Human Performance and Sports Science Laboratory, Faculty of Sport Sciences, University of Murcia, Murcia, Spain.
Exercise Physiology Lab at Toledo, University of Castilla-La Mancha, Toledo, Spain.
Eur J Sport Sci. 2021 Mar;21(3):341-350. doi: 10.1080/17461391.2020.1748117. Epub 2020 Apr 26.
Training prescription in running activities have benefited from power output (P) data obtained by new technologies. Nevertheless, to date, the suitability of P data provided by these tools is still uncertain. The present study aimed to: (i) analyze the repeatability of five commercially available technologies for running P estimation, and (ii) examine the concurrent validity through the relationship between each technology P and oxygen uptake (VO). On two occasions (test-retest), twelve endurance-trained male athletes performed on a treadmill (indoor) and an athletic track (outdoor) three submaximal running protocols with manipulations in speed, body weight and slope. P was simultaneously registered by the commercial technologies Stryd, Stryd, RunScribe, Garmin and Polar, while VO was monitored by a metabolic cart. Test-retest data from the environments (indoor and outdoor) and conditions (speed, body weight and slope) were used for repeatability analysis, which included the standard error of measurement (SEM), coefficient of variation (CV) and intraclass correlation coefficient (ICC). A linear regression analysis and the standard error of estimate (SEE) were used to examine the relationship between P and VO. Stryd device was found as the most repeatable technology for all environments and conditions (SEM ≤ 12.5 W, CV ≤ 4.3%, ICC ≥ 0.980), besides the best concurrent validity to the VO ( ≥ 0.911, SEE ≤ 7.3%). On the contrary, although the Polar, Garmin and RunScribe technologies maintain a certain relationship with VO, their low repeatability questions their suitability. The Stryd can be considered as the most recommended tool, among the analyzed, for P measurement.
在跑步活动中，训练方案受益于新技术获得的功率输出（P）数据。然而，迄今为止，这些工具提供的 P 数据的适用性仍然不确定。本研究旨在：（i）分析五种市售的跑步 P 估计技术的可重复性，（ii）通过每种技术 P 与耗氧量（VO）的关系来检验其同时效度。在两次测试（测试-再测试）中，十二名耐力训练的男性运动员在跑步机（室内）和田径场（室外）上进行了三种亚最大速度跑步协议，速度、体重和坡度进行了调整。商业技术 Stryd、Stryd、RunScribe、Garmin 和 Polar 同时记录 P，而 VO 则通过代谢箱监测。来自环境（室内和室外）和条件（速度、体重和坡度）的测试-再测试数据用于可重复性分析，包括测量误差（SEM）、变异系数（CV）和组内相关系数（ICC）。线性回归分析和估计标准误差（SEE）用于检验 P 与 VO 之间的关系。Stryd 设备被发现是所有环境和条件下最可重复的技术（SEM≤12.5W，CV≤4.3%，ICC≥0.980），除了与 VO 具有最佳的同时效度（≥0.911，SEE≤7.3%）。相反，尽管 Polar、Garmin 和 RunScribe 技术与 VO 保持一定的关系，但它们的低可重复性质疑其适用性。Stryd 可以被认为是在分析的工具中，最适合用于 P 测量的工具。
