Department of Movement and Sports Sciences, Ghent University, Ghent, BELGIUM.
Med Sci Sports Exerc. 2024 Sep 1;56(9):1770-1781. doi: 10.1249/MSS.0000000000003468. Epub 2024 May 15.
The aim of this study was to characterize W' recovery kinetics in response to a partial W' depletion. We hypothesized that W' recovery following a partial depletion would be better described by a biexponential than by a monoexponential model.
Nine healthy men performed a ramp incremental exercise test, three to five constant load trials to determine critical power and W', and 10 experimental trials to quantify W' depletion. Each experimental trial consisted of two constant load work bouts (WB1 and WB2) interspersed by a recovery interval. WB1 was designed to evoke a 25% or 75% W' depletion (DEP 25% and DEP 75% ). Subsequently, participants recovered for 30, 60, 120, 300, or 600 s and then performed WB2 to exhaustion to calculate the observed W' recovery (W' OBS ). W' OBS data were fitted using monoexponential and biexponential models, both with a variable and with a fixed model amplitude. Root mean square error and Akaike information criterion (AIC c ) were calculated to evaluate the models' goodness-of-fit.
The biexponential model fits were associated with overall lower root mean square error values (0.4% to 5.0%) when compared with the monoexponential models (2.9% to 8.0%). However, ΔAIC c resulted in negative values (-15.5 and -23.3) for the model fits where the amplitude was kept free, thereby favoring the use of a monoexponential model for both depletion conditions. For the model fits where the amplitude was fixed at 100%, ΔAIC c was negative for DEP 25% (-15.0) but positive for DEP 75% (11.2). W' OBS values were strongly correlated between both depletion conditions ( r = 0.92) and positively associated with V̇O 2peak , critical power, and gas exchange threshold ( r = 0.67 to 0.77).
The present study results did not provide evidence in favor of a biexponential modeling technique to characterize W' recovery following a partial depletion. Moreover, we demonstrated that fixed time constants were insufficient to model W' recovery across different depletion levels, and that W' recovery was positively associated with aerobic fitness. These findings underline the importance of employing variable and individualized time constants in future predictive W' models.
本研究旨在描述 W' 在部分 W' 耗竭后的恢复动力学。我们假设,部分耗竭后 W' 的恢复可以用双指数模型更好地描述,而不是用单指数模型。
9 名健康男性进行了递增斜坡式运动试验,3 至 5 次恒定负荷试验以确定临界功率和 W',以及 10 次实验性试验以量化 W' 耗竭。每个实验性试验由两个恒定负荷工作阶段(WB1 和 WB2)组成,中间间隔恢复间隔。WB1 的设计目的是引起 25%或 75%的 W' 耗竭(DEP 25%和 DEP 75%)。随后,参与者恢复 30、60、120、300 或 600 秒,然后进行 WB2 至力竭,以计算观察到的 W' 恢复(W' OBS)。使用单指数和双指数模型对 W' OBS 数据进行拟合,两个模型都具有可变和固定的模型幅度。均方根误差和赤池信息量准则(AIC c)用于评估模型的拟合优度。
与单指数模型相比(2.9%至 8.0%),双指数模型的拟合结果整体上具有更低的均方根误差值(0.4%至 5.0%)。然而,对于保持幅度自由的模型拟合,ΔAIC c 产生负值(-15.5 和-23.3),因此两种耗竭条件都更倾向于使用单指数模型。对于幅度固定为 100%的模型拟合,ΔAIC c 对于 DEP 25%为负值(-15.0),但对于 DEP 75%为正值(11.2)。两种耗竭条件下的 W' OBS 值均高度相关(r=0.92),与 V̇O 2peak、临界功率和气体交换阈值呈正相关(r=0.67 至 0.77)。
本研究结果并未提供支持双指数建模技术来描述部分耗竭后 W' 恢复的证据。此外,我们证明了固定时间常数不足以对不同耗竭水平下的 W' 恢复进行建模,并且 W' 恢复与有氧健身呈正相关。这些发现强调了在未来的预测性 W' 模型中使用可变和个体化时间常数的重要性。