Johnston Lucas A, Butler Robert J, Sparling Tawnee L, Queen Robin M
1Michael W. Krzyzewski Human Performance Research Laboratory, Department of Orthopaedic Surgery; 2Division of Physical Therapy, Department of Community and Family Medicine, Orthopaedic Surgery; and 3Department of Orthopaedic Surgery, Duke University, Durham, North Carolina.
J Strength Cond Res. 2015 Feb;29(2):396-407. doi: 10.1519/JSC.0000000000000779.
Vertical jump performance is related to high-level function in athletics. The purpose of this study was to determine whether a single set of biomechanical variables exist that can predict vertical jump height during multiple jumping strategies: single foot jump, drop jump, and countermovement jump. Three-dimensional mechanics were collected during the 3 different jumping tasks in 50 recreational male athletes. Three successful trials were analyzed for each jump type. Testing order was randomized to minimize fatigue effects, and the dominant limb was used for analysis. All discrete variables were correlated to jump height and the 10 variables that had the strongest correlation were inserted into a linear regression model to identify what variables predicted maximum jump height. No single set of variables that predicted jump height existed across all 3 jumping tasks. One foot jump height was predicted by peak knee power, peak hip extension moment, peak knee extension velocity, and the percentage of the trial when peak knee flexion velocity occurred (r = 0.58). Countermovement jump height was predicted by peak hip power, ankle range of motion, and knee range of motion (r = 0.65). Drop jump height was predicted by the peak vertical ground reaction force and the percentage of the trial when the peak hip velocity occurred (r = 0.37). A single set of variables was not identified that could predict jump performance across different types of jumping tasks; therefore, additional interventional investigations are needed to better understand how to alter and improve jump performance.
垂直跳跃能力与田径运动中的高水平表现相关。本研究的目的是确定是否存在一组单一的生物力学变量,能够在多种跳跃策略(单脚跳、纵跳和蹲跳)中预测垂直跳跃高度。在50名男性业余运动员进行3种不同跳跃任务时收集了三维力学数据。每种跳跃类型分析3次成功的试验。测试顺序随机安排以尽量减少疲劳影响,并使用优势肢体进行分析。所有离散变量都与跳跃高度相关,将相关性最强的10个变量纳入线性回归模型,以确定哪些变量可预测最大跳跃高度。在所有3种跳跃任务中,不存在一组单一的变量能够预测跳跃高度。单脚跳高度由峰值膝关节功率、峰值髋关节伸展力矩、峰值膝关节伸展速度以及出现峰值膝关节屈曲速度时的试验百分比预测(r = 0.58)。蹲跳高度由峰值髋关节功率、踝关节活动范围和膝关节活动范围预测(r = 0.65)。纵跳高度由峰值垂直地面反作用力以及出现峰值髋关节速度时的试验百分比预测(r = 0.37)。未确定一组能够预测不同类型跳跃任务中跳跃表现的单一变量;因此,需要进行更多的干预性研究,以更好地了解如何改变和提高跳跃表现。