The neuromuscular fatigue induced by repeated scrums generates instability that can be limited by appropriate recovery.

The aim of this study was to evaluate the influence of the fatigue on the machine scrum pushing sagittal forces during repeated scrums and to determine the origin of the knee extensor fatigue. Twelve elite U23 rugby union front row players performed six 6-s scrums every 30 s against a dynamic scrum machine with passive or active recovery. The peak, average, and the standard deviation of the force were measured. A neuromuscular testing procedure of the knee extensors was carried out before and immediately after the repeated scrum protocol including maximal voluntary force, evoked force, and voluntary activation. The average and peak forces did not decrease after six scrums with passive recovery. The standard deviation of the force increased by 70.2 ± 42.7% (P < 0.001). Maximal voluntary/evoked force and voluntary activation decreased (respectively 25.1 ± 7.0%, 14.6 ± 5.5%, and 24 ± 9.9%; P < 0.001). The standard deviation of the force did not increase with active recovery and was associated with lower decrease of maximal voluntary/evoked force and voluntary activation (respectively 12.8 ± 7.9%, 4.9 ± 6.5%, and 7.6 ± 4.1%; all P < 0.01). As a conclusion repeated scrummaging induced an increased machine scrum pushing instability associated with central and peripheral fatigue of the knee extensors. Active recovery seems to limit all these manifestations of fatigue.

Contraction velocity influence the magnitude and etiology of neuromuscular fatigue during repeated maximal contractions.

This study aimed to compare the magnitude and etiology of neuromuscular fatigue during maximal repeated contractions performed in two contraction modes (concentric vs isometric) and at two contraction velocities (30/s vs 240°/s). Eleven lower limb-trained males performed 20 sets of maximal contractions at three different angular velocities: 0°/s (KE0), 30/s (KE30), and 240°/s (KE240). Cumulated work, number of contraction, duty cycle, and contraction time were controlled. Torque, superimposed and resting twitches, as well as gas exchange, were analyzed. Increasing contraction velocity was associated with greater maximal voluntary torque loss (KE0: -9.8 ± 3.9%; KE30: -16.4 ± 8.5%; KE240: -32.6 ± 6.3%; P < 0.05). Interestingly, the torque decrease was similar for a given cumulated work. Compared with KE0, KE240 generated a greater evoked torque loss (Db100: -24.3 ± 5.3% vs -5.9 ± 6.9%; P < 0.001), a higher O2 consumption (23.7 ± 6.4 mL/min/kg vs 15.7 ± 3.8 mL/min/kg; P < 0.001), but a lower voluntary activation (VA) loss (-4.3 ± 1.6% vs -11.2 ± 4.9%; P < 0.001). The neuromuscular perturbations were intermediate for KE30 (Db100: -10.0 ± 6.8%; VA: -7.2 ± 2.8%). Although the amount of mechanical work cumulated strongly determined the magnitude of torque decrease, the contraction velocity and mode influenced the origin of the neuromuscular fatigue. The metabolic stress and peripheral fatigue increased but reduction of VA is attenuated when the contraction velocity increased from 0°/s to 240°/s.

Torque and power-velocity relationships in cycling: relevance to track sprint performance in world-class cyclists.

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.

Determinants of the energy cost of front-crawl swimming in children.

The aim of the present study was to define the determinants of the energy cost of swimming (Cs) in children. Eleven healthy children [mean (SD) age: 12.42 (0.53) years] who practised 7.5-8.5 h x week(-1) volunteered to take part in this study. Anthropometric dimensions such as height (H), body mass (BM), hydrostatic lift (HL) and body surface area (SA) were measured. Forty-eight hours later when maximal oxygen consumption (VO(2max)) had been measured during 400 m of front-crawl swimming, Cs was measured over 200 m for three submaximal swimming speeds (0.9, 1.0 and 1.1 m x s(-1)). Oxygen consumption (Douglas bag method), stroke frequency (SF) and stroke length (SL) were calculated during the last 50 m of each 200 m. The mean (SD) VO(2max) of the young swimmers was 2.19 (0.38) l x min(-1) at a maximal aerobic velocity of 1.19 (0.03) m x s(-1). The values of for Cs at 0.9 m x s(-1), 1.0 m x s(-1) and 1.1 m x s(-1) were 29.27 (3.13) ml x m(-1), 30.25 (3.68) ml x m(-1) and 32.91 (3.59) ml x m(-1), respectively. There was a significant increase in Cs with increasing swim speed. In addition, SF increased with velocity when SL remained constant. The values for SF at 0.9 m x s(-1), 1.0 m x s(-1) and 1.1 m x s(-1) were 31.28 (4.36) strokes x min(-1), 34.10 (5.09) strokes x min(-1) and 38.31 (5.90) strokes x min(-1), respectively. No significant correlation was obtained between Cs and the anthropometric or stroking parameters. It was concluded that for young swimmers, anthropometric characteristics, SF and SL are not good predictors of Cs in front-crawl swimming, and that further studies are needed to explore the influence of underwater torque on Cs in prepubertal children.

Influence of fatigue on EMG/force ratio and cocontraction in cycling.

