Busso Thierry, Chalencon Sébastien
Laboratoire Interuniversitaire de Biologie de la Motricité, Université Jean Monnet Saint-Etienne, Lyon 1, Université Savoie Mont-Blanc, EA 7424, F-42023, Saint-Etienne, France.
Club Des Dauphins de Guilherand-Granges, 07500, Guilherand-Granges, France.
Eur J Appl Physiol. 2025 May;125(5):1437-1448. doi: 10.1007/s00421-024-05692-z. Epub 2024 Dec 22.
This study aimed to investigate whether the variable dose-response model, with estimates free to vary over time, can account for overreaching during intensified training in swimmers.
A time-varying model using a recursive least squares algorithm was applied to data from eight swimmers collected over 61 weeks, comprising five training cycles. Each data set included daily training load calculated from pool kilometers and dry land training equivalents, and performance measured twice weekly from 50 m trials. Weekly changes in model parameters were used to calculate the model impulse response that is defined as the time course of performance after a single training session.
Functional overreaching was evidenced by a significant decline in performance within four cycles of increased training, followed by a peak in performance after two or three weeks of reduced training. Model estimates from the time-varying model provided markers to distinguish overreaching from acute fatigue during intensified training. When an increase in training led to a decrease in performance, the characteristics of the modelled impulse responses showed a significant increase in the acute negative effect and a decrease in the delayed positive effect of a single workout.
Weekly variations in estimates from a time-varying model could be useful in diagnosing overreaching from changes in the acute negative effect and delayed positive effect of training. This information provided by the model at a particular point in the training process could help practitioners to re-adjust subsequent training.
本研究旨在调查可变剂量反应模型(其估计值可随时间变化)是否能解释游泳运动员强化训练期间的过度训练现象。
使用递归最小二乘算法的时变模型应用于八名游泳运动员在61周内收集的数据,包括五个训练周期。每个数据集包括根据泳池公里数和旱地训练当量计算出的每日训练负荷,以及每周两次从50米测试中测得的成绩。模型参数的每周变化用于计算模型脉冲响应,该响应定义为单次训练课后成绩的时间进程。
功能性过度训练的证据是,在增加训练的四个周期内成绩显著下降,随后在减少训练两到三周后成绩达到峰值。时变模型的估计值提供了在强化训练期间区分过度训练和急性疲劳的指标。当训练增加导致成绩下降时,模拟脉冲响应的特征显示单次训练的急性负面影响显著增加,延迟正面影响下降。
时变模型估计值的每周变化可能有助于从训练的急性负面影响和延迟正面影响的变化中诊断过度训练。该模型在训练过程的特定点提供的这些信息可以帮助从业者重新调整后续训练。