Abstract
PURPOSE: The aim of the present study was to develop a novel index using fuzzy logic procedures conflating cardiorespiratory and pulmonary kinetics during dynamic exercise as a representative indicator for exercise tolerance. METHODS: Overall 69 data sets were re-analyzed: (age: 29 ± 1.2 y [mean ± SEM], height: 179 ± 1.0 cm; body mass: 78 ± 1.4 kg; peak oxygen uptake ([Formula: see text]̇O(2peak)): 48 ± 1.1 ml·min(-1)·kg(-1)), that comprised pseudo random binary sequence work rate (WR) changes between 30 and 80 W on a cycle ergometer, with additional voluntary exhaustion to estimate [Formula: see text]O(2peak). Heart rate (HR), stroke volume (SV) and gas exchange (pulmonary oxygen uptake ([Formula: see text]O(2pulm))) were measured beat-to-beat and breath-by-breath, respectively. For estimation of muscle oxygen uptake ([Formula: see text]O(2musc)) kinetics and for the analysis of kinetic responses of the parameters of interest (perfusion ([Formula: see text] = HR·SV), [Formula: see text]O(2pulm), [Formula: see text]O(2musc)) the approach of Hoffmann et al. (2013) was applied. For calculation of the Fuzzy Kinetics Index [Formula: see text], [Formula: see text]O(2pulm), and [Formula: see text]O(2musc) were used as input variables for the subsequent fuzzy- and defuzzyfication procedures. RESULTS: For both absolute and relative [Formula: see text]O(2peak) a significant correlation has been observed with FKI, whereas the correlation coefficient is higher for relative (r = 0.430; p < 0.001; n = 69) compared to absolute [Formula: see text]O(2peak) (r = 0.358; p < 0.01; n = 69). No significant correlations have been found between FKI and age, height or body mass (p > 0.05 each). CONCLUSIONS: The significant correlations between FKI and [Formula: see text]O(2peak) represent a physiological connection between the regulatory and the capacitive system and its exercise performance. In turn, the application of FKI can serve as an indicator for healthy participants to assess exercise tolerance and sport performance.