Sports Performance Research Institute New Zealand, Auckland University of Technology, 1142 Auckland, New Zealand.
Department of Sports Sciences and Physical Education, Nord University, 7601 Levanger, Norway.
Sensors (Basel). 2020 Dec 17;20(24):7240. doi: 10.3390/s20247240.
Vertical jump is a valuable training, testing, and readiness monitoring tool used across a multitude of sport settings. However, accurate field analysis has not always been readily available or affordable. For this study, two-dimensional motion capture (Mo-Cap), G-Flight micro-sensor, and PUSH accelerometer technologies were compared to a research-grade force-plate. Twelve healthy university students (7 males, 5 females) volunteered for this study. Each participant performed squat jumps, countermovement jumps, and drop jumps on three separate occasions. Between-device differences were determined using a one-way repeated measures ANOVA. Systematic bias was determined by limits of agreement using Bland-Altman analysis. Variability was examined via the coefficient of variation, interclass correlation coefficient, and typical error of measure. Dependent variables included jump height, contact-time, and reactive strength index (RSI). Mo-Cap held the greatest statistical similarity to force-plates, only overestimating contact-time (+12 ms). G-Flight (+1.3-4 cm) and PUSH (+4.1-4.5 cm) consistently overestimate jump height, while PUSH underestimates contact-time (-24 ms). Correspondingly, RSI was the most valid metric across all technologies. All technologies held small to moderate variably; however, variability was greatest with the G-Flight. While all technologies are practically implementable, practitioners may want to consider budget, athlete characteristics, exercise demands, set-up, and processing time before purchasing the most appropriate equipment.
垂直跳跃是一种在多种运动环境中被广泛应用的有价值的训练、测试和准备情况监测工具。然而，精确的现场分析并不总是易于获得或负担得起。在这项研究中，二维运动捕捉（Mo-Cap）、G-Flight 微传感器和 PUSH 加速度计技术与研究级测力板进行了比较。十二名健康的大学生（7 名男性，5 名女性）自愿参加了这项研究。每位参与者在三种不同情况下进行了深蹲跳、反向跳和跳落。使用单向重复测量方差分析来确定设备之间的差异。使用 Bland-Altman 分析确定系统偏差。通过变异系数、组内相关系数和测量的典型误差来检查可变性。跳跃高度、接触时间和反应强度指数（RSI）是依赖变量。Mo-Cap 与测力板具有最大的统计相似性，仅高估了接触时间（+12ms）。G-Flight（+1.3-4cm）和 PUSH（+4.1-4.5cm）持续高估跳跃高度，而 PUSH 低估接触时间（-24ms）。相应地，RSI 是所有技术中最有效的指标。所有技术的可变性都较小到中等；然而，G-Flight 的可变性最大。虽然所有技术都具有实际可操作性，但在购买最合适的设备之前，从业者可能需要考虑预算、运动员特征、运动需求、设置和处理时间。
