German Sport University Cologne, Am Sportpark Müngersdorf 6, 50933, Cologne, Germany.
Eur J Appl Physiol. 2021 May;121(5):1349-1357. doi: 10.1007/s00421-021-04611-w. Epub 2021 Feb 18.
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.
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): 48 ± 1.1 ml·min·kg), 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. Heart rate (HR), stroke volume (SV) and gas exchange (pulmonary oxygen uptake ([Formula: see text]O)) were measured beat-to-beat and breath-by-breath, respectively. For estimation of muscle oxygen uptake ([Formula: see text]O) kinetics and for the analysis of kinetic responses of the parameters of interest (perfusion ([Formula: see text] = HR·SV), [Formula: see text]O, [Formula: see text]O) the approach of Hoffmann et al. (2013) was applied. For calculation of the Fuzzy Kinetics Index [Formula: see text], [Formula: see text]O, and [Formula: see text]O were used as input variables for the subsequent fuzzy- and defuzzyfication procedures.
For both absolute and relative [Formula: see text]O 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 (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).
The significant correlations between FKI and [Formula: see text]O 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.
本研究的目的是开发一种新的指数,使用模糊逻辑程序融合心肺和肺动力学在动态运动期间作为运动耐量的代表指标。
重新分析了总共 69 组数据:(年龄:29±1.2 岁[平均值±标准误差],身高:179±1.0cm;体重:78±1.4kg;峰值摄氧量([Formula: see text]̇O):48±1.1ml·min·kg),包括在自行车测力计上进行伪随机二进制序列工作率(WR)变化 30 至 80W,以及额外的自愿衰竭以估计[Formula: see text]O。心率(HR)、每搏量(SV)和气体交换(肺摄氧量[Formula: see text]O)分别逐搏和逐呼吸进行测量。为了估计肌肉摄氧量[Formula: see text]O 动力学,并分析感兴趣参数的动力学响应(灌注[Formula: see text]
= HR·SV)、[Formula: see text]O、[Formula: see text]O),应用了 Hoffmann 等人的方法(2013 年)。为了计算模糊动力学指数[Formula: see text],[Formula: see text]O 和[Formula: see text]O 被用作后续模糊和反模糊化过程的输入变量。
对于绝对和相对[Formula: see text]O,都观察到与 FKI 有显著相关性,而相对(r=0.430;p<0.001;n=69)的相关系数高于绝对[Formula: see text]O(r=0.358;p<0.01;n=69)。FKI 与年龄、身高或体重之间没有发现显著相关性(p>0.05 各)。
FKI 与[Formula: see text]O 之间的显著相关性代表了调节系统和电容系统及其运动表现之间的生理联系。反过来,FKI 的应用可以作为健康参与者评估运动耐力和运动表现的指标。