The association between negative muscle work and pedaling rate.

The objective of this research was to use a pedal force decomposition approach to quantify the amount of negative muscular crank torque generated by a group of competitive cyclists across a range of pedaling rates. We hypothesized that negative muscular crank torque increases at high pedaling rates as a result of the activation dynamics associated with muscle force development and the need for movement control, and that there is a correlation between negative muscular crank torque and pedaling rate. To test this hypothesis, data were collected during 60, 75, 90, 105 and 120 revolutions per minute (rpm) pedaling at a power output of 260 W. The statistical analysis supported our hypothesis. A significant pedaling rate effect was detected in the average negative muscular crank torque with all pedaling rates significantly different from each other (p < 0.05). There was no negative muscular crank torque generated at 60 rpm and negligible amounts at 75 and 90 rpm. But substantial negative muscular crank torque was generated at the two highest pedaling rates (105 and 120 rpm) that increased with increasing pedaling rates. This result suggested that there is a correlation between negative muscle work and the pedaling rates preferred by cyclists (near 90 rpm), and that the cyclists' ability to effectively accelerate the crank with the working muscles diminishes at high pedaling rates.     

A theoretical analysis of an optimal chainring shape to maximize crank power during isokinetic pedaling

Previous studies have sought to improve cycling performance by altering various aspects of the pedaling motion using novel crank–pedal mechanisms and non-circular chainrings. However, most designs have been based on empirical data and very few have provided significant improvements in cycling performance. The purpose of this study was to use a theoretical framework that included a detailed musculoskeletal model driven by individual muscle actuators, forward dynamic simulations and design optimization to determine if cycling performance (i.e., maximal power output) could be improved by optimizing the chainring shape to maximize average crank power during isokinetic pedaling conditions. The optimization identified a consistent non-circular chainring shape at pedaling rates of 60, 90 and 120 rpm with an average eccentricity of 1.29 that increased crank power by an average of 2.9% compared to a conventional circular chainring. The increase in average crank power was the result of the optimal chainrings slowing down the crank velocity during the downstroke (power phase) to allow muscles to generate power longer and produce more external work. The data also showed that chainrings with higher eccentricity increased negative muscle work following the power phase due to muscle activation–deactivation dynamics. Thus, the chainring shape that maximized average crank power balanced these competing demands by providing enough eccentricity to increase the external work generated by muscles during the power phase while minimizing negative work during the subsequent recovery phase.     

Evaluation of performance criteria for simulation of submaximal steady-state cycling using a forward dynamic model.

The objectives of this study were twofold. The first was to develop a forward dynamic model of cycling and an optimization framework to simulate pedaling during submaximal steady-state cycling conditions. The second was to use the model and framework to identify the kinetic, kinematic, and muscle timing quantities that should be included in a performance criterion to reproduce natural pedaling mechanics best during these pedaling conditions. To make this identification, kinetic and kinematic data were collected from 6 subjects who pedaled at 90 rpm and 225 W. Intersegmental joint moments were computed using an inverse dynamics technique and the muscle excitation onset and offset were taken from electromyographic (EMG) data collected previously (Neptune et al., 1997). Average cycles and their standard deviations for the various quantities were used to describe normal pedaling mechanics. The model of the bicycle-rider system was driven by 15 muscle actuators per leg. The optimization framework determined both the timing and magnitude of the muscle excitations to simulate pedaling at 90 rpm and 225 W. Using the model and optimization framework, seven performance criteria were evaluated. The criterion that included all of the kinematic and kinetic quantities combined with the EMG timing was the most successful in replicating the experimental data. The close agreement between the simulation results and the experimentally collected kinetic, kinematic, and EMG data gives confidence in the model to investigate individual muscle coordination during submaximal steady-state pedaling conditions from a theoretical perspective, which to date has only been performed experimentally.     

Functional roles of the leg muscles when pedaling in the recumbent versus the upright position

