more persistent at cadences up to 120 rpm, indicated by increasing EnHL values. Changes in EnHL at the level of the individual muscles differed from the changes in muscle coordination EnHL, with longer EnHL occurring at the slowest (<80 rpm) and fastest (>120 rpm) cadences. The EnHL of the main power producing muscles, however, reached a minimum by 80 rpm and did not change across the faster cadences studied.

CONCLUSIONS

Muscle coordination patterns, rather than the contribution of individual muscles, are key to power production at faster cadences in trained cyclists. Reductions in maximum power output at cadences above 120 rpm could be a function of the time available to coordinate orientation and transfer of forces to the pedals.

Neuromuscular adaptations and sensorimotor integration following a unilateral transfemoral amputation

BACKGROUND

Following an amputation, the human postural control system develops neuromuscular adaptations to regain an effective postural control. We investigated the compensatory mechanisms behind these adaptations and how sensorimotor integration is affected after a lower-limb transfemoral amputation.

METHODS

Center of pressure (CoP) data of 12 unilateral transfemoral amputees and 12 age-matched able-bodied subjects were recorded during quiet standing with eyes open (EO) and closed (EC). CoP adjustments under each leg were recorded to study their contribution to posture control. The spatial structure of the CoP displacements was characterized by measuring the mean distance, the mean velocity of the CoP adjustments, and the sway area. The Entropic Half-Life (EnHL) quantifies the temporal structure of the CoP adjustments and was used to infer disrupted sensory feedback loops in amputees. We expanded the analysis with measures of weight-bearing imbalance and asymmetry, and with two standardized balance assessments, the Berg Balance Scale (BBS) and Timed Up-and-Go (TUG).

RESULTS

There was no difference in the EnHL values of amputees and controls when combining the contributions of both limbs (p = 0.754). However, amputees presented significant differences between the EnHL values of the intact and prosthetic limb (p <  0.001). Suppressing vision reduced the EnHL values of the intact (p = 0.001) and both legs (p = 0.028), but not in controls. Vision feedback in amputees also had a significant effect (increase) on the mean CoP distance (p <  0.001), CoP velocity (p <  0.001) and sway area (p = 0.007). Amputees presented an asymmetrical stance. The EnHL values of the intact limb in amputees were positively correlated to the BBS scores (EO: ρ = 0.43, EC: ρ = 0.44) and negatively correlated to the TUG times (EO: ρ = - 0.59, EC: ρ = - 0.69).

CONCLUSION

These results suggest that besides the asymmetry in load distribution, there exist neuromuscular adaptations after an amputation, possibly related to the loss of sensory feedback and an altered sensorimotor integration. The EnHL values suggest that the somatosensory system predominates in the control of the intact leg. Further, suppressing the visual system caused instability in amputees, but had a minimal impact on the CoP dynamics of controls. These findings points toward the importance of providing somatosensory feedback in lower-limb prosthesis to reestablish a normal postural control.

TRIAL REGISTRATION

DRKS00015254 , registered on September 20th, 2018.

How Do the Mechanical Demands of Cycling Affect the Information Content of the EMG?

PURPOSE

The persistence of phase-related information in EMG signals can be quantified by its entropic half-life (EnHL). It has been proposed that the EnHL would increase with the demands of a movement task, and thus increase as the pedaling power increased during cycling. However, simulation work on the properties of EMG signals suggests that the EnHL depends on burst duration and duty cycle in the EMG that may not be related to task demands. This study aimed to distinguish between these alternate hypotheses.

METHODS

The EnHL was characterized for 10 muscles from nine cyclists cycling at a range of powers (35 to 260 W) and cadences (60-140 rpm) for the raw EMG, phase-randomized surrogate EMG, EMG intensity, and the principal components describing the muscle coordination patterns.

