Maximum Mean Power Research Articles

Influence of Pedaling Cadence and Incremental Protocol on the Estimation of EMGFT

Duff, TM, Fournier, H, Hopp, OB, Ochshorn, E, Sanders, ES, Stevens, RE, and Malek, MH. Influence of pedaling cadence and incremental protocol on the estimation of EMGFT. J Strength Cond Res 30(8): 2206-2211, 2016-Theoretically, the electromyographic fatigue threshold (EMGFT) is the highest exercise intensity that an individual can exercise at indefinitely without an increase in electromyography (EMG) amplitude. This index is estimated from a single incremental test. There are, however, factors that may influence EMG amplitude such as pedaling cadence or the incremental protocol used. The purposes of this study were to determine whether different pedaling cadences and/or incremental protocols influence the estimation of the EMGFT. Eight healthy college-aged men performed incremental cycle ergometry on three separate visits. The participants exercised using the following combinations of pedaling cadences and incremental protocols in random order: 25 W at 70 RPM; 13 W at 70 RPM; and 25 W at 100 RPM. The EMGFT value was determined from the vastus lateralis muscle of each participant for each of the three conditions. Separate 1-way repeated measures analysis of variances were performed to determine mean differences for various outcome indices. The mean maximal power output for the 13 W at 70 RPM condition was significantly lower than the two other conditions. There were, however, no significant mean differences (F (2,14) = 2.03; p = 0.169) for EMGFT between the three conditions. The findings of this study indicated that different pedaling cadences and incremental protocols did not influence the estimation of the EMGFT.

A symbol timing recovery algorithm of M-PSK signals for burst modem applications with small packet size

Feedforward symbol timing recovery techniques are particularly important for initial acquisition in burst modems. However, these techniques either have large calculation burden or sensitive to frequency offsets. In this paper, we proposed an efficient symbol timing recovery algorithm of MPSK signals named OMQ (Ordered Maximum power using Quadratic approximation partially) algorithm which is based on the Quadratic Approximation (QA) algorithm. We used ordered statistic sorting method to reduce the computational complexity further, meanwhile maximum mean power principle was used to decrease frequency offset sensitivity. The proposed algorithm adopts estimation-down sampling structure which is suitable for small packet size transmission. The results show that, while comparing with the QA algorithm, the computational complexity is reduced by 75% at most when 8 samples per symbol are used. The proposed algorithm shows better performance in terms of the jitter variance and sensitivity to frequency offsets.

A new physical performance classification system for elite handball players: cluster analysis.

The aim of the present study was to identify different cluster groups of handball players according to their physical performance level assessed in a series of physical assessments, which could then be used to design a training program based on individual strengths and weaknesses, and to determine which of these variables best identified elite performance in a group of under-19 [U19] national level handball players. Players of the U19 National Handball team (n=16) performed a set of tests to determine: 10 m (ST10) and 20 m (ST20) sprint time, ball release velocity (BRv), countermovement jump (CMJ) height and squat jump (SJ) height. All players also performed an incremental-load bench press test to determine the 1 repetition maximum (1RMest), the load corresponding to maximum mean power (LoadMP), the mean propulsive phase power at LoadMP (PMPPMP) and the peak power at LoadMP (PPEAKMP). Cluster analyses of the test results generated four groupings of players. The variables best able to discriminate physical performance were BRv, ST20, 1RMest, PPEAKMP and PMPPMP. These variables could help coaches identify talent or monitor the physical performance of athletes in their team. Each cluster of players has a particular weakness related to physical performance and therefore, the cluster results can be applied to a specific training programmed based on individual needs.

Maximum theoretical power absorption of connected floating bodies under motion constraints

In this paper, a mathematical model is presented to evaluate the maximum mean power that can be absorbed by a three-dimensional system of connected floating bodies in waves under a weighted global constraint. The constraint imposed on the motion amplitudes of the system can be used to limit the motions of the bodies in order to make sure that the assumption of linear theory for wave–structure interaction remains valid. The absorbed power of a structure can be considered as the difference between excitation and radiated power without consideration of practical power take off. The solutions for the maximum relative capture widths of rigidly connected two rafts have a good agreement with the calculated ones for the same rafts being seen as a single whole structure. Meanwhile, the results of maximum power absorption of two hinged slender rafts in cuboid shape give a good agreement as well with those by using slender-body approximations. Then dynamics of a hinged two rafts are studied and results show how the maximum efficiency is affected by raft width and restricting the motions.