An understanding of the coordination of the leg muscles in recumbent pedaling would be useful to the design of rehabilitative pedaling exercises. The objectives of this work were to (i) determine whether patterns of muscle activity while pedaling in the recumbent and upright positions are similar when the different orientation in the gravity field is considered, (ii) compare the functional roles of the leg muscles while pedaling in the recumbent position to the upright position to the upright position and (iii) determine whether leg muscle onset and offset timing for recumbent and upright pedaling respond similarly to changes in pedaling rate. To fulfill these objectives, surface electromyograms were recorded from 10 muscles of 15 subjects who pedaled in both the recumbent and upright positions at 75, 90, and 105 rpm and at a constant workrate of 250 W. Patterns of muscle activation were compared over the crank cycle. Functional roles of muscles in recumbent and upright pedaling were compared using the percent of integrated activation in crank cycle regions determined previously for upright pedaling. Muscle onset and offset timing were also compared. When the crank cycle was adjusted for orientation in the gravity field, the activation patterns for the two positions were similar. Functional roles of the muscles in the two positions were similar as well. In recumbent pedaling, the uniarticular hip and knee extensors functioned primarily to produce power during the extension region of the crank cycle, whereas the biarticular muscles crossing the hip and knee functioned to propel the leg through the transition regions of the crank cycle. The adaptations of the muscles to changes in pedaling rate were also similar for the two body positions with the uniarticular power producing muscles of the hip and knee advancing their activity to earlier in the crank cycle as the pedaling rate increased. This information on the functional roles of the leg muscles provides a basis by which to form functional groups, such as power-producing muscles and transition muscles, to aid in the development of rehabilitative pedaling exercises and recumbent pedaling simulations to further our understanding of task-dependent muscle coordination.     

Diurnal variations in cycling kinematics

Physiological and biomechanical constraints as well as their fluctuations throughout the day must be considered when studying determinant factors in the preferred pedaling rate of elite cyclists. The aim of this study was to monitor the diurnal variation of spontaneous pedaling rate and movement kinematics over the crank cycle. Twelve male competitive cyclists performed a submaximal exercise on a cycle ergometer for 15 min at 50% of their W(max). Two test sessions were performed at 06:00 and 18:00 h on two separate days to assess diurnal variation in the study variables. For each test session, the exercise bout was divided into three equivalent 5-min periods during which subjects were requested to use different pedal rates (spontaneous cadence, 70 and 90 rev min(-1)). Pedal rate and kinematics data (instantaneous pedal velocity and angle of the ankle) were collected. The results show a higher spontaneous pedal rate in the late afternoon than in the early morning (p < 0.001). For a given pedal rate condition, there was a less variation in pedal velocity during a crank cycle in the morning than in the late afternoon. Moreover, diurnal variations were observed in ankle mobility across the crank cycle, the mean plantar flexion observed throughout the crank cycle being greater in the 18:00 h test session (p < 0.001). These results suggest that muscular activation patterns during a cyclical movement could be under the influence of circadian fluctuations.     

Muscle contributions to specific biomechanical functions do not change in forward versus backward pedaling

Previous work had identified six biomechanical functions that need to be executed by each limb in order to produce a variety of pedaling tasks. The functions can be organized into three antagonistic pairs: an Ext/Flex pair that accelerates the foot into extension or flexion with respect to the pelvis, an Ant/Post pair that accelerates the foot anteriorly or posteriorly with respect to the pelvis, and a Plant/Dorsi pair that accelerates the foot into plantarflexion or dorsiflexion. Previous analyses of experimental data have inferred that muscles perform the same function during different pedaling tasks (e.g. forward versus backward pedaling) because the EMG timing was similar, but they did not present rigorous biomechanical analyses to assess whether a muscle performed the same biomechanical function, and if so, to what degree. Therefore, the objective of this study was to determine how individual muscles contribute to these biomechanical functions during two different motor tasks, forward and backward pedaling, through a theoretical analysis of experimental data. To achieve this objective, forward and backward pedaling simulations were generated and a mechanical energy analysis was used to examine how muscles generate, absorb or transfer energy to perform the pedaling tasks. The results showed that the muscles contributed to the same primary Biomechanical functions in both pedaling directions and that synergistic performance of certain functions effectively accelerated the crank. The gluteus maximus worked synergistically with the soleus, the hip flexors worked synergistically with the tibialis anterior, and the vasti and hamstrings functioned independently to accelerate the crank. The rectus femoris used complex biomechanical mechanisms including negative muscle work to accelerate the crank. The negative muscle work was used to transfer energy generated elsewhere (primarily from other muscles) to the pedal reaction force in order to accelerate the crank. Consistent with experimental data, a phase shift was required from those muscles contributing to the Ant/Post functions as a result of the different limb kinematics between forward and backward pedaling, although they performed the same biomechanical function. The pedaling simulations proved necessary to interpret the experimental data and identify motor control mechanisms used to accomplish specific motor tasks, as the mechanisms were often complex and not always intuitively obvious.     

