The Critical Power Function is Dependent on the Duration of the Predictive Exercise Tests Chosen

The linear relationship between work accomplished (W_lim) and time to exhaustion (t_lim) can be described by the equation: W_lim = a + CP · t_lim. Critical power (CP) is the slope of this line and is thought to represent a maximum rate of ATP synthesis without exhaustion, presumably an inherent characteristic of the aerobic energy system. The present investigation determined whether the choice of predictive tests would elicit significant differences in the estimated CP. Ten female physical education students completed, in random order and on consecutive days, five all-out predictive tests at preselected constant-power outputs. Predictive tests were performed on an electrically-braked cycle ergometer and power loadings were individually chosen so as to induce fatigue within approximately 1 -10 mins. CP was derived by fitting the linear Wlim - tlim regression and calculated three ways: 1) using the first, third and fifth W_lim - t_lim coordinates (l₁₃₅, 2) using coordinates from the three highest power outputs (l₁₂₃; mean tlim = 68 -193 s) and 3) using coordinates from the lowest power outputs (l₃₄₅; mean t_lim = 193 - 485 s). Repeated measures ANOVA revealed that CPI₁₂₃ (201.0 ± 37.9 W) > CPI₁₃₅ (176.1 ± 27.6 W) > CPI₃₄₅ (164.0 ± 22.8 W) (P < 0.05). When the three sets of data were used to fit the hyperbolic Power -tlim regression, statistically significant differences between each CP were also found (P < 0.05). The shorter the predictive trials, the greater the slope of the W_lim - t_lim regression; possibly because of the greater influence of 'aerobic inertia' on these trials. This may explain why CP has failed to represent a maximal, sustainable work rate. The present findings suggest that if CP is to represent the highest power output that an individual can maintain „for a very long time without fatigue” then CP should be calculated over a range of predictive tests in which the influence of aerobic inertia is minimised.

Key words

Anaerobic work capacity - females - mathematical modelling - methodology