Megan E. Anderson

Enhancement of 2000-m rowing performance after caffeine ingestion.

PURPOSE To investigate the effect of caffeine ingestion on short-term endurance performance in competitive rowers. METHODS In this randomized double-blind crossover study, eight competitive oarsmen (peak oxygen uptake [VO2peak] 4.7+/-0.4 L x min(-1), mean +/- SD) performed three familiarization trials of a 2000-m rowing test on an air-braked ergometer, followed by three experimental trials at 3- to 7-d intervals, each 1 h after ingesting caffeine (6 or 9 mg x kg(-1) body mass) or placebo. Trials were preceded by a standardized warm-up (6 min at 225+/-39 W; 75+/-7.7% VO2peak). RESULTS Urinary caffeine concentration was similar before ingestion (approximately 1 mg x L(-1)) but rose to 6.2+/-3.6 and 14.5+/-7.0 mg x L(-1) for the low and high caffeine doses, respectively. Plasma free fatty acid concentration before exercise was higher after caffeine ingestion (0.29+/-0.17 and 0.39+/-0.20 mM for 6 and 9 mg x kg(-1), respectively) than after placebo (0.13+/-0.05 mM). Respiratory exchange ratio during the warm-up was also substantially lower with caffeine (0.94+/-0.09 and 0.93+/-0.06 for the low and high dose) than with placebo (0.98+/-0.12). Subjects could not distinguish between treatments before or after the exercise test. Both doses of caffeine had a similar ergogenic effect relative to placebo: performance time decreased by a mean of 1.2% (95% likely range 0.4-1.9%); the corresponding increase in mean power was 2.7% (0.4-5.0%). Performance time showed some evidence of individual differences in the effect of caffeine (SD 0.9%; 95% likely range 1.5 to -0.9%). CONCLUSIONS Ingestion of 6 or 9 mg x kg(-1) of caffeine produces a worthwhile enhancement of short-term endurance performance in a controlled laboratory setting.

Ability of test measures to predict competitive performance in elite swimmers

Abstract The purpose of this study was to quantify the relationship between changes in test measures and changes in competition performance for individual elite swimmers. The 24 male and 16 female swimmers, who were monitored for 3.6 years (s = 2.5), raced in a major competition at the end of each 6-month season (3.6 competitions, s = 2.2). A 7×200-m incremental swimming step-test and anthropometry were conducted in up to four training phases each season. Correlations of changes in step-test and anthropometry measures between training phases and seasons with changes in competition performance between seasons were derived with repeated-measures mixed-modelling and linear regression. Changes in competition performance were best tracked by changes in test measures between taper phases. The best single predictor of competition performance was skinfolds for females (r = −0.53). The best predictor from the step-test was stroke rate at a blood lactate concentration of 4 mmol · l−1 (females: r = 0.46; males: r = 0.41); inclusion of the second-best step-test predictor in a multiple linear regression improved the correlations (females: r = 0.52 with speed in the seventh step included; males: r = 0.58 with peak lactate concentration included). In conclusion, a combination of fitness and technique factors is important for competitive performance. The step-test is a useful adjunct in a swimmers training preparation for tracking large changes in performance.

Monitoring seasonal and long-term changes in test performance in elite swimmers

Abstract The purpose of this study was to characterize changes and variability in test performance of swimmers within and between seasons over their elite competitive career. Forty elite swimmers (24 male, 16 female) performed a 7×200-m incremental swimming step test several times each 6-month season (10±5 tests, spanning 0.5–6.0 y). Mixed linear modeling provided estimates of percent change in the mean and individual responses (within-athlete variation as a coefficient of variation) for measures based on submaximal performance (fixed 4-mM lactate), maximal performance (the seventh step) and lean mass (from skinfolds and body mass). Submaximal and maximal swim speed increased within each season from pre to taper phase by ∼2.2% for females and ∼1.5% for males (95% confidence limits ±1.0%), with variable contributions from stroke rate and stroke length. Most of the gains in speed were lost in the off-season, leaving a net average annual improvement of ∼1.0% for females and ∼0.6% for males (±1.0%). For submaximal and maximal speed, individual variation between phases was ±2.2% and the typical measurement error was ±0.80%. Step test and anthropometric measures can be used to confidently monitor progressions in swimmers in an elite training program within and between seasons.

Effect of 10 week beta-alanine supplementation on competition and training performance in elite swimmers.

Although some laboratory-based studies show an ergogenic effect with beta-alanine supplementation, there is a lack of field-based research in training and competition settings. Elite/Sub-elite swimmers (n = 23 males and 18 females, age = 21.7 ± 2.8 years; mean ± SD) were supplemented with either beta-alanine (4 weeks loading phase of 4.8 g/day and 3.2 g/day thereafter) or placebo for 10 weeks. Competition performance times were log-transformed, then evaluated before (National Championships) and after (international or national selection meet) supplementation. Swimmers also completed three standardized training sets at baseline, 4 and 10 weeks of supplementation. Capillary blood was analyzed for pH, bicarbonate and lactate concentration in both competition and training. There was an unclear effect (0.4%; ±0.8%, mean, ±90% confidence limits) of beta-alanine on competition performance compared to placebo with no meaningful changes in blood chemistry. While there was a transient improvement on training performance after 4 weeks with beta-alanine (−1.3%; ±1.0%), there was an unclear effect at ten weeks (−0.2%; ±1.5%) and no meaningful changes in blood chemistry. Beta-alanine supplementation appears to have minimal effect on swimming performance in non-laboratory controlled real-world training and competition settings.

An accelerometer-based system for elite athlete swimming performance analysis

The measurement of sport specific performance characteristics is an important part of an athletes training and preparation for competition. Thus automated measurement, extraction and analysis of performance measures is desired and addressed in this paper. A tri-axial accelerometer based system was located on the lower back or swimmers to record acceleration profiles. The accelerometer system contained two ADXL202 bi-axial accelerometers positioned perpendicular to one another, and can store over 6 hours of data at 150Hz per channel using internal flash memory. The simultaneous collection of video and electronics touch pad timing was used to validate the algorithm results. Using the tri-axial accelerometer data, algorithms have been developed to derive lap times and stroke count. Comparison against electronic touch pad timing against accelerometer lap times has produced results with a typical error of better than ±0.5 seconds. Video comparison of the stroke count algorithm for freestyle also produced results with an average error of ±1 stroke. The developed algorithms have a higher level of reliability compared to hand timed and counted date that is commonly used during training.

Signal analysis of accelerometry data using gravity based modelling

Triaxial accelerometers have been used to measure human movement parameters in swimming. Interpretation of data is difficult due to interference sources including interaction of external bodies. In this investigation the authors developed a model to simulate the physical movement of the lower back. Theoretical accelerometery outputs were derived thus giving an ideal, or noiseless dataset. An experimental data collection apparatus was developed by adapting a system to the aquatic environment for investigation of swimming. Model data was compared against recorded data and showed strong correlation. Comparison of recorded and modeled data can be used to identify changes in body movement, this is especially useful when cyclic patterns are present in the activity. Strong correlations between data sets allowed development of signal processing algorithms for swimming stroke analysis using first the pure noiseless data set which were then applied to performance data. Video analysis was also used to validate study results and has shown potential to provide acceptable results.