Diurnal Variations in Cycling Kinematics

Physiological and biomechanical constraints as well as their fluctuations throughout the day must be considered when studying determinant factors in the preferred pedaling rate of elite cyclists. The aim of this study was to monitor the diurnal variation of spontaneous pedaling rate and movement kinematics over the crank cycle. Twelve male competitive cyclists performed a submaximal exercise on a cycle ergometer for 15 min at 50% of their W_max. Two test sessions were performed at 06:00 and 18:00 h on two separate days to assess diurnal variation in the study variables. For each test session, the exercise bout was divided into three equivalent 5‐min periods during which subjects were requested to use different pedal rates (spontaneous cadence, 70 and 90 rev min^?1). Pedal rate and kinematics data (instantaneous pedal velocity and angle of the ankle) were collected. The results show a higher spontaneous pedal rate in the late afternoon than in the early morning (p < 0.001). For a given pedal rate condition, there was a less variation in pedal velocity during a crank cycle in the morning than in the late afternoon. Moreover, diurnal variations were observed in ankle mobility across the crank cycle, the mean plantar flexion observed throughout the crank cycle being greater in the 18:00 h test session (p < 0.001). These results suggest that muscular activation patterns during a cyclical movement could be under the influence of circadian fluctuations.     

Determinants of metabolic cost during submaximal cycling.

The metabolic cost of producing submaximal cycling power has been reported to vary with pedaling rate. Pedaling rate, however, governs two physiological phenomena known to influence metabolic cost and efficiency: muscle shortening velocity and the frequency of muscle activation and relaxation. The purpose of this investigation was to determine the relative influence of those two phenomena on metabolic cost during submaximal cycling. Nine trained male cyclists performed submaximal cycling at power outputs intended to elicit 30, 60, and 90% of their individual lactate threshold at four pedaling rates (40, 60, 80, 100 rpm) with three different crank lengths (145, 170, and 195 mm). The combination of four pedaling rates and three crank lengths produced 12 pedal speeds ranging from 0.61 to 2.04 m/s. Metabolic cost was determined by indirect calorimetery, and power output and pedaling rate were recorded. A stepwise multiple linear regression procedure selected mechanical power output, pedal speed, and pedal speed squared as the main determinants of metabolic cost (R(2) = 0.99 +/- 0.01). Neither pedaling rate nor crank length significantly contributed to the regression model. The cost of unloaded cycling and delta efficiency were 150 metabolic watts and 24.7%, respectively, when data from all crank lengths and pedal speeds were included in a regression. Those values increased with increasing pedal speed and ranged from a low of 73 +/- 7 metabolic watts and 22.1 +/- 0.3% (145-mm cranks, 40 rpm) to a high of 297 +/- 23 metabolic watts and 26.6 +/- 0.7% (195-mm cranks, 100 rpm). These results suggest that mechanical power output and pedal speed, a marker for muscle shortening velocity, are the main determinants of metabolic cost during submaximal cycling, whereas pedaling rate (i.e., activation-relaxation rate) does not significantly contribute to metabolic cost.     

Patterns of leg muscle recruitment vary between novice and highly trained cyclists

This study compared patterns of leg muscle recruitment and coactivation, and the relationship between muscle recruitment, coactivation and cadence, in novice and highly trained cyclists. Electromyographic (EMG) activity of tibialis anterior (TA), tibialis posterior (TP), peroneus longus (PL), gastrocnemius lateralis (GL) and soleus (SOL) was recorded using intramuscular fine-wire electrodes. Four experimental conditions of varying cadence were investigated. Differences were evident between novice and highly trained cyclists in the recruitment of all muscles. Novice cyclists were characterized by greater individual variance, greater population variance, more extensive and more variable muscle coactivation, and greater EMG amplitude in periods between primary EMG bursts. Peak EMG amplitude increased linearly with cadence and was not different at individual preferred cadence in either novice or highly trained cyclists. However, EMG amplitude in periods between primary EMG bursts, as well as the duration of primary EMG bursts, increased with increasing cadence in novice cyclists but were not influenced by cadence in highly trained cyclists. Our findings suggest that muscle recruitment is highly skilled in highly trained cyclists and less refined in novice cyclists. More skilled muscle recruitment in highly trained cyclists is likely a result of neuromuscular adaptations due to repeated performance of the cycling movement in training and competition.     

