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肢体角色、运动方向和肢体优势对排球中阻挡跳投落地时运动策略的影响。

The influence of limb role, direction of movement and limb dominance on movement strategies during block jump-landings in volleyball.

机构信息

Department of Physical and Sport Education, Faculty of Sport, Human Lab - Sport and Health University Research Institute (iMUDS), University of Granada, Carretera de Alfacar, s/n, 18011, Granada, Spain.

Department of Computer Science and Artificial Intelligence, DICITS, DASCI, IMUDS, University of Granada, Granada, Spain.

出版信息

Sci Rep. 2021 Dec 8;11(1):23668. doi: 10.1038/s41598-021-03106-0.

Abstract

The identification of movement strategies in situations that are as ecologically valid as possible is essential for the understanding of lower limb interactions. This study considered the kinetic and kinematic data for the hip, knee and ankle joints from 376 block jump-landings when moving in the dominant and non-dominant directions from fourteen senior national female volleyball players. Two Machine Learning methods were used to generate the models from the dataset, Random Forest and Artificial Neural Networks. In addition, decision trees were used to detect which variables were relevant to discern the limb movement strategies and to provide a meaningful prediction. The results showed statistically significant differences when comparing the movement strategies between limb role (accuracy > 88.0% and > 89.3%, respectively), and when moving in the different directions but performing the same role (accuracy > 92.3% and > 91.2%, respectively). This highlights the importance of considering limb dominance, limb role and direction of movement during block jump-landings in the identification of which biomechanical variables are the most influential in the movement strategies. Moreover, Machine Learning allows the exploration of how the joints of both limbs interact during sporting tasks, which could provide a greater understanding and identification of risky movements and preventative strategies. All these detailed and valuable descriptions could provide relevant information about how to improve the performance of the players and how to plan trainings in order to avoid an overload that could lead to risk of injury. This highlights that, there is a necessity to consider the learning models, in which the spike approach unilaterally is taught before the block approach (bilaterally). Therefore, we support the idea of teaching bilateral approach before learning the spike, in order to improve coordination and to avoid asymmetries between limbs.

摘要

在尽可能符合生态有效性的情况下识别运动策略对于理解下肢相互作用至关重要。本研究考虑了从 14 名高级国家女排运动员向优势和非优势方向移动时,376 次阻挡跳跃着陆的髋关节、膝关节和踝关节的运动学和运动学数据。两种机器学习方法(随机森林和人工神经网络)用于从数据集生成模型。此外,决策树用于检测哪些变量与辨别肢体运动策略相关,并提供有意义的预测。结果表明,当比较肢体作用(准确率分别为>88.0%和>89.3%)和不同方向但执行相同作用(准确率分别为>92.3%和>91.2%)的运动策略时,存在统计学上的显著差异。这强调了在识别哪些生物力学变量对运动策略最有影响时,考虑肢体优势、肢体作用和运动方向的重要性。此外,机器学习允许探索在体育任务中如何使两个肢体的关节相互作用,这可以提供对危险运动和预防策略的更好理解和识别。所有这些详细而有价值的描述都可以提供有关如何提高运动员表现以及如何规划训练以避免可能导致受伤风险的过载的相关信息。这强调了在学习之前,有必要考虑学习模型,即先教授单侧扣球方法(双侧)。因此,我们支持在学习扣球之前教授双侧方法的想法,以提高协调能力并避免肢体之间的不对称。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d76b/8654914/7153c8c868d4/41598_2021_3106_Fig1_HTML.jpg

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