Effects of Increased Muscle Strength and Muscle Mass on Endurance-Cycling Performance.

Despite early and ongoing debate among athletes, coaches, and sport scientists, it is likely that resistance training for endurance cyclists can be tolerated, promotes desired adaptations that support training, and can directly improve performance. Lower-body heavy strength training performed in addition to endurance-cycling training can improve both short- and long-term endurance performance. Strength-maintenance training is essential to retain strength gains during the competition season. Competitive female cyclists with greater lower-body lean mass (LBLM) tend to have ~4-9% higher maximum mean power per kg LBLM over 1 s to 10 min. Such relationships enable optimal body composition to be modeled. Resistance training off the bike may be particularly useful for modifying LBLM, whereas more cycling-specific training strategies like eccentric cycling and single-leg cycling with a counterweight have not been thoughtfully investigated in well-trained cyclists. Potential mechanisms for improved endurance include postponed activation of less efficient type II muscle fibers, conversion of type IIX fibers into more fatigue-resistant IIa fibers, and increased muscle mass and rate of force development.

Body Water Status and Short-term Maximal Power Output during a Multistage Road Bicycle Race (Giro d'Italia 2014).

An investigation of whether body water changes during the Giro d'Italia affected average maximal mean power (MMP) of different time durations and to establish whether phase-angle and body cell mass (BCM) are related to MMP in elite cyclists. Approximately 2 h after each stage of the race, a bioelectrical impedance analysis was performed on 8 cyclists and analysed according to bioelectrical impedance vector analyses. Additionally, MMP of different time durations were recorded during each stage. Body mass increased (p<0.001), vector-length shortened (p<0.001) and MMP15 (maximal mean power for 15 s; p=0.043) decreased in the course of the Giro d'Italia. The shortening of the vector was negatively related to MMP10 (r=- 0.749, p=0.032) and MMP15 (r=- 0.735, p=0.038) during stage 16 (heavy mountain-stage) and MMP60 (r=- 0.751, p=0.032), MMP300 (r=- 0.739, p=0.036) and MMP1800 (r=- 0.769, p=0.026) during stage 19 (time-trial). Additionally, the baseline phase-angle and BCM were associated to MMP15 best (r=0.781, p=0.022 and 0.756, p=0.030, respectively). In the course of the Giro d'Italia, MMP15 decreased, indicating progressive fatigue. The vector-length shortening and to some extent the body mass increase indicate that cyclists gained body water during the race. This gain was positively associated with performance during the last stages, possibly due to improved thermoregulation. Furthermore, phase-angle and BCM, shown to be linked to cellular function and to represent metabolic active tissue, reflect individual MMP of short duration in professional road cyclists.

Cardiovascular risk and fitness in veteran football players

ABSTRACTVeteran football players above 40 years have rarely been subject to scientific investigations. This is worrisome because their number is considerable and their cardiovascular risk probably increased. Therefore, a cross-sectional study was conducted in 100 football players between 40 and 63 years of age. This included a medical history and physical examination, venous blood sampling, measurement of resting blood pressure, a resting electrocardiogram (ECG), an exhaustive cycle ergometry and a multistage field test. Also, measurements of heart rate and blood lactate concentration were carried out during one typical training session and one match. Participants trained 1.0 ± 0.6 sessions per week and played 27 ± 8 matches per season. Of them, 19% were smokers. Resting blood pressure was 138 ± 15/88 ± 8 mmHg. Hypertension prevalence (WHO definition) was 66%. Total cholesterol averaged 220 ± 41 mg . dl−1, HDL 46 ± 13 mg . dl−1 and LDL 134 ± 33 mg . dl−1. The average 10-year risk for cardiovascular events (Framingham score) was 6%. Mean maximal power output on the cycle ergometer was 2.8 ± 0.6 W . kg−1, mean VO2peak 40.0 ± 7.3 ml . min−1 . kg−1. Comparing training and competition, no significant differences in cardiovascular and metabolic load were found. In summary, their cardiovascular risk was similar to age-adjusted reference values. However, they showed slightly better ergometric performance. More frequent training stimuli might be necessary to reach more favourable risk factor profiles. Training and competition lead to similar cardiocirculatory and metabolic stress which is considerably high and might put players into danger who have pre-existing cardiac disease.