Generating dynamic simulations of movement using computed muscle control

Computation of muscle excitation patterns that produce coordinated movements of muscle-actuated dynamic models is an important and challenging problem. Using dynamic optimization to compute excitation patterns comes at a large computational cost, which has limited the use of muscle-actuated simulations. This paper introduces a new algorithm, which we call computed muscle control, that uses static optimization along with feedforward and feedback controls to drive the kinematic trajectory of a musculoskeletal model toward a set of desired kinematics. We illustrate the algorithm by computing a set of muscle excitations that drive a 30-muscle, 3-degree-of-freedom model of pedaling to track measured pedaling kinematics and forces. Only 10 min of computer time were required to compute muscle excitations that reproduced the measured pedaling dynamics, which is over two orders of magnitude faster than conventional dynamic optimization techniques. Simulated kinematics were within 1 degrees of experimental values, simulated pedal forces were within one standard deviation of measured pedal forces for nearly all of the crank cycle, and computed muscle excitations were similar in timing to measured electromyographic patterns. The speed and accuracy of this new algorithm improves the feasibility of using detailed musculoskeletal models to simulate and analyze movement.     

Understanding muscle coordination of the human leg with dynamical simulations

Muscles coordinate multijoint motion by generating forces that cause reaction forces throughout the body. Thus, a muscle can redistribute existing segmental energy by accelerating some segments and decelerating others. In the process, a muscle may also produce or absorb energy, in which case its summed energetic effect on the segments is positive or negative, respectively. This Borelli Lecture shows how dynamical simulations derived from musculoskeletal models reveal muscle-induced segmental energy redistribution and muscle co-functions and synergies. Synergy occurs when co-excited muscles distribute segmental energy differently to execute the motor task. In maximum height jumping, high vertical velocity at lift-off occurs desirably at full body extension because biarticular leg muscles redistribute the energy produced by the uniarticular leg muscles. In pedaling, synergistic ankle plantarflexor force generation during leg extension allows the high energy produced by the uniarticular hip and knee extensors to be delivered to the crank. An analogous less-powerful flexor synergy exists during leg flexion. Hamstrings reduce crank deceleration during the leg extension-to-flexion transition by not only producing energy but delivering it to the crank through its contribution to the tangential (accelerating) crank force, though this hamstrings function occurs at the opposite (flexion-extension) transition when pedaling backwards. In walking, the eccentric quadriceps activity in early stance not only decelerates the leg but also accelerates the trunk. In mid-stance, the uni- and biarticular plantarflexors, by having opposite segmental energetic effects, act in synergy to support the whole body, so segmental potential and kinetic energy exchange can occur. To conclude, the extraction of unmeasurable variables from dynamical simulations emulating task kinematics, kinetics, and EMGs shows how the production of force and energy by individual muscles contribute to the energy flow among the individual segments during task execution.     

A theoretical analysis of preferred pedaling rate selection in endurance cycling

One objective of this study was to investigate whether neuromuscular quantities were associated with preferred pedaling rate selection during submaximal steady-state cycling from a theoretical perspective using a musculoskeletal model with an optimal control analysis. Specific neuromuscular quantities of interest were the individual muscle activation, force, stress and endurance. To achieve this objective, a forward dynamic model of cycling and optimization framework were used to simulate pedaling at three different rates of 75, 90 and 105 rpm at 265 W. The pedaling simulations were produced by optimizing the individual muscle excitation timing and magnitude to reproduce experimentally collected data. The results from these pedaling simulations indicated that all neuromuscular quantities were minimized at 90 rpm when summed across muscles. In the context of endurance cycling, these results suggest that minimizing neuromuscular fatigue is an important mechanism in pedaling rate selection. A second objective was to determine whether any of these quantities could be used to predict the preferred pedaling rate. By using the quantities with the strongest quadratic trends as the performance criterion to be minimized in an optimal control analysis, these quantities were analyzed to assess whether they could be further minimized at 90 rpm and produce normal pedaling mechanics. The results showed that both the integrated muscle activation and average endurance summed across all muscles could be further minimized at 90 rpm indicating that these quantities cannot be used individually to predict preferred pedaling rates.     

