Validity of dynamical analysis to characterize heart rate and oxygen consumption during effort tests

Abstract

Performance is usually assessed by simple indices stemming from cardiac and respiratory data measured during graded exercise test. The goal of this study is to test the interest of using a dynamical analysis of these data. Therefore, two groups of 32 and 14 athletes from two different cohorts performed two different graded exercise testing before and after a period of training or deconditioning. Heart rate (HR) and oxygen consumption (VO2) were measured. The new dynamical indices were the value without effort, the characteristic time and the amplitude (gain) of the HR and VO2 response to the effort. The gain of HR was moderately to strongly associated with other performance indices, while the gain for VO2 increased with training and decreased with deconditioning with an effect size slightly higher than VO2 max.Dynamical analysis performed on the first 2/3 of the effort tests showed similar patterns than the analysis of the entire effort tests, which could be useful to assess individuals who cannot perform full effort tests. In conclusion, the dynamical analysis of HR and VO2 obtained during effort test, especially through the estimation of the gain, provides a good characterization of physical performance, robust to less stringent effort test conditions.

Decrease of heart rate variability during exercise: an index of cardiorespiratory fitness

“…The similarity of these two representations during the effort resides in the linear relation that HR and VO 2 have when performing graded exercise tests (29). Their differences reside in the shorter dynamical time of VO 2 compared to HR, and is revealed at exercise onset and exercise cessation (24,30).…”

“…An estimated curve can then be produced by numerical integration of the differential equation with the obtained coefficients. This simple model produces indices sensitive to CRF and performance changes (24). The possibility to estimate the gain (the amplitude of the HR increase corresponding to a workload increase) for each power step of the exercise test allows to reproduces up to 99% of the HR dynamics during the GET, and yields coefficients varying consistently with the metabolic changes associated to the respiratory thresholds (25).…”

“…Each individual RR series was first detrended to obtain a stationary RR series. The detrending has been performed by a tested and characterized dynamical model based on simple physiological considerations [22][23][24] and free from ad-hoc parameters (see "detrending" subsection). HRV during each individual effort was then quantified by the standard deviation of the detrended RR intervals (SDRR) calculated on adjacent windows of one minute (corresponding to each effort step during effort, see "Heart rate variability" subsection).…”

“…An estimated curve can then be produced by numerical integration of the differential equation with the obtained coefficients. This simple model produces indices sensitive to CRF and performance changes (24). The possibility to estimate the gain (the amplitude of the HR increase corresponding to a workload increase)…”