Analysis of Mean Maximal Power in cycling with a modified Critical Power model allowing for a non-constant Anaerobic Work Capacity

Introduction : Since its introduction by Monod and Sherrer 1 the Critical Power model has been applied to the analysis of cycling performances. In this model the Critical Power CP is the highest power that can be sustained without fatigue, and the total amount of work that can be produced until fatigue at any level above CP is indicated as the anaerobic work capacity W’. As yet W’ is considered to be a constant quantity. However Mean Maximal Power data, indicated by MMP, or a (t lim ,P lim ) data set can by described adequately by this CP-model only in a limited time range, typically between t lim =20’ and t lim =60’. Although the model can also formally be applied to short efforts, the relevant parameters CP and W’ as obtained from short and long efforts will differ significantly. Therefore we propose a modified CP-W’ model that will describe the MMP curve for the full relevant time range. Theory and results: The standard critical power model is expressed as 𝑃 ð‘i = 𝐶𝑃 + where t is the limiting time that a power P can be sustained until exhaustion. This equation is valid for all values of P(t) > CP but it leads to a catastrophe for short sustainable times because lim → 𝑃 ð‘i = ∞ Therefore some authors have proposed a general modification 𝑃 ð‘i = 𝐶𝑃 + 𝑓 ð‘i wherethefunction 𝑓 ð‘i hastobechosensuchthat lim → 𝑃 ð‘i = 𝑃 !# and P max is the zero-extrapolated maximal power. The effective work that can be delivered above CP is then ð‘S ! = ð‘S 𝑓 ð‘i . Examination of a number of MMP curves have lead us to consider 2 sustainable time zones, each zone being described with an appropriate correction function f(t). The full MMP curve is described as 𝑃 ð‘i = 𝐶𝑃 + 1 − 1 − ð‘i 𝑈 ( 𝑇 − ð‘i ) 𝑈 ð‘i − ð‘i𝑠𝑤 + 𝑀𝐴𝑃 + ( 1 − 𝑒 / ) 𝑈 ( ð‘i𝑠𝑤 − ð‘i ) 𝑇 !# !# Where U(t) is the unit step function i.e. U(t ≥ 0)=1 and U(t SCP the available W eff is much lower than the saturation value. This indicates that for this cyclist any test at sustainable times shorter than Tscp = 22 minutes will inevitably lead to anomalously high values of CP and low values of W’. Conclusions : We have presented a new model describing the full MMP-curves. Detailed analysis of the MMP and the [P,W’] data yield a set of field-based power parameters CP, W’,SCP,T SCP , MAP, P max , I„ . This model lifts the long standing discrepancy between the determinations of CP from short or from long efforts. CP from short test is closely related to MAP, while CP from long times is related to Maximal Lactate Steady State. CP test should be performed in the exhaustive time interval where W eff ’ has a constant value, i.e. for times higher than T SCP . Further research may focus on the relevance of these objective parameters for qualifying the strengths of sprinters, punchers, time trialists and climbers.