Simulation analysis of muscle activity changes with altered body orientations during pedaling

Testing hypotheses related to the effect of gravitational orientation on neural control mechanisms is difficult for most locomotor tasks, like walking, because body orientation with respect to gravity affects both sensorimotor control and task mechanics. To examine the mechanical effect of body orientation independently from changes in workload and posture, Brown et al. (J. Biomech. 29 p. 1349, 1996) studied pedaling at altered body orientations. They found that subjects pedaling at different orientations changed needlessly their muscle excitations, putatively to preserve body-upright pedaling kinematics. We tested the feasibility of this hypothesis using simulations based on a three biomechanical-function pair organization for control of lower limb muscles (limb extension/flexion pair, extension/flexion transition pair, and foot plantarflexion/dorsiflexion pair), where each pair consists of alternating agonistic/antagonistic muscles. Adjustment of only three parameters, one to scale the muscle excitations of each pair, was sufficient to preserve pedaling kinematics to altered body orientation. Because these adjustments produced changes in muscle excitation and net joint moments similar to those observed in pedaling subjects, the hypothesis is supported. Moreover, the effectiveness of a decoupled gain adjustment procedure where each parameter was adjusted by error in only one aspect of the pedaling trajectory during each iteration (i.e., cadence adjusted the Ext/Flex parameter; peak-to-peak variation in crank velocity over the cycle adjusted the transition parameter; average ankle angle over the cycle adjusted the foot parameter) further supports the distinct function of each muscle pair.     

Laboratory versus outdoor cycling conditions: differences in pedaling biomechanics

The aim of our study was to compare crank torque profile and perceived exertion between the Monark ergometer (818 E) and two outdoor cycling conditions: level ground and uphill road cycling. Seven male cyclists performed seven tests in seated position at different pedaling cadences: (a) in the laboratory at 60, 80, and 100 rpm; (b) on level terrain at 80 and 100 rpm; and (c) on uphill terrain (9.25% grade) at 60 and 80 rpm. The cyclists exercised for 1 min at their maximal aerobic power. The Monark ergometer and the bicycle were equipped with the SRM Training System (Schoberer, Germany) for the measurement of power output (W), torque (Nxm), pedaling cadence (rpm), and cycling velocity (kmxh-1). The most important findings of this study indicate that at maximal aerobic power the crank torque profiles in the Monark ergometer (818 E) were significantly different (especially on dead points of the crank cycle) and generate a higher perceived exertion compared with road cycling conditions.     

Sloped muscle excitation waveforms improve the accuracy of forward dynamic simulations

Mathematical models of the muscle excitation are useful in forward dynamic simulations of human movement tasks. One objective was to demonstrate that sloped as opposed to rectangular excitation waveforms improve the accuracy of forward dynamic simulations. A second objective was to demonstrate the differences in simulated muscle forces using sloped versus rectangular waveforms. To fulfill these objectives, surface EMG signals from the triceps brachii and elbow joint angle were recorded and the intersegmental moment of the elbow joint was computed from 14 subjects who performed two cyclic elbow extension experiments at 200 and 300 deg/s. Additionally, the surface EMG signals from the leg musculature, joint angles, and pedal forces were recorded and joint intersegmental moments were computed during a more complex pedaling task (90 rpm at 250 W). Using forward dynamic simulations, four optimizations were performed in which the experimental intersegmental moment was tracked for the elbow extension tasks and four optimizations were performed in which the experimental pedal angle, pedal forces, and joint intersegmental moments were tracked for the pedaling task. In these optimizations the three parameters (onset and offset time, and peak excitation) defining the sloped (triangular, quadratic, and Hanning) and rectangular excitation waveforms were varied to minimize the difference between the simulated and experimentally tracked quantities. For the elbow extension task, the intersegmental elbow moment root mean squared error, onset timing error, and offset timing error were less from simulations using a sloped excitation waveform compared to a rectangular excitation waveform (p<0.001). The average and peak muscle forces were from 7% to 16% larger and 20-28% larger, respectively, when using a rectangular excitation waveform. The tracking error for pedaling also decreased when using a sloped excitation waveform, with the quadratic waveform generating the smallest tracking errors for both tasks. These results support the use of sloped over rectangular excitation waveforms to establish greater confidence in the results of forward dynamic simulations.     

