This study aimed to validate a simple field method for determining force- and power-velocity relationships and mechanical effectiveness of force application during sprint running. The proposed method, based on an inverse dynamic approach applied to the body center of mass, estimates the step-averaged ground reaction forces in runner's sagittal plane of motion during overground sprint acceleration from only anthropometric and spatiotemporal data. Force- and power-velocity relationships, the associated variables, and mechanical effectiveness were determined (a) on nine sprinters using both the proposed method and force plate measurements and (b) on six other sprinters using the proposed method during several consecutive trials to assess the inter-trial reliability. The low bias (<5%) and narrow limits of agreement between both methods for maximal horizontal force (638 ± 84 N), velocity (10.5 ± 0.74 m/s), and power output (1680 ± 280 W); for the slope of the force-velocity relationships; and for the mechanical effectiveness of force application showed high concurrent validity of the proposed method. The low standard errors of measurements between trials (<5%) highlighted the high reliability of the method. These findings support the validity of the proposed simple method, convenient for field use, to determine power, force, velocity properties, and mechanical effectiveness in sprint running.

The objective of this study was to characterize the mechanics of maximal running sprint acceleration in high-level athletes. Four elite (100-m best time 9.95-10.29 s) and five sub-elite (10.40-10.60 s) sprinters performed seven sprints in overground conditions. A single virtual 40-m sprint was reconstructed and kinetics parameters were calculated for each step using a force platform system and video analyses. Anteroposterior force (FY), power (PY), and the ratio of the horizontal force component to the resultant (total) force (RF, which reflects the orientation of the resultant ground reaction force for each support phase) were computed as a function of velocity (V). FY-V, RF-V, and PY-V relationships were well described by significant linear (mean R(2) of 0.892 ± 0.049 and 0.950 ± 0.023) and quadratic (mean R(2) = 0.732 ± 0.114) models, respectively. The current study allows a better understanding of the mechanics of the sprint acceleration notably by modeling the relationships between the forward velocity and the main mechanical key variables of the sprint. As these findings partly concern world-class sprinters tested in overground conditions, they give new insights into some aspects of the biomechanical limits of human locomotion.

Although pedaling is constrained by the circular trajectory of the pedals, it is not a simple movement. This review attempts to provide an overview of the pedaling technique using an electromyographic (EMG) approach. Literature concerning the electromyographic analysis of pedaling is reviewed in an effort to make a synthesis of the available information, and to point out its relevance for researchers, clinicians and/or cycling/triathlon trainers. The first part of the review depicts methodological aspects of the EMG signal recording and processing. We show how the pattern of muscle activation during pedaling can be analyzed in terms of muscle activity level and muscle activation timing. Muscle activity level is generally quantified with root mean square or integrated EMG values. Muscle activation timing is studied by defining EMG signal onset and offset times that identify the duration of EMG bursts and, more recently, by the determination of a lag time maximizing the cross-correlation coefficient. In the second part of the review, we describe whether the patterns of the lower limb muscles activity are influenced by numerous factors affecting pedaling such as power output, pedaling rate, body position, shoe-pedal interface, training status and fatigue. Some research perspectives linked to pedaling performance are discussed throughout the manuscript and in the conclusion.

The aims of the present study were both to describe anthropometrics and cycling power-velocity characteristics in top-level track sprinters, and to test the hypothesis that these variables would represent interesting predictors of the 200 m track sprint cycling performance. Twelve elite cyclists volunteered to perform a torque-velocity test on a calibrated cycle ergometer, after the measurement of their lean leg volume (LLV) and frontal surface area (A(p)), in order to draw torque- and power-velocity relationships, and to evaluate the maximal power (P(max)), and both the optimal pedalling rate (f(opt)) and torque (T(opt)) at which P (max) is reached. The 200 m performances--i.e. velocity (V200) and pedalling rate (f 200)--were measured during international events (REC) and in the 2002 French Track Cycling Championships (NAT). P(max), f(opt), and T(opt) were respectively 1600 +/- 116 W, 129.8 +/- 4.7 rpm and 118.5 +/- 9.8 N . m. P(max) was strongly correlated with T(opt) (p < 0.001), which was correlated with LLV (p < 0.01). V200 was related to P(max) normalized by A(p) (p < or = 0.05) and also to f(opt) (p < 0.01) for REC and NAT. f 200 (155.2 +/- 3, REC; 149 +/- 4.3, NAT) were significantly higher than f(opt) (p < 0.001). These findings demonstrated that, in this population of world-class track cyclists, the optimization of the ratio between P(max) and A(p) represents a key factor of 200 m performance. Concerning the major role also played by f(opt), it is assumed that, considering high values of f 200, sprinters with a high value of optimal pedalling rate (i.e. lower f200-f(opt) difference) could be theoretically in better conditions to maximize their power output during the race and hence performance.