Power-velocity curve: relevance of the SRM Ergometer for simulated cycling performance and constant duration tests

Introduction : When trying to obtain cycling performance capacity, a controlled laboratory setting is required to obtain valid and reliable results [1]. Ecological validity is important, as several studies found poor agreement between lab and field time trials [2,3]. To perform realistic time trials on an ergometer, it is important that the cyclist is able to 1) choose its own cadence, 2) that the ergometer accounts for changes in kinetic energy and 3) the ergometer accounts for the non-linear relation between air-frictional forces and velocity. The SRM Ergometer has a free mode with a gear box and a big flywheel, so requirements 1 and 2 are fulfilled. It is unknown if the brake algorithm of the ergometer is linear or non- linear and how this mimics real life cycling. The aim of the present study is therefore to determine the relationship between the mechanical power output and the velocity in the SRM ergometer compared to cycling on a velodrome. Methods : The relation between mechanical power output and velocity in incremental cycling on an SRM Ergometer (2Hz sampling rate) was determined with the ergometer set in the “Open End Test” mode, which allows the cyclist to freely choose his gear and self-select his pace. Power output and velocity were collected over 30 s intervals of steady state cycling per stage, resulting in the power-velocity curve. The SRM Ergometer was propelled using a dynamic calibration rig to simulate a pedalling cadence ranging from 60-160 rpm, with 10 rpm steps through gears 7- 12 of the Rohloff nave. The rig was attached to the crank of the SRM Ergometer via a counterbalanced double universal joint. The axle was centred at the bottom bracket of the SRM Ergometer and attached to the crank at the position of the left pedal. By upshifting gears and increasing cadence, a range of velocities and accompanying power outputs could be evaluated. The calibration rig was powered by a 3 Ph – AC electro motor with a maximum power output of 2.2 kW. Data of 2 elite track pursuit cyclists were obtained for comparison with the ergometer. Cyclist 1 rode in standard position and cyclist 2 in aerodynamic position on a 250 m indoor velodrome in Alkmaar, the Netherlands, with an air density of 1.19 and 1.20 kg.m3 respectively. The track bikes were equipped with a SRM 7 track system. Sample rate was set at 2 Hz. Two laps at six different velocities were cycled, starting at 30 km/h with an increase in velocity of 5 km/h to 55 km/h. For SRM ergometer cycling as well as for track cycling, trend lines were added based on least-squares fit, and coefficients of determination were obtained. The best fits were used to predict power output at fixed speeds between 25 and 60 km/h for the ergometer and track cyclists. From these data Pearson product-moment correlation coefficient and absolute and relative differences in power output between the ergometer and track cyclist were determined Purpose: The objective of this study was to determine if exercise mode played a part in the acute immune responses to exercise. Results : Power fit trend lines were found to resemble the best fit for the power-velocity curve for both the SRM Ergometer as well as in the real world situation (see Figure 1). This indicates that the SRM Ergometer uses a non- linear instead of a linear breaking algorithm, related to the velocity of the flywheel. The correlation for the predicted power output at fixed speeds was perfect (r=1.000) between the SRM ergometer and both cycling position on the track, with a standard error of the estimate of 1.64 and 2.96 respectively for standard and aero position. At high velocities, the SRM Ergometer required a similar power output as standard cycling but a higher power output than required in track cycling in aero position at the same velocity (see Table 1). Conclusion : The non-linear power-velocity curve of the SRM Ergometer that closely resembles the power-velocity curve of track cycling indicates that it mimics real life cycling behaviour and that it therefore could be used to simulate free ride efforts like time trials and constant duration tests to determine mean maximal power output. However, one must be cautious to use the velocity measured by the ergometer to predict field performance, as at the same power output the speed on the track is higher in aero position.

How 100-m event analyses improve our understanding of world-class men's and women's sprint performance.

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 (Pmax , F0 , and V0 ). The results showed that the maximal sprint velocity (Vmax ) and mean power output (W/kg) developed over the entire 100m 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 100m, 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 Vmax and their greater decrease in velocity, and in turn their lower performance level, which can be explained by their higher V0 and its correlation with performance. This highlights the importance of the capability to keep applying horizontal force to the ground at high velocities.

Impact of Altitude on Power Output during Cycling Stage Racing.

