Storniolo Jorge L, Pavei Gaspare, Minetti Alberto E
Laboratory of Locomotion Physiomechanics, Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy.
Front Physiol. 2017 Nov 1;8:868. doi: 10.3389/fphys.2017.00868. eCollection 2017.
Maximum aerobic power ([Formula: see text]) as an indicator of body fitness is today a very well-known concept not just for athletes but also for the layman. Unfortunately, the accurate measurement of that variable has remained a complex and exhaustive laboratory procedure, which makes it inaccessible to many active people. In this paper we propose a quick estimate of it, mainly based on the heart rate off-kinetics immediately after an all-out 60-m sprint run. The design of this test took into account the recent availability of wrist wearable, heart band free, multi-sensor smart devices, which could also inertially detect the different phases of the sprint and check the distance run. 25 subjects undertook the 60-m test outdoor and a [Formula: see text] test on the laboratory treadmill. Running average speed, HR excursion during the sprint and the time constant (τ) of HR exponential decay in the off-kinetics were fed into a multiple regression, with measured [Formula: see text] as the dependent variable. Statistics revealed that within the investigated range (25-55 ml O/(kg min)), despite a tendency to overestimate low values and underestimate high values, the three predictors confidently estimate individual [Formula: see text] ( = 0.65, < 0.001). The same analysis has been performed on a 5-s averaged time course of the same measured HR off-kinetics, as these are the most time resolved data for HR provided by many modern smart watches. Results indicate that despite of the substantial reduction in sample size, predicted [Formula: see text] still explain 59% of the variability of the measured [Formula: see text].
最大有氧能力([公式:见原文])作为身体适应性的指标,如今不仅对运动员,而且对外行来说都是一个广为人知的概念。不幸的是,该变量的准确测量仍然是一个复杂且详尽的实验室程序,这使得许多活跃人群无法进行。在本文中,我们提出一种对其的快速估计方法,主要基于全力冲刺60米跑后心率的动力学变化。该测试的设计考虑到了近期出现的无需心率带的腕部可穿戴多传感器智能设备,这些设备还能通过惯性检测冲刺的不同阶段并核查跑过的距离。25名受试者在户外进行了60米测试,并在实验室跑步机上进行了[公式:见原文]测试。将跑步平均速度、冲刺过程中的心率波动以及心率动力学变化中指数衰减的时间常数(τ)输入多元回归模型,以测量得到的[公式:见原文]作为因变量。统计结果显示,在研究范围内(25 - 55毫升氧气/(千克·分钟)),尽管存在高估低值和低估高值的趋势,但这三个预测指标能够可靠地估计个体的[公式:见原文]( = 0.65,< 0.001)。对相同测量的心率动力学变化的5秒平均时间进程进行了同样的分析,因为这些是许多现代智能手表提供的关于心率的时间分辨率最高的数据。结果表明,尽管样本量大幅减少,但预测的[公式:见原文]仍能解释测量得到的[公式:见原文]变异性的59%。