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Assessments of maximal intensity exercise which determine peak power output on friction-baked cycle ergometers have fallen into two categories: correction procedures which account for changes in momentum of the ergometer's flywheel and optimization procedures which attempt to satisfy muscle force-velocity relationships. The aim of this study was to compare performance in each procedure and so investigate assumptions which underpin the tests. Nineteen males aged 20.9-0.4 years and 18 females aged 22.2-0.7 years (mean - S.E.M.), who were fully accustomed to the procedures, participated in a single experimental protocol. After a 5 min warm-up, the subjects performed four bouts of all-out exercise on a Monark 814E cycle ergometer against randomly assigned loads. The loads were selected to produce peak pedalling rates in the range 100-200 rev min[sup -1] and each bout lasted 10 s. From the inverse linear relationship between applied load and peak pedalling rate, optimized peak power output (PP[sub opt]) and the accompanying pedalling rate (RPM[sub opt]) were calculated. One of the bouts used a loading equivalent to 7.5% of body weight and for this bout corrected peak power output (PP[sub corr]) and its corresponding pedalling rate (RPM[sub corr])were calculated. The PP[sub opt] was less than PP [sub corr] in the males (915-35 vs 1005-32 W) and females (673-33 vs 777-39 W) (both P< 0.001).Similarly, RPM [sub opt] was less than RPM[sub corr] (111-1 vs 128-2 rev min[sup -1] and 101-1 vs 111-2 rev min[sup -1] in the males and females, respectively; P < 0.001). The results demonstrate that optimization and correction procedures produce different values of performance. These differences are probably attributable to the mechanical principles which underpin the tests. [ABSTRACT FROM AUTHOR]

The aims of this study were to determine if the primary time constant (tau) for oxygen uptake (VO2) at the onset of moderate-intensity treadmill exercise is related to endurance running performance, and to establish if tau could be considered a determinant of endurance running performance. Thirty-six endurance trained male runners performed a series of laboratory tests, on separate days, to determine maximal oxygen uptake (VO2max), the ventilatory threshold (VT) and running economy. In addition, runners completed six transitions from walking (4 km x h-1) to moderate-intensity running (80% VT) for the determination of the VO2 primary time constant and mean response time. During all tests, pulmonary gas-exchange was measured breath-by-breath. Endurance running performance was determined using a treadmill 5-km time-trial, after which runners were considered as combined performers (n=36) and, using a ranking system, high performers (n=10) and low performers (n=10). Relationships between tau and endurance running performance were quantified using correlation coefficients (r). Stepwise multiple regression was used to determine the primary predictor variables of endurance running performance in combined performers. Moderate correlations were observed between tau, mean response time and endurance running performance, but only for the combined performers (r=-0.55, P=0.001 and r=-0.50, P=0.002, respectively). The regression model for predicting 5-km performance did not include tau or mean response time. The velocity at VO2max was strongly correlated to endurance running performance in all groups (r=0.72 - 0.84, P < 0.01) and contributed substantially to the prediction of performance. In conclusion, the results suggest that despite their role in determining the oxygen deficit and having a moderate relationship with endurance running performance, neither tau nor mean response time is a primary determinant of endurance running performance.

Research into the physiology of exercise and kinanthropometry is intended to improve our understanding of how the body responds and adapts to exercise. If such studies are to be meaningful, they have to be well designed and analysed. Advances in personal computing have made available statistical analyses that were previously the preserve of elaborate mainframe systems and have increased opportunities for investigation. However, the ease with which analyses can be performed can mask underlying philosophical and epistemological shortcomings. The aim of this review is to examine the use of four techniques that are especially relevant to physiological studies: (1) bivariate correlation and linear and non-linear regression, (2) multiple regression, (3) repeated-measures analysis of variance and (4) multi-level modelling. The importance of adhering to underlying statistical assumptions is emphasized and ways to accommodate violations of these assumptions are identified.

The non-motorized treadmill system initially reported by Lakomy in 1984 has been used extensively to assess sprinting performance. However, there has been limited research into the reliability of power output measurement using such systems. The aim of this study was to design a system and protocol capable of measuring treadmill sprinting performance in rugby players and to assess the reliability of this system for measuring power output. Twenty-seven rugby players, all of whom were familiar with treadmill sprinting, performed three maximal 6 s sprints with 2 min recovery between sprints, on two occasions 1 week apart. Both tests were performed on a non-motorized Woodway tramp treadmill, interfaced to a data acquisition system. There were no significant differences (P > 0.05) between power output for repeated trials on the same day (between trials) or for repeated trials on different days (between days). Limits of agreement for maximum average power (the average of 100 readings per second) were 4+/-98 and 30+/-157 W for between trials and between days, respectively. When reported as ratio limits of agreement, these were 1.07 (*/divided 1.12) and 1.03 (*/divided 1.16), respectively. The limits of agreement for maximum instantaneous power (the highest of 100 readings per second) were 51+/-464 and 105+/-588 W for between trials and between days, respectively. When reported as ratio limits of agreement, these were 1.02 (*/divided 1.20) and 1.04 (*/divided 1.21) for between trials and between days, respectively. The coefficients of variation for all measures of power output were less than 9.3%. Hence, the treadmill system and protocol developed in this study provide a reliable measure of power output for rugby players.