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The mathematical modeling of lactate curves from graded incremental exercise tests

##article.authors##

  • Simon Nolte Institute of Movement and Neurosciences, German Sport University Cologne https://orcid.org/0000-0003-1643-1860
  • Oliver Jan Quittmann Institute of Movement and Neurosciences, German Sport University Cologne, Cologne, Germany
  • Volker Meden Institut für Theorie der Statistischen Physik, RWTH Aachen University, Aachen, Germany

DOI:

https://doi.org/10.51224/SRXIV.136

Keywords:

lactate testing, anaerobic threshold, endurance performance, performance diagnostics, cycling

Abstract

Purpose: Measuring the blood lactate concentration allows for a glimpse at the metabolic processes during exercise. To extract characteristics of metabolism the relationship between blood lactate concentration and power or velocity is modeled. Current modeling approaches allow only limited interpretation, are in conflict with basic principles of scientific mathematical modeling, and lack a phenomenological reasoning.

Methods: We developed a simple analytical expression to model lactate concentration data from graded incremental exercise tests. We compared our new approach to a traditional one in a dataset of N = 24 exercise tests performed by elite junior triathletes.

Results: The new procedure leads to three independent fitting parameters characterizing the baseline lactate concentration, the intensity (power, velocity) at the onset as well as the rate of increase of the lactate concentration. These parameters have a clear meaning and can directly be used for diagnostics. They can be interpreted with more confidence compared to the characteristics extracted in the traditional approach.

Conclusion: The performance indicators, naturally appearing in our modeling, should supersede the single points obtained from the traditional evaluation of graded incremental exercise tests (“lactate thresholds”), which can hardly be justified based on the principles of scientific mathematical modeling.

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Posted

2022-03-21