PurposeThe purpose of this study was to quantify the effects of moderate-high altitude on power output, cadence, speed and heart rate during a multi-day cycling tour.MethodsPower output, heart rate, speed and cadence were collected from elite male road cyclists during maximal efforts of 5, 15, 30, 60, 240 and 600 s. The efforts were completed in a laboratory power-profile assessment, and spontaneously during a cycling race simulation near sea-level and an international cycling race at moderate-high altitude. Matched data from the laboratory power-profile and the highest maximal mean power output (MMP) and corresponding speed and heart rate recorded during the cycling race simulation and cycling race at moderate-high altitude were compared using paired t-tests. Additionally, all MMP and corresponding speeds and heart rates were binned per 1000m (<1000m, 1000–2000, 2000–3000 and >3000m) according to the average altitude of each ride. Mixed linear modelling was used to compare cycling performance data from each altitude bin.ResultsPower output was similar between the laboratory power-profile and the race simulation, however MMPs for 5–600 s and 15, 60, 240 and 600 s were lower (p ≤ 0.005) during the race at altitude compared with the laboratory power-profile and race simulation, respectively. Furthermore, peak power output and all MMPs were lower (≥ 11.7%, p ≤ 0.001) while racing >3000 m compared with rides completed near sea-level. However, speed associated with MMP 60 and 240 s was greater (p < 0.001) during racing at moderate-high altitude compared with the race simulation near sea-level.ConclusionA reduction in oxygen availability as altitude increases leads to attenuation of cycling power output during competition. Decrement in cycling power output at altitude does not seem to affect speed which tended to be greater at higher altitudes.

Laboratory and Field-Based Evaluation of Short-Term Effort with Maximal Intensity in Individuals with Intellectual Disabilities.

Results of previous studies have not indicated clearly which tests should be used to assess short-term efforts of people with intellectual disabilities. Thus, the aim of the present study was to evaluate laboratory and field-based tests of short-term effort with maximal intensity of subjects with intellectual disabilities. Twenty four people with intellectual disability, who trained soccer, participated in this study. The 30 s Wingate test and additionally an 8 s test with maximum intensity were performed on a bicycle ergometer. The fatigue index, maximal and mean power, relative maximal and relative mean power were measured. Overall, nine field-based tests were conducted: 5, 10 and 20 m sprints, a 20 m shuttle run, a seated medicine ball throw, a bent arm hang test, a standing broad jump, sit-ups and a hand grip test. The reliability of the 30 s and 8 s Wingate tests for subjects with intellectual disability was confirmed. Significant correlation was observed for mean power between the 30 s and 8 s tests on the bicycle ergometer at a moderate level (r >0.4). Moreover, significant correlations were indicated between the results of laboratory tests and field tests, such as the 20 m sprint, the 20 m shuttle run, the standing long jump and the medicine ball throw. The strongest correlation was in the medicine ball throw. The 30 s Wingate test is a reliable test assessing maximal effort in subjects with intellectual disability. The results of this research confirmed that the 8 s test on a bicycle ergometer had a moderate correlation with the 30 s Wingate test in this population, thus, this comparison needs further investigation to examine alternativeness of the 8 s to 30 s Wingate tests. The non-laboratory tests could be used to indirectly assess performance in short-term efforts with maximal intensity.

Effect Of L-citrulline On Muscle Recovery After Anaerobic And Aerobic Exercise

PURPOSE: Previous research shows that acute L-citrulline (CT) supplementation improves anaerobic performance and reduces muscle soreness, suggesting it may improve muscle recovery following exercise. With a double blind crossover design, we evaluated the acute effect of CT supplementation on muscle recovery and cycling sprint and 2 mi time trial (TT) performance. METHODS: 22 college students (19.5 ± 1.3 y) completed a preliminary cycling VO2 max test (43.2 ± 10.8 ml/kg/min) and were then twice familiarized with the sprint test (4x12 s sprints at 5.5% of body mass, separated by 2.5 min of active recovery) and the TT; 48 h separated testing sessions. Approximately 5 d later and 1 hr before repeating the tests, 11 subjects consumed 6 g of CT, while the other 11 ingested 6 g of a cornstarch placebo (PT); to assess recovery, the tests were repeated 24 hr later. After a 1 wk washout, subjects repeated the tests with the other treatment. Data were analyzed with two-way repeated measures ANOVA; Bonferroni post-hoc analyses located specific differences. RESULTS: Table 1 shows mean power in watts (W) for maximum peak power (MPP), average peak power (APP), maximum mean power (MMP), and average mean power (AMP) for the sprint tests, and mean time in seconds and power (W) for the TT. CONCLUSION: Citrulline decreased aerobic performance, reducing TT power and increasing TT time relative to PT; CT did not affect anaerobic performance or muscle recovery. In contrast, 6 g or 24 kcal of cornstarch ingested 1 h before exercise improved sprint performance 24 h after a bout of similar exercise.Table: No title available.

