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6 分钟亚极量跑步测试预测最大摄氧量。

A 6-minute sub-maximal run test to predict VO max.

机构信息

a Centro de Investigación en Tecnoloxías da Información (CiTIUS) , Universidade de Santiago de Compostela , Santiago de Compostela , Spain.

b Department of Sport, Exercise and Rehabilitation , Northumbria University , Newcastle-upon-Tyne , UK.

出版信息

J Sports Sci. 2018 Nov;36(22):2531-2536. doi: 10.1080/02640414.2018.1468149. Epub 2018 Apr 24.

DOI:10.1080/02640414.2018.1468149
PMID:29688149
Abstract

Maximal oxygen uptake ([Formula: see text] max) is a key indicator to assess health as well as sports performance. Currently, maximal exercise testing is the most accurate measure of maximal aerobic power, since submaximal approaches are still imprecise. In this paper, we propose a new method to predict [Formula: see text] max from a submaximal, low intensity, test in sports men and women. 182 males and 108 females from the High Performance Center of Pontevedra (Spain), aged 10-46 years old, with a [Formula: see text] max between 30.1 and 81.2 mL·min·kg, completed a maximal incremental test to volitional exhaustion. The test began at a speed of 6 km·h and increased by 0.25 km·h every 15 seconds. Using the data gathered during the first 6 minutes of the test, two different regression models were adjusted using functional data analysis and a traditional linear regression model with scalar covariates. The functional regression model obtained the best results, adjusted r = 0.845 and RMSE = 2.8 mL·min·kg, but the linear regression model also obtained a good fit, adjusted r = 0.798 and RMSE = 3.5 mL·min·kg. Both methods are more accurate than classical submaximal tests, although oxygen consumption needs to be measured during the test.

摘要

最大摄氧量 ([Formula: see text] max) 是评估健康和运动表现的关键指标。目前,最大运动测试是最大有氧能力的最准确测量方法,因为亚最大方法仍然不够精确。在本文中,我们提出了一种新的方法,可以从男性和女性运动员的亚最大、低强度测试中预测 [Formula: see text] max。来自西班牙蓬特韦德拉高性能中心的 182 名男性和 108 名女性,年龄在 10-46 岁之间,[Formula: see text] max 在 30.1 至 81.2 mL·min·kg 之间,完成了最大递增至力竭的测试。测试以 6 公里/小时的速度开始,每 15 秒增加 0.25 公里/小时。使用测试前 6 分钟收集的数据,使用功能数据分析和带有标量协变量的传统线性回归模型分别调整了两个不同的回归模型。功能回归模型得到了最好的结果,调整 r=0.845,RMSE=2.8 mL·min·kg,但线性回归模型也得到了很好的拟合,调整 r=0.798,RMSE=3.5 mL·min·kg。这两种方法都比经典的亚最大测试更准确,尽管在测试过程中需要测量耗氧量。

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