Capostagno Benoit, Lambert Michael I, Lamberts Robert P
Int J Sports Physiol Perform. 2016 Sep;11(6):707-714. doi: 10.1123/ijspp.2016-0174. Epub 2016 Aug 24.
Finding the optimal balance between high training loads and recovery is a constant challenge for cyclists and their coaches. Monitoring improvements in performance and levels of fatigue is recommended to correctly adjust training to ensure optimal adaptation. However, many performance tests require a maximal or exhaustive effort, which reduces their real-world application. The purpose of this review was to investigate the development and use of submaximal cycling tests that can be used to predict and monitor cycling performance and training status. Twelve studies met the inclusion criteria, and 3 separate submaximal cycling tests were identified from within those 12. Submaximal variables including gross mechanical efficiency, oxygen uptake (VO), heart rate, lactate, predicted time to exhaustion (pTE), rating of perceived exertion (RPE), power output, and heart-rate recovery (HRR) were the components of the 3 tests. pTE, submaximal power output, RPE, and HRR appear to have the most value for monitoring improvements in performance and indicate a state of fatigue. This literature review shows that several submaximal cycle tests have been developed over the last decade with the aim to predict, monitor, and optimize cycling performance. To be able to conduct a submaximal test on a regular basis, the test needs to be short in duration and as noninvasive as possible. In addition, a test should capture multiple variables and use multivariate analyses to interpret the submaximal outcomes correctly and alter training prescription if needed.
对于自行车运动员及其教练而言,在高强度训练负荷与恢复之间找到最佳平衡始终是一项挑战。建议监测运动表现的提升和疲劳程度,以便正确调整训练,确保实现最佳适应效果。然而,许多运动表现测试需要运动员竭尽全力,这限制了它们在实际中的应用。本综述的目的是研究次最大强度自行车测试的发展及应用,这些测试可用于预测和监测自行车运动表现及训练状态。有12项研究符合纳入标准,从这12项研究中确定了3种不同的次最大强度自行车测试。次最大强度变量包括总机械效率、摄氧量(VO)、心率、乳酸、预计力竭时间(pTE)、主观用力感觉等级(RPE)、功率输出和心率恢复(HRR),它们是这3种测试的组成部分。pTE、次最大强度功率输出、RPE和HRR在监测运动表现提升方面似乎最具价值,并且能表明疲劳状态。这篇文献综述表明,在过去十年中已经开发了几种次最大强度自行车测试,旨在预测、监测和优化自行车运动表现。为了能够定期进行次最大强度测试,测试需要持续时间短且尽可能无创。此外,一项测试应涵盖多个变量,并使用多变量分析来正确解释次最大强度测试结果,并在需要时调整训练方案。