Ma Shuzhen, Geok Soh Kim, Binti Japar Salimah, Xu Simao, Zhicheng Guo
Department of Sports Studies, Faculty of Educational Studies, Universiti Putra Malaysia, Selangor, 43400, Malaysia.
College of Public Administration, Guilin University of Technology, Guilin, 541004, China.
Heliyon. 2024 Jul 24;10(15):e35145. doi: 10.1016/j.heliyon.2024.e35145. eCollection 2024 Aug 15.
Core strength training plays an essential role in maximizing performance for badminton athletes. The core muscles in the abdominal, back, and hip regions provide stability, enable efficient power transfer between the upper and lower body, and allow for rapid changes in direction - all crucial components for success in badminton. However, optimizing core training requires an understanding of its impact on sport-specific skills. A variety of exercises targeting the abdominal, back, and hip muscles are discussed. Incorporating core strength training into regular regimens can improve athletes' overall strength, endurance, balance, control, and prevent injuries. This study investigates the effects of various core exercises on stability, agility, and power in badminton players. A comprehensive literature review was conducted to explore the biomechanical demands of badminton and how core musculature contributes to movements like serving, smashing, and lunging. Studies assessing the effects of core training programs in related racquet sports were also examined. The results indicate that targeted core exercises significantly improve athletes' stability, agility, and power output. Exercises targeting the abdominal, back, and hip muscles enhance performance capabilities while reducing injury risk. Machine learning (ML) techniques are then applied to further analyze the relationship between core training and athletic performance. An Artificial Neural Network (ANN) is developed using a dataset of athletes' training histories, metrics, and injury profiles. The model predicts enhancements to stability, agility, and strength from optimized core strengthening routines. Validation confirms the network accurately captures the complex interactions between training variables and physical attributes. This integrated approach provides evidence-based guidelines for tailoring individualized training regimens to unleash players' full abilities. ANNs hold promise for analyzing large datasets on athletes' performance metrics, training variables, and injury histories to design personalized training programs. Linear regression analysis confirmed the ANN's accurate predictions. The findings emphasize integrating data-driven core strength training tailored for badminton into comprehensive programs can help optimize physical abilities and elevate performance levels.
核心力量训练对于羽毛球运动员发挥最佳水平起着至关重要的作用。腹部、背部和臀部区域的核心肌肉提供稳定性，使上下半身之间能够有效地传递力量，并能实现快速变向——这些都是羽毛球运动取得成功的关键要素。然而，优化核心训练需要了解其对特定运动技能的影响。本文讨论了针对腹部、背部和臀部肌肉的各种练习。将核心力量训练纳入常规训练方案可以提高运动员的整体力量、耐力、平衡能力和控制能力，并预防受伤。本研究调查了各种核心练习对羽毛球运动员稳定性、敏捷性和力量的影响。进行了全面的文献综述，以探讨羽毛球的生物力学需求以及核心肌肉组织如何助力发球、扣杀和弓步等动作。还研究了评估核心训练计划对相关球拍运动影响的研究。结果表明，有针对性的核心练习能显著提高运动员的稳定性、敏捷性和力量输出。针对腹部、背部和臀部肌肉的练习在提高运动表现能力的同时降低了受伤风险。然后应用机器学习（ML）技术进一步分析核心训练与运动表现之间的关系。使用运动员的训练历史、指标和伤病情况数据集开发了一个人工神经网络（ANN）。该模型预测优化后的核心强化训练对稳定性、敏捷性和力量的提升效果。验证证实该网络准确捕捉了训练变量与身体属性之间的复杂相互作用。这种综合方法为制定个性化训练方案提供了循证指南，以释放运动员的全部能力。人工神经网络有望分析关于运动员表现指标、训练变量和伤病历史的大型数据集，以设计个性化训练计划。线性回归分析证实了人工神经网络的准确预测。研究结果强调，将为羽毛球量身定制的数据驱动型核心力量训练纳入综合训练计划有助于优化身体能力并提高运动表现水平。
