仿形(计算机编程)
运动医学
运动员
耐力训练
医学
物理医学与康复
物理疗法
计算机科学
操作系统
作者
Ed Maunder,Stephen Seiler,Mathew J. Mildenhall,Andrew E. Kilding,Daniel J. Plews
出处
期刊:Sports Medicine
[Springer Science+Business Media]
日期:2021-04-22
卷期号:51 (8): 1619-1628
被引量:120
标识
DOI:10.1007/s40279-021-01459-0
摘要
Profiling physiological attributes is an important role for applied exercise physiologists working with endurance athletes. These attributes are typically assessed in well-rested athletes. However, as has been demonstrated in the literature and supported by field data presented here, the attributes measured during routine physiological-profiling assessments are not static, but change over time during prolonged exercise. If not accounted for, shifts in these physiological attributes during prolonged exercise have implications for the accuracy of their use in intensity regulation during prolonged training sessions or competitions, quantifying training adaptations, training-load programming and monitoring, and the prediction of exercise performance. In this review, we argue that current models used in the routine physiological profiling of endurance athletes do not account for these shifts. Therefore, applied exercise physiologists working with endurance athletes would benefit from development of physiological-profiling models that account for shifts in physiological-profiling variables during prolonged exercise and quantify the 'durability' of individual athletes, here defined as the time of onset and magnitude of deterioration in physiological-profiling characteristics over time during prolonged exercise. We propose directions for future research and applied practice that may enable better understanding of athlete durability.
科研通智能强力驱动
Strongly Powered by AbleSci AI