RESULTS

There was phase-related information in the raw EMG signals and EMG intensities that was related to the EMG burst duration, duty cycle pedaling cadence, and power. The EnHL for the EMG intensities of the individual muscles (excluding quadriceps) and for the coordination patterns decreased as cycling power and cadence increased.

CONCLUSIONS

The EnHL provide information on the structure of the motor control signals and their constituent motor unit action potentials, both within and between muscles, rather than on the mechanical demands of the cycling task per se.

Interplay Between Workload and Functional Perceptual-Cognitive-Affective Responses: An Inclusive Model

The extent to and manner in which psychological states change as a function of physical effort and related physiological responses have been addressed separately in various theoretical frameworks. The authors explored a proposed conceptual scheme examining the relationships among perceived exertion, attentional allocation, and affective responses under different workload domains. Thirty male participants performed an incremental cycling test to assess the progression of rating of perceived exertion, attentional focus, affect, and felt arousal along a parallel increase in heart rate using ventilatory threshold as a reference point. Results revealed that ventilatory threshold acts as a metabolic landmark for the attentional shifts toward aversive sensory cues, sustained increases in perceived exertion, negative valence, and physiological activation. Monitoring the dynamics of perceived exertion, attention, and affect can complement physiological measures for an accurate control of training workloads during exercise prescription.

Development of a multichannel current-EMG system for coherence modulation with visual biofeedback

By means of biofeedback, neuromotor control can be modified. Recent biofeedback experiments have used the power of the electromyogram of one muscle in different frequency bands to control a two-dimensional cursor. However, the human body usually requires coherent activation of multiple muscles to achieve daily life tasks. Additionally, electromyography (EMG) instrumentation has remained the same for decades, and might not be the most suitable to measure coherent activations from pennated muscles according to recent experiments by von Tscharner and colleagues. In this study, we propose the development of a multichannel current-based EMG amplifier to use intermuscular coherence as the control feature of a visual biofeedback system. The system was used in a leg extension protocol to voluntarily increase intermuscular coherence between the vastii muscles. Results from ten subjects show that it is possible to increase intermuscular coherence through visual biofeedback. Such a system can have applications in endurance training and rehabilitation.

Effect of increasing workload on knee extensor and flexor muscular activity during cycling as measured with intramuscular electromyography

The purpose of this study was to describe the effect of increasing workload on individual thigh muscle activation during a 20 minute incremental cycling test. Intramuscular electromyographic signals were recorded from the knee extensors rectus femoris, vastus lateralis, vastus medialis and vastus intermedius and the knee flexors semimembranosus, semitendinosus, and the short and long heads of the biceps femoris during increasing workloads. Mean activation levels were compared over the whole pedaling cycle and the crank angles at which onset and offset of activation and peak activity occurred were identified for each muscle. These data were compared between three workloads. EMG activation level significantly increased (p<0.05) with increasing workload in the rectus femoris, vastus medialis, vastus lateralis, vastus intermedius, biceps femoris long head, semitendinosus and semimembranosus but not in the biceps femoris short head. A significant change in activation timing was found for the rectus femoris, vastus lateralis, vastus medialis and semitendinosus. Of the knee flexors only the short head of the biceps femoris had its peak activity during the upstroke phase at the two highest workloads indicating a unique contribution to knee flexion.

Surface electromyography can quantify temporal and spatial patterns of activation of intrinsic human foot muscles

Intrinsic foot muscles (IFM) are a crucial component within the human foot. Investigating their functioning can help understand healthy and pathological behaviour of foot and ankle, fundamental for everyday activities. Recording muscle activation from IFM has been attempted with invasive techniques, mainly investigating single muscles. Here we present a novel methodology, to investigate the feasibility of recording physiological surface EMG (sEMG) non-invasively and quantify patterns of activation across the whole plantar region of the foot. sEMG were recorded with a 13 × 5 array from the sole of the foot (n = 25) during two-foot stance, two-foot tiptoe and anterior/posterior sways. Physiological features of sEMG were analysed. During anterior/posterior epochs within the sway task, sEMG patterns were analysed in terms of signal amplitude (intensity) and structure (Sample Entropy) distribution, by evaluating the centre of gravity (CoG) of each topographical map. Results suggest signals are physiological and not affected by loading. Both amplitude and sample entropy CoG coordinates were grouped in one region and overlapped, suggesting that the region with highest amplitude corresponds with the most predictable signal. Therefore, both spatial and temporal features of IFM activation may be recorded non-invasively, providing opportunity for more detailed investigation of IFM function in healthy and patient populations.