PURPOSE: The purpose of the present study was to observe force and power losses and electromyographic manifestations of fatigue during repeated sprints performed on a friction-loaded cycle ergometer. METHODS: Ten subjects performed 15 maximal 5-s sprints with 25-s rests between them. Power, velocity, and torque were measured during sprints 1 and 13 and during two submaximal constant-velocity (50 rpm) periods of cycling performed before and after the sprints. The EMG signals of five leg muscles were stored to determine the EMG/force ratio of power producer muscles and the coactivation of antagonist muscles. The power producer muscles were activated to the same level during sprints 1 and 13, despite a loss of force, whereas the vastus lateralis muscle was recruited more during the submaximal cycling period under fatigue conditions. RESULTS: This led to an increased EMG/force ratio for the power producer muscles, indicating the peripheral fatigue status of these muscles. Antagonist muscles were less activated during the sprints after fatigue; whereas they stayed unchanged during the last submaximal cycling period. CONCLUSIONS: This suggests that there is a decrease in coactivation as agonist force is lost. This decrease in coactivation under fatigue conditions has not been previously reported and is probably due to the training status of the subjects. Subjects may have learned to better use their antagonist muscles to efficiently transfer force and power to the rotating pedal. This coordination can be adapted to cope with fatigue of the power producer muscles.

A method for assessing muscle fatigue during sprint exercise in humans using a friction-loaded cycle ergometer.

This study investigated the mechanical changes induced by muscle fatigue caused by repeated sprints and determined whether a friction-loaded cycle ergometer has any advantages for assessing muscle fatigue. Nine subjects performed 15 sprints, each of 5 s with a 25-s rest, on a friction-loaded cycle ergometer. The averaged force, power and velocity of each push-off were calculated. Maximal power decreased by 17.9%, with a concomitant slowing of muscle contraction, but without any change in the maximal force. These results demonstrated that repeated sprints slow down muscle contraction, leading to a fall in maximal power without any loss of force. This would suggest that fast twitch fibres are selectively fatigued by repeated sprints. However, the ergometer used in the present study made it difficult to evaluate the relative influences of contraction velocity and sprinting time. This was certainly the most important limitation. On the other hand, it showed the advantage of measuring instantaneous power and total work dissipated in the environment simultaneously. It also permitted a force-velocity relationship to be obtained from a single sprint and this relationship is known to be closely related to the muscle fibre composition.

Optimal velocity for maximal power production in non-isokinetic cycling is related to muscle fibre type composition.

To determine whether power-velocity relationships obtained on a nonisokinetic cycle ergometer could be related to muscle fibre type composition, ten healthy specifically trained subjects (eight men and two women) performed brief periods of maximal cycling on a friction loaded cycle ergometer. Frictional force and flywheel velocity were recorded at a sampling frequency of 200 Hz. Power output was computed as the product of velocity and inertial plus frictional forces. Force, velocity and power were averaged over each down stroke. Muscle fibre content was determined by biopsy of the vastus lateralis muscle. Maximal down stroke power [14.36 (SD 2.37)W.kg-1] and velocity at maximal power [120 (SD 8) rpm] were in accordance with previous results obtained on an isokinetic cycle ergometer. The proportion of fast twitch fibres expressed in terms of cross sectional area was related to optimal velocity (r = 0.88, P < 0.001), to squat jump performance (r = 0.78, P < 0.01) and tended to be related to maximal power expressed per kilogram of body mass (r = 0.60, P = 0.06). Squat jump performance was also related to cycling maximal power. expressed per kilogram of body mass (r = 0.87, P < 0.01) and to optimal velocity (r = 0.86, P < 0.01). All these data suggest that the nonisokinetic cycle ergometer is a good tool with which to evaluate the relative contribution of type II fibres to maximal power output. Furthermore, the strong correlation obtained demonstrated that optimal velocity, when related to training status, would appear to be the most accurate parameter to explore the fibre composition of the knee extensor muscle.

Relationships between postcompetition blood lactate concentration and average running velocity over 100-m and 200-m races.

The relationships between anaerobic glycolysis and average velocity (v) sustained during sprint running were studied in 12 national level male sprinters. A blood sample was obtained within 3 min of the completion of semi-finals and finals in the 100-m and 200-m Cameroon national championships and blood lactate concentration ([la-]b) was measured. The 35-m times were video-recorded. The 100-m and 200-m [la-]b were 8.5 (SD 0.8) and 10.3 (SD 0.8) mmol.l-1, respectively. These were not correlated with the performances. Over 200 m [la-]b was correlated with the v sustained over the last 165 m (r = 0.65, P < 0.05). In the 9 athletes who participated in both the 100-m and 200-m races, the difference between the [la-]b measured at the end of the two races was negatively correlated to the difference in v sustained over the two races (r = 0.76, P > 0.02). Energy expenditure during sprint running was estimated from the [la-]b values. This estimate was mainly based on the assumption that a 1 mmol.l-1 increase in [la-]b corresponds to the energy produced by the utilization of 3.30 ml O2.kg-1. The energy cost of running was estimated at 0.275 (SD 0.02) ml O2.kg-1.m-1 over 200-m and 0.433 (SD 0.03) ml O2.kg-1.m-1 over 100-m races. These results would suggest that at the velocities studied anaerobic glycolysis contributes to at least 55% of the energy expenditure related to spring running. However, the influence of both mechanical factors and the contribution of other energy processes obscure the relationship between [la-]b and performance.