Crank inertial load has little effect on steady-state pedaling coordination

Inertial load can affect the control of a dynamic system whenever parts of the system are accelerated ordeclerated. During steady-state pedating, because within-cycle variations in crank angular acceleration still exist, the amount of crank inertia present (which varies widely with road-riding gear ratio) may affect the within-cycle coordination of muscles. However, the effect of inertial load on steady-state pedaling coordination is almos always assumed to be negligible, since the net mechanical energy per cycle developed by muscles only depends on the constant cadence and workload. This study tests the hypothesis that under steady-state conditions, the net joint torques produced by muscles at the hip, knee, and ankle are unaffected by crank inertial load. To perform the investigation, we constructed a pedaling apparatus which could emulate the low inertial load of a standard ergometer or the high inertial load of a road bicycle in high gear. Crank angle and bilateral pedal force and angle data were collected from ten subjects instructed to pedal steadily (i.e. constant speed across cycles) and smoothly (i.e. constant speed within a cycle) against both inertias at a constant workload. Virtually no statistically significant changes were found in the net hip and knee muscle joint torques calculated from an inverse dynamics analysis. Though the net ankle muscle joint torque, as well as the one- and two-legged crank torque, showed statistically significant increases at the higher inertia, the changes were small. In contrast, large statistically significant reductions were found in crank kinematic variability both within a cycle and between cycles (i.e. cadence), primarily because a larger inertial load means a slower crank dynamic response. Nonetheless, the reduction in cadence variability was somewhat attenuated by a large statistically significant increase in one-legged crank torque variability. We suggest, therefore, that muscle coordination during steady-state pedaling is largely unaffected, though less well regulated, when crank inertial load is increased.     

A comparison of muscular mechanical energy expenditure and internal work in cycling

The hypothesis that the sum of the absolute changes in mechanical energy (internal work) is correlated with the muscular mechanical energy expenditure (MMEE) was tested using two elliptical chainrings, one that reduced and one that increased the internal work (compared to circular). Upper and lower bounds were put on the extra MMEE (work done by net joint torques in excess of the external work) with respect to the effect of intercompensation between joint torques due to biarticular muscles. This was done by having two measures of MMEE, one that allowed no intercompensation and one that allowed complete intercompensation between joints spanned by biarticular muscles. Energy analysis showed no correlation between internal work and the two measures of MMEE. When compared to circular, the chainring that reduced internal work increased MMEE, and phases of increased crank velocity associated with the elliptical shape resulted in increased power absorbed by the upstroke leg as it was accelerated against gravity. The resulting negative work necessitated additional positive work. Thus, the hypothesis that the internal work is correlated with MMEE was found to be invalid, and the total mechanical work done cannot be estimated by summing the internal and external work. Changes in the dynamics of cycling caused by a non-circular chainring may affect performance and must be considered during the non-circular chainring design process.     

A phenomenological model and validation of shortening-induced force depression during muscle contractions

History-dependent effects on muscle force development following active changes in length have been measured in a number of experimental studies. However, few muscle models have included these properties or examined their impact on force and power output in dynamic cyclic movements. The goal of this study was to develop and validate a modified Hill-type muscle model that includes shortening-induced force depression and assess its influence on locomotor performance. The magnitude of force depression was defined by empirical relationships based on muscle mechanical work. To validate the model, simulations incorporating force depression were developed to emulate single muscle in situ and whole muscle group leg extension experiments. There was excellent agreement between simulation and experimental values, with in situ force patterns closely matching the experimental data (average RMS error <1.5 N) and force depression in the simulated leg extension exercise being similar in magnitude to experimental values (6.0% vs. 6.5%, respectively). To examine the influence of force depression on locomotor performance, simulations of maximum power pedaling with and without force depression were generated. Force depression decreased maximum crank power by 20–40%, depending on the relationship between force depression and muscle work used. These results indicate that force depression has the potential to substantially influence muscle power output in dynamic cyclic movements. However, to fully understand the impact of this phenomenon on human movement, more research is needed to characterize the relationship between force depression and mechanical work in large muscles with different morphologies.     

Reproducibility of eight lower limb muscles activity level in the course of an incremental pedaling exercise.

Despite the wide use of surface electromyography (EMG) recorded during dynamic exercises, the reproducibility of EMG variables has not been fully established in a course of a dynamic leg exercise. The aim of this study was to investigate the reproducibility of eight lower limb muscles activity level during a pedaling exercise performed until exhaustion. Eight male were tested on two days held three days apart. Surface EMG was recorded from vastus lateralis, rectus femoris (RF), vastus medialis, semimembranosus, biceps femoris, gastrocnemius lateral, gastrocnemius medianus and tibialis anterior during incremental exercise test. The root mean square, an index of global EMG activity, was averaged every five crank revolutions (corresponding to about 3 s at 85 rpm) throughout the tests. Despite inter-subjects variations, we showed a high reproducibility of the activity level of lower limb muscles during a progressive pedaling exercise performed until exhaustion. However, RF muscle seemed to be the less reproducible of the eight muscles investigated during incremental pedaling exercise. These results suggest that each subject adopt a personal muscle activation strategy in a course of an incremental cycling exercise but fatigue phenomenon can induce some variations in the most fatigable muscles (RF).