Evaluation of a six-week whole-body vibration intervention on neuromuscular performance in older adults.

Research in the field of whole-body vibration (WBV) for the enhancement of neuromuscular performance is becoming increasingly popular. However, additional understanding of optimal WBV training protocols is still necessary to develop optimal and effective training and prevention concepts, especially for elderly people. The intention of this study was to evaluate a 6-week WBV intervention program based on optimal vibration loads adapted from the literature on lower-limb strength parameters and performance, as well as on perceived exertion according to a subjective rating. A total of 21 older adults were allocated randomly into either a WBV training or control group (CO). Before and after the intervention period, jump height was measured during a countermovement jump. In addition, isolated isokinetic maximal knee extension and flexion strength, mean power, and work were recorded using a motor-driven dynamometer. Borg's scale for rating of perceived exertion was used to evaluate the intensity of WBV exercises within each training session. After the intervention period, jump height increased by 18.55% (p < 0.001) in the WBV group, whereas values of the CO remained unchanged. There were no statistically significant differences in isokinetic maximal strength, mean power, or work values in knee extension or flexion (all p > 0.05). Finally, the subjective perceived exertion of the WBV exercises and respective training parameters ranged between moderate rating levels of 7 and 13 of Borg's scale. Our data show that WBV is a feasible and safe training program for elderly people to increase multijoint strength performance of the lower limbs during a countermovement jump. This could help to determine the potential of WBV programs in training of the elderly to prevent age-related reduction of neuromuscular performance.

Ultrasound imaging algorithm based on generalized sidelobe canceller

The traditional delay and sum (DAS) algorithm is the most widely adopted method in medical ultrasound imaging; although it can produce images quickly, it sacrifices the resolution and the contrast ratio. The adaptive method such as the minimum variance (MV) continuously updates the apodization weighting vectors according to the received signals, so that the variance of the weighted signals is minimized, and thus the quality of the ultrasound imaging can be improved, especially its resolution. Although the image quality may be improved in the contrast ratio as well as the resolution after combining the minimum variance with the coherence factor (MV-CF), it complicates the algorithm, and the robustness against noise is enhanced but a little. An improved ultrasound imaging algorithm based on the generalized side lobe canceller (GSC) is proposed, which is constructed according to the minimum variance principle. The canceller is designed to classify the signal into desired and noise signals, combined with wiping off the big interferential eigenvectors, so that the robustness against noise can be enhanced. Firstly, the canceller divides the weighting vector into non-adaptive and adaptive weights, then the eigenstructure subspace is established according to the covariance matrix of the received signals, and the renewed weighting vector is achieved finally by projecting the weighting vector into the left singular space of the eigenstructure subspace. Simulations of the point targets and the cyst phantom through the simulation tool Field II demonstrate that the ultrasound image acquired through the proposed method is better than the traditional DAS and MV-CF algorithms in terms of the contrast ratio and resolution. In practice, the contrast ratio increases by roughly 7 dB compared to DAS and 5 dB to MV-CF. Furthermore, the proposed method gives a more satisfactory lateral resolution as well as the lowest side lobe peak level. From the sound-absorbing speckle simulation, the contrast ratio increases by 3 dB more than that of DAS and over 4 dB than that of MV-CF when noise exists. In addition, MV-CF performs the worst in the robustness aspect while the proposed GSC method makes improvement on the basis of it. Besides, the image quality can be further improved by combining the proposed method with sign coherence factor (GSC-SCF). After such a combination, the noise added to the data sets is almost invisible in point targets simulation. It also possesses the maximum mean power in cyst region in sound-absorbing speckle simulation. Finally, an experiment is conducted on the basis of the complete data sets which are offered by the University of Michigan. Results indicate that the proposed methods can perform better than the conventional DAS and MV-CF in resolution, contrast ratio and the robustness against noise.

