A heuristic approach for lactate threshold estimation for training
  decision-making: An accessible and easy to use solution for recreational
  runners

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Abstract

In this work, a heuristic as operational tool to estimate the lactate threshold and to facilitate its integration into the training process of recreational runners is proposed. To do so, we formalize the principles for the lactate threshold estimation from empirical data and an iterative methodology that enables experience based learning. This strategy arises as a robust and adaptive approach to solve data analysis problems. We compare the results of the heuristic with the most commonly used protocol by making a first quantitative error analysis to show its reliability. Additionally, we provide a computational algorithm so that this quantitative analysis can be easily performed in other lactate threshold protocols. With this work, we have shown that a heuristic %60 of 'endurance running speed reserve', serves for the same purpose of the most commonly used protocol in recreational runners, but improving its operational limitations of accessibility and consistent use.

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Most cited references 8

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Peak treadmill running velocity during the VO2 max test predicts running performance.

K. H. Myburgh, T. D. Noakes, R Schall (1989)

Twenty specialist marathon runners and 23 specialist ultra-marathon runners underwent maximal exercise testing to determine the relative value of maximum oxygen consumption (VO2max), peak treadmill running velocity, running velocity at the lactate turnpoint, VO2 at 16 km h-1, % VO2max at 16 km h-1, and running time in other races, for predicting performance in races of 10-90 km. Race time at 10 or 21.1 km was the best predictor of performance at 42.2 km in specialist marathon runners and at 42.2 and 90 km in specialist ultra-marathon runners (r = 0.91-0.97). Peak treadmill running velocity was the best laboratory-measured predictor of performance (r = -0.88(-)-0.94) at all distances in ultra-marathon specialists and at all distances except 42.2 km in marathon specialists. Other predictive variables were running velocity at the lactate turnpoint (r = -0.80(-)-0.92); % VO2max at 16 km h-1 (r = 0.76-0.90) and VO2max (r = 0.55(-)-0.86). Peak blood lactate concentrations (r = 0.68-0.71) and VO2 at 16 km h-1 (r = 0.10-0.61) were less good predictors. These data indicate: (i) that in groups of trained long distance runners, the physiological factors that determine success in races of 10-90 km are the same; thus there may not be variables that predict success uniquely in either 10 km, marathon or ultra-marathon runners, and (ii) that peak treadmill running velocity is at least as good a predictor of running performance as is the lactate turnpoint. Factors that determine the peak treadmill running velocity are not known but are not likely to be related to maximum rates of muscle oxygen utilization.