Hug F, Turpin NA, Couturier A, Dorel S. Consistency of muscle synergies during pedaling across different mechanical constraints. J Neurophysiol 106: 91-103, 2011. First published April 13, 2011 doi:10.1152/jn.01096.2010The purpose of the present study was to determine whether muscle synergies are constrained by changes in the mechanics of pedaling. The decomposition algorithm used to identify muscle synergies was based on two components: "muscle synergy vectors," which represent the relative weighting of each muscle within each synergy, and "synergy activation coefficients," which represent the relative contribution of muscle synergy to the overall muscle activity pattern. We hypothesized that muscle synergy vectors would remain fixed but that synergy activation coefficients could vary, resulting in observed variations in individual electromyographic (EMG) patterns. Eleven cyclists were tested during a submaximal pedaling exercise and five all-out sprints. The effects of torque, maximal torque-velocity combination, and posture were studied. First, muscle synergies were extracted from each pedaling exercise independently using non-negative matrix factorization. Then, to crossvalidate the results, muscle synergies were extracted from the entire data pooled across all conditions, and muscle synergy vectors extracted from the submaximal exercise were used to reconstruct EMG patterns of the five all-out sprints. Whatever the mechanical constraints, three muscle synergies accounted for the majority of variability [mean variance accounted for (VAF) ϭ 93.3 Ϯ 1.6%, VAF muscle Ͼ 82.5%] in the EMG signals of 11 lower limb muscles. In addition, there was a robust consistency in the muscle synergy vectors. This high similarity in the composition of the three extracted synergies was accompanied by slight adaptations in their activation coefficients in response to extreme changes in torque and posture. Thus, our results support the hypothesis that these muscle synergies reflect a neural control strategy, with only a few timing adjustments in their activation regarding the mechanical constraints.module; non-negative matrix factorization; motor control; cycling THE REDUNDANCY of the musculoskeletal system (Bernstein 1967) implies vast degrees of freedom. This provides great flexibility but makes the control of these degrees of freedom extremely complex. Consequently, the question of how the central nervous system coordinates activity among numerous muscles is central to understanding motor control. Low-dimensional modules formed by muscles activated in synchrony, named muscle synergies, have been proposed as building blocks that could simplify the construction of motor behaviors (2005) reported that combinations of a small number of synergies accounted for a large fraction of the variation in the EMG patterns observed during jumping, swimming, and walking in frogs. However, due to different muscle architectures and fiber type composition (and thus to different mechanical advantages) among muscles participating in the same mus...

Our aim was to determine whether muscle synergies are similar across trained cyclists (and thus whether the same locomotor strategies for pedaling are used), despite interindividual variability of individual EMG patterns. Nine trained cyclists were tested during a constant-load pedaling exercise performed at 80% of maximal power. Surface EMG signals were measured in 10 lower limb muscles. A decomposition algorithm (nonnegative matrix factorization) was applied to a set of 40 consecutive pedaling cycles to differentiate muscle synergies. We selected the least number of synergies that provided 90% of the variance accounted for VAF. Using this criterion, three synergies were identified for all of the subjects, accounting for 93.5+/-2.0% of total VAF, with VAF for individual muscles ranging from 89.9+/-8.2% to 96.6+/-1.3%. Each of these synergies was quite similar across all subjects, with a high mean correlation coefficient for synergy activation coefficients (0.927+/-0.070, 0.930+/-0.052, and 0.877+/-0.110 for synergies 1-3, respectively) and muscle synergy vectors (0.873+/-0.120, 0.948+/-0.274, and 0.885+/-0.129 for synergies 1-3, respectively). Despite a large consistency across subjects in the weighting of several monoarticular muscles into muscle synergy vectors, we found larger interindividual variability for another monoarticular muscle (soleus) and for biarticular muscles (rectus femoris, gastrocnemius lateralis, biceps femoris, and semimembranosus). This study demonstrated that pedaling is accomplished by the combination of the similar three muscle synergies among trained cyclists. The interindividual variability of EMG patterns observed during pedaling does not represent differences in the locomotor strategy for pedaling.

This study aimed to compare the force (F)-velocity (v)-power (P)-time (t) relationships of female and male world-class sprinters. A total of 100 distance-time curves (50 women and 50 men) were computed from international 100-m finals, to determine the acceleration and deceleration phases of each race: (a) mechanical variables describing the velocity, force, and power output; and (b) F-P-v relationships and associated maximal power output, theoretical force and velocity produced by each athlete (P , F , and V ). The results showed that the maximal sprint velocity (V ) and mean power output (W/kg) developed over the entire 100 m strongly influenced 100-m performance (r > -0.80; P ≤ 0.001). With the exception of mean force (N/kg) developed during the acceleration phase or during the entire 100 m, all of the mechanicals variables observed over the race were greater in men. Shorter acceleration and longer deceleration in women may explain both their lower V and their greater decrease in velocity, and in turn their lower performance level, which can be explained by their higher V and its correlation with performance. This highlights the importance of the capability to keep applying horizontal force to the ground at high velocities.

This study demonstrates that the strain applied to human muscle fibres during eccentric contractions strongly influences the magnitude of muscle damage in vivo. Achilles tendon compliance decreases the amount of strain, while architectural gear ratio may moderately contribute to attenuating muscle fascicle lengthening and hence muscle damage. Further studies are necessary to explore the impact of various types of task to fully understand the contribution of muscle-tendon interactions during active lengthening to muscle damage.