Physiological Profile of an Uphill Time Trial in Elite Cyclists

CONTEXT

While a number of studies have researched road-cycling performance, few have attempted to investigate the physiological response in field conditions.

PURPOSE

To describe the physiological and performance profile of an uphill time trial (TT) frequently used in cycling competitions.

METHODS

Fourteen elite road cyclists (mean ± SD age 25 ± 6 y, height 174 ± 4.2 cm, body mass 64.4 ± 6.1 kg, fat mass 7.48% ± 2.82%) performed a graded exercise test to exhaustion to determine maximal parameters. They then completed a field-based uphill TT in a 9.2-km first-category mountain pass with a 7.1% slope. Oxygen uptake (VO₂), power output, heart rate (HR), lactate concentration, and perceived-exertion variables were measured throughout the field-based test.

RESULTS

During the uphill TT, mean power output and velocity were 302 ± 7 W (4.2 ± 0.1 W/kg) and 18.7 ± 1.6 km/h, respectively. Mean VO₂ and HR were 61.6 ± 2.0 mL · kg^-1 · min^-1 and 178 ± 2 beats/min, respectively. Values were significantly affected by the 1st, 2nd, 6th, and final kilometers (P < .05). Lactate concentration and perceived exertion were 10.87 ± 1.12 mmol/L and 19.1 ± 0.1, respectively, at the end of the test, being significantly different from baseline measures.

CONCLUSION

The studied uphill TT is performed at 90% of maximum HR and VO₂ and 70% of maximum power output. To the authors' knowledge, this is the first study assessing cardiorespiratory parameters combined with measures of performance, perceived exertion, and biochemical variables during a field-based uphill TT in elite cyclists.

Movement Complexity and Neuromechanical Factors Affect the Entropic Half-Life of Myoelectric Signals

Appropriate neuromuscular functioning is essential for survival and features underpinning motor control are present in myoelectric signals recorded from skeletal muscles. One approach to quantify control processes related to function is to assess signal variability using measures such as Sample Entropy. Here we developed a theoretical framework to simulate the effect of variability in burst duration, activation duty cycle, and intensity on the Entropic Half-Life (EnHL) in myoelectric signals. EnHLs were predicted to be <40 ms, and to vary with fluctuations in myoelectric signal amplitude and activation duty cycle. Comparison with myoelectic data from rats walking and running at a range of speeds and inclines confirmed the range of EnHLs, however, the direction of EnHL change in response to altered locomotor demand was not correctly predicted. The discrepancy reflected different associations between the ratio of the standard deviation and mean signal intensity (Ist:It¯) and duty factor in simulated and physiological data, likely reflecting additional information in the signals from the physiological data (e.g., quiescent phase content; variation in action potential shapes). EnHL could have significant value as a novel marker of neuromuscular responses to alterations in perceived locomotor task complexity and intensity.

