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物理随机性训练对新手虚拟和实验室高尔夫推杆表现的影响。

Effects of physical randomness training on virtual and laboratory golf putting performance in novices.

作者信息

Pataky T C, Lamb P F

机构信息

a Institute for Fiber Engineering , Shinshu University , Ueda , Japan.

b School of Physical Education, Sport and Exercise Sciences , University of Otago , Dunedin , New Zealand.

出版信息

J Sports Sci. 2018 Jun;36(12):1355-1362. doi: 10.1080/02640414.2017.1378493. Epub 2017 Oct 9.

Abstract

External randomness exists in all sports but is perhaps most obvious in golf putting where robotic putters sink only 80% of 5 m putts due to unpredictable ball-green dynamics. The purpose of this study was to test whether physical randomness training can improve putting performance in novices. A virtual random-physics golf-putting game was developed based on controlled ball-roll data. Thirty-two subjects were assigned a unique randomness gain (RG) ranging from 0.1 to 2.0-times real-world randomness. Putter face kinematics were measured in 5 m laboratory putts before and after five days of virtual training. Performance was quantified using putt success rate and "miss-adjustment correlation" (MAC), the correlation between left-right miss magnitude and subsequent right-left kinematic adjustments. Results showed no RG-success correlation (r = -0.066, p = 0.719) but mildly stronger correlations with MAC for face angle (r = -0.168, p = 0.358) and clubhead path (r = -0.302, p = 0.093). The strongest RG-MAC correlation was observed during virtual training (r = -0.692, p < 0.001). These results suggest that subjects quickly adapt to physical randomness in virtual training, and also that this learning may weakly transfer to real golf putting kinematics. Adaptation to external physical randomness during virtual training may therefore help golfers adapt to external randomness in real-world environments.

摘要

外部随机性存在于所有运动项目中,但在高尔夫球推杆运动中可能最为明显,在该运动中,由于不可预测的球与果岭之间的动态关系,机器人推杆在5米推杆时的成功率仅为80%。本研究的目的是测试物理随机性训练是否能提高新手的推杆表现。基于可控的球滚动数据开发了一款虚拟随机物理高尔夫推杆游戏。32名受试者被分配了一个独特的随机性增益(RG),范围从现实世界随机性的0.1倍到2.0倍。在进行五天虚拟训练前后,在实验室中对5米推杆时的推杆杆面运动学进行了测量。使用推杆成功率和“失误调整相关性”(MAC)对表现进行量化,“失误调整相关性”是指左右失误幅度与随后的左右运动学调整之间的相关性。结果显示,RG与成功率之间没有相关性(r = -0.066,p = 0.719),但与杆面角度的MAC有稍强的相关性(r = -0.168,p = 0.358),与杆头路径的MAC也有稍强的相关性(r = -0.302,p = 0.093)。在虚拟训练期间观察到最强的RG - MAC相关性(r = -0.692,p < 0.001)。这些结果表明,受试者在虚拟训练中能迅速适应物理随机性,并且这种学习可能会微弱地转移到实际高尔夫推杆运动学中。因此,在虚拟训练中适应外部物理随机性可能有助于高尔夫球手在现实环境中适应外部随机性。

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