Características espaço-temporais de corridas com obstáculo e testes ergométricos durante a preparação no atletismo

The main goal of this study was to assess the appropriateness of both ergometric and modified hurdles tests for an annual cycle of hurdlers who were working on mastering the 400 m distance. Nine Polish hurdlers (personal best: 54.46±2.16 s, age: 20.67±1.87 years) were chosen as the research participants. In each of two mastering periods in the research, an ergometric test and a specific test were implemented during a hurdle run. In February, an interval ergometric test (5×6 s) and an interval hurdle test (IHT) were performed. Additionally, in May, a classic Wingate test and a 200 m hurdle run were introduced. With regard to the ergometric tests, we assessed the following measurements: maximum power (Pmax) and mean power (P×) reached in five repetitions as well as total work (Wtotal) performed in five attempts. The Mann-Whitney test was used to distinguish between the athletic test results obtained in the preparation period outlined above and those obtained in the first period. Lactate (LA) concentrations were assessed with the Chi-square test. Moreover, Spearman's rank correlation coefficients were used in the analysis. The achieved study results indicate the lack of significant differentiation of the ergometric test parameters (p≥ 0.05). The spatial structure of both specific tests (5×2 H v. 200 m H) was similar given that the first and the second parts of both hurdle races and the number of steps taken were similar. The basic parameters of the ergometric tests did not exhibit any relationship with the recommended record time achieved for the 400 m hurdle run.

Measures of training stress in cyclists do not usefully predict maximum mean power in competitions

Background: Many competitive cyclists use mobile ergometers to monitor power output during training and competition rides. A training-impulse model is then often used to combine a training-stress score from each ride into measures of fitness and fatigue, the difference in which is interpreted as a measure of that might predict competitive performance. Purpose: To determine the effect of fitness, fatigue and freshness the day before cycling competitions on physiological indicators of performance in the competitions. Methods: Twenty male and four female competitive cyclists (29 ± 9 y, 71 ± 7 kg, mean ± SD) provided recordings of their SRM or Quarq mobile ergometers for training rides, 55 time trials (16-40 km), and 447 mass-start road races over a 6- to 8-month period. TrainingPeaks software (version WKO+ 3) was used to synthesize fitness, fatigue and freshness scores on the day before each competition and to extract maximal mean power (MMP) for four durations (5 s, 60 s, 5 min, 20 min) from the competition ride. The within-cyclist relationship between each measure of training and each measure of performance was investigated by producing scatterplots of the deviations from each rider's mean training and mean performance measure for time trials and road races in single-day and multi-day competitions. Mixed modeling was used to quantify the relationship as the linear effect of a change of two within-cyclist standard deviations of the measure of training, assuming a smallest important change in performance of 1%. Results:Individual typical variation in maximum mean power from competition to competition ranged from ±7.1% (5-min MMP) to ±14% (5-s MMP). Scatterplots were generally consistent with a random relationship between the indicators of performance in competitions and the measures of training the previous day, and all effects of training measures on performance measures were unclear. Discussion: The uncertainty in the relationships between the measures of training and the measures of performance is due to the extremely poor reliability of the measures of maximum mean power. Contextual information about each competition ride might improve the reliability by helping to filter out or otherwise account for poorer performances. Alternatively other measures of performance from competitions are needed to determine whether fitness, fatigue and freshness usefully predict competition performance. Conclusions: Maximum mean power in competitions is too unreliable to determine whether the measures of fitness, fatigue and freshness provided by mobile ergometers and TrainingPeaks software reflect readiness for competitions.