Acute Neuromuscular Adaptations in the Postural Control of Patients with Parkinson's Disease after Perturbed Walking

Patients suffering from Parkinson’s disease (PD) present motor impairments reflected in the dynamics of the center of pressure (CoP) adjustments during quiet standing. One method to study the dynamics of CoP adjustments is the entropic half-life (EnHL), which measures the short-term correlations of a time series at different time scales. Changes in the EnHL of CoP time series suggest neuromuscular adaptations in the control of posture. In this study, we sought to investigate the immediate changes in the EnHL of CoP adjustments of patients with PD during one session of perturbed (experimental group) and unperturbed treadmill walking (control group). A total of 39 patients with PD participated in this study. The experimental group (n = 19) walked on a treadmill providing small tilting of the treadmill platform. The control group (n = 20) walked without perturbations. Each participant performed 5-min practice followed by three 5-min training blocks of walking with or without perturbation (with 3-min resting in between). Quiet standing CoP data was collected for 30 s at pre-training, after each training block, immediately post-training, and after 10 min retention. The EnHL was computed on the original and surrogates (phase-randomized) CoP signals in the medio-lateral (ML) and anterior–posterior (AP) directions. Data was analyzed using four-way mixed ANOVA. Increased EnHL values were observed for both groups (Time effect, p < 0.001) as the intervention progressed, suggesting neuromuscular adaptations in the control of posture. The EnHL of surrogate signals were significantly lower than for original signals (p < 0.001), confirming that these adaptations come from non-random control processes. There was no Group effect (p = 0.622), however by analyzing the significant Group by Direction by Time interaction (p < 0.05), a more pronounced effect in the ML direction of the perturbed group was observed. Altogether, our findings show that treadmill walking decreases the complexity of CoP adjustments, suggesting neuromuscular adaptations in balance control during a short training period. Further investigations are required to assess these adaptations during longer training intervals.

Reduced complexity of force and muscle activity during low level isometric contractions of the ankle in diabetic individuals

BACKGROUND

This study evaluated the structure and amount of variability of surface electromyography (sEMG) patterns and ankle force data during low-level isometric contractions in diabetic subjects with different degrees of neuropathy.

METHODS

We assessed 10 control subjects and 38 diabetic patients, classified as absent, mild, moderate, or severe neuropathy, by a fuzzy system based on clinical variables. Multichannel sEMG (64-electrode matrix) of tibialis anterior and gastrocnemius medialis muscles were acquired during isometric contractions at 10%, 20%, and 30% of the maximum voluntary contraction, and force levels during dorsi- and plantarflexion were recorded. Standard deviation and sample entropy of force signals were calculated and root mean square and sample entropy were calculated from sEMG signals. Differences among groups of force and sEMG variables were verified using a multivariate analysis of variance.

FINDINGS

Overall, during dorsiflexion contractions, moderate and severe subjects had higher force standard deviation and moderate subjects had lower force sample entropy. During plantarflexion, moderate subjects had higher force standard deviation and all diabetic subjects had lower entropy. Tibialis anterior presented higher root mean square in absent group and lower entropy in mild subjects. For gastrocnemius medialis, entropy was higher in severe and lower in moderate subjects.

INTERPRETATION

Diabetic neuropathy affects the complexity of the neuromuscular system during low-level isometric contractions, reducing the system's capacity to adapt to challenging mechanical demands. The observed patterns of neuromuscular complexity were not associated with disease severity, with the majority of alterations recorded in moderate subject.

Changes in cortical activity measured with EEG during a high-intensity cycling exercise

This study investigated the effects of a high-intensity cycling exercise on changes in spectral and temporal aspects of electroencephalography (EEG) measured from 10 experienced cyclists. Cyclists performed a maximum aerobic power test on the first testing day followed by a time-to-exhaustion trial at 85% of their maximum power output on 2 subsequent days that were separated by ∼48 h. EEG was recorded using a 64-channel system at 500 Hz. Independent component (IC) analysis parsed the EEG scalp data into maximal ICs. An equivalent current dipole model was calculated for each IC, and results were clustered across subjects. A time-frequency analysis of the identified electrocortical clusters was performed to investigate the magnitude and timing of event-related spectral perturbations. Significant changes (P < 0.05) in electrocortical activity were found in frontal, supplementary motor and parietal areas of the cortex. Overall, there was a significant increase in EEG power as fatigue developed throughout the exercise. The strongest increase was found in the frontal area of the cortex. The timing of event-related desynchronization within the supplementary motor area corresponds with the onset of force production and the transition from flexion to extension in the pedaling cycle. The results indicate an involvement of the cerebral cortex during the pedaling task that most likely involves executive control function, as well as motor planning and execution.

