The effect of mathematical modeling on critical velocity

The purpose of this investigation was to examine the effects of mathematica l modeling on critical velocity (CV) estimates and the oxygen consumption ( VO2), heart rate (HR), and plasma lactate values that corresponded to the f ive CV estimates. Ten male subjects performed a maximal, incremental treadm ill test to determine maximal VO2, and four randomly ordered treadmill runs for the estimation of CV. Two linear, two nonlinear, and one exponential m athematical models were used to estimate CV. Regression analyses were used to determine the VO2, HR, and plasma lactate values that corresponded to th e five CV estimates from the relationships for VO2, HR, and plasma lactate versus running velocity from the maximal, incremental test. The nonlinear, three-component model (Nonlinear-3) resulted in a mean CV that was signific antly (P < 0.05) less than the mean values derived from the other four mode ls, and was the lowest CV estimate for each subject. The percent of maximal VO2, HR, and plasma lactate values that corresponded to the Nonlinear-3 mo del were 89%, 93%, and 63%, respectively. These findings indicate that CV e stimates differ by as much as 20% depending upon the model used to determin e the characteristics of the velocity/time relationship. Future studies are needed to determine which model provides the most valid estimate of the de marcation point between heavy and severe exercise.