Power and Impulse Applied During Push Press Exercise

The aim of this study was to quantify the load, which maximized peak and mean power, and impulse applied to these loads, during the push press and to compare them to equivalent jump squat data. Resistance-trained men performed 2 push press (n = 17; age: 25.4 ± 7.4 years; height: 183.4 ± 5 cm; body mass: 87 ± 15.6 kg) and jump squat (n = 8 of original 17; age: 28.7 ± 8.1 years; height: 184.3 ± 5.5 cm; mass: 98 ± 5.3 kg) singles with 10-90% of their push press and back squat 1 repetition maximum (1RM), respectively, in 10% 1RM increments while standing on a force platform. Push press peak and mean power was maximized with 75.3 ± 16.4 and 64.7 ± 20% 1RM, respectively, and impulses applied to these loads were 243 ± 29 N·s and 231 ± 36 N·s. Increasing and decreasing load, from the load that maximized peak and mean power, by 10 and 20% 1RM reduced peak and mean power by 6-15% (p ≤ 0.05). Push press and jump squat maximum peak power (7%, p = 0.08) and the impulse that was applied to the load that maximized peak (8%, p = 0.17) and mean (13%, p = 0.91) power were not significantly different, but push press maximum mean power was significantly greater than the jump squat equivalent (∼9.5%, p = 0.03). The mechanical demand of the push press is comparable with the jump squat and could provide a time-efficient combination of lower-body power and upper-body and trunk strength training.

The effects of different strength training regimes on cycling performance

Background: There is conflicting literature on the effect of strength training on road cycling performance, with the most recent literature showing a positive effect with maximal strength training (RA¸nnestad & Mujika, 2013: Scan J Med Sci Sports, Aug 5. doi: 10.1111/sms.12104). Most of these studies are flawed in that they compare strength training added to an endurance program with only endurance training, while many elite cyclists already use some sort of strength training in their program, mainly sub maximal or explosive resistance training. Purpose: To determine if maximal strength training is superior to sub maximal strength training, we compared the effects of maximal and sub maximal strength training programs on cycling performance in young elite cyclists, while keeping the number of strength training sessions equal. Methods: The programs consisted of maximal (front squats, squat jumps, 1 arm dumbbell press, box steps, Romanian deadlifts (week 1-4) and squat (90o), box jumps, 1 arm dumbbell pull, one legged squat and deadlift from knee height (week 6-9), 3-5 sets of 3-6 RM) or sub maximal strength training (half squat, squat jumps, 1 arm dumbbell press, leg press (1 leg), Romanian deadlift (week 1-4) and half squat, hip flexion, bent over row, box steps and calf lifting (week 6-9), 3 sets of 8-12 repetitions). Strength training was performed twice a week and was concurrent to cycling endurance training, which was kept similar for both groups, though individualized. Seventeen male cyclists were assessed for mean maximal power output over 5, 15, 30, 60, 240 and 600 s (Quad et al., 2010: Int J Sports Med, 31(6), 397-401) 3-7 days before and after the first and last strength training. Precision of the estimate was used to determine probabilities of practical significance. Results: Between-group differences for all cycling tests were found unclear, except at 15 s mean maximal power (4.2%; ±3.5% likely) and at 30 s mean maximal power (7.6%; ±5.6% very likely), where the maximal strength group performed worse (Table 1). Discussion: Maximal strength training was not superior over sub maximal strength training in these elite cyclists. A possible explanation for the discrepancy with recent studies is that the participants in our study were already used to strength training, while in these recent studies the participants had no experience with strength training and the strength training was added to their cycling training, increasing the amount of training time for the experimental groups (e.g. RA¸nnestad et al., 2010: Eur J Appl Physiol, 110(6), 1269-1282). Coming from relative rest, the increase in endurance performance in both groups show that both training programs are effective, although the maximal training group decreased their 15 s and 30 s mean maximal power output, possibly due to detraining of the anaerobic glycolytic pathways, while the sub max group did maintain these pathways through the multiple efforts with short recovery. Conclusion: No difference was found in increase in endurance performance in elite cyclists using maximal or sub maximal strength training, suggesting that sub maximal strength training is sufficient and effective for road cycling performance.

Application to cycling of a bioenergetic model: Towards a multi-level biomechanical model for global cyclist performance analysis

Application to cycling of a bioenergetic model: Towards a multi-level biomechanical model for global cyclist performance analysis