Task-Dependent Intermuscular Motor Unit Synchronization between Medial and Lateral Vastii Muscles during Dynamic and Isometric Squats

PURPOSE

Motor unit activity is coordinated between many synergistic muscle pairs but the functional role of this coordination for the motor output is unclear. The purpose of this study was to investigate the short-term modality of coordinated motor unit activity-the synchronized discharge of individual motor units across muscles within time intervals of 5ms-for the Vastus Medialis (VM) and Lateralis (VL). Furthermore, we studied the task-dependency of intermuscular motor unit synchronization between VM and VL during static and dynamic squatting tasks to provide insight into its functional role.

METHODS

Sixteen healthy male and female participants completed four tasks: Bipedal squats, single-leg squats, an isometric squat, and single-leg balance. Monopolar surface electromyography (EMG) was used to record motor unit activity of VM and VL. For each task, intermuscular motor unit synchronization was determined using a coherence analysis between the raw EMG signals of VM and VL and compared to a reference coherence calculated from two desynchronized EMG signals. The time shift between VM and VL EMG signals was estimated according to the slope of the coherence phase angle spectrum.

RESULTS

For all tasks, except for singe-leg balance, coherence between 15-80Hz significantly exceeded the reference. The corresponding time shift between VM and VL was estimated as 4ms. Coherence between 30-60Hz was highest for the bipedal squat, followed by the single-leg squat and the isometric squat.

CONCLUSION

There is substantial short-term motor unit synchronization between VM and VL. Intermuscular motor unit synchronization is enhanced for contractions during dynamic activities, possibly to facilitate a more accurate control of the joint torque, and reduced during single-leg tasks that require balance control and thus, a more independent muscle function. It is proposed that the central nervous system scales the degree of intermuscular motor unit synchronization according to the requirements of the movement task at hand.

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.

Alterations in lower limb multimuscle activation patterns during stair climbing in female total knee arthroplasty patients

Total knee arthroplasty (TKA) patients commonly experience neuromuscular adaptations that may affect stair climbing competence. This study identified multimuscle pattern (MMP) changes in postoperative female TKA patients during stair climbing with a support vector machine (SVM). It was hypothesized that TKA patients adopt temporal and spectral muscle activation characteristics indicative of muscle atrophy and cocontraction strategies. Nineteen female subjects [10 unilateral sex-specific TKAs, 62.2 ± 8.6 yr, body mass index (BMI) 28.2 ± 5.4 kg/m(2); 9 healthy control subjects, 61.4 ± 7.4 yr, BMI 25.6 ± 2.4 kg/m(2)] were recruited. Surface electromyograms (EMGs) were obtained for seven lower limb muscles of the affected limb of TKA subjects and a randomly assigned limb for control subjects during stair climbing. Stance phase (±30%) EMG data were wavelet transformed and normalized to total power. Data across all muscles were combined to form MMPs and analyzed with a SVM. Statistical analysis was performed with binomial tests, independent group t-tests, or independent group Mann-Whitney U-tests in SPSS (P < 0.05). SVM results indicated significantly altered muscle activation patterns in the TKA group for biceps femoris (recognition rate 84.2%), semitendinosus (recognition rate 73.7%), gastrocnemius (recognition rate 68.4%), and tibialis anterior (recognition rate 68.4%). Further analysis identified no significant differences in spectral activation characteristics between groups. Temporal adaptations, indicative of cocontraction strategies, were, however, evident in TKA MMPs. This approach may provide a valuable tool for clinical neuromuscular function assessment and rehabilitation monitoring.