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相关概念视频

Exercise and Muscle Performance01:27

Exercise and Muscle Performance

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Exercise induces a range of adaptations in muscle tissue, depending on the type and duration of activity. Such physical training can be broadly categorized into two types: endurance exercises and resistance exercises.
Endurance exercises
Endurance exercises involve running, swimming, or cycling, which require repetitive movements with low force output. When a person engages in endurance exercise, a few noticeable changes occur in their skeletal muscles. For instance, the number of capillaries...
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An Innovative Running Wheel-based Mechanism for Improved Rat Training Performance
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基于机器学习的个性化训练模型,通过金字塔式和极化训练强度分布来优化马拉松表现.

Gang Qin1, Seongno Lee1, Sungmin Kim2,3,4

  • 1Major in Sport Science, College of Performing Arts and Sport, Hanyang University, 04763, Seoul, Republic of Korea.

Scientific reports
|November 25, 2025
PubMed
概括

个性化的马拉松训练强度分布是关键. 机器学习发现,经验丰富的跑步者从两极分化的训练中获益更多,而新手则擅长使用金字塔式方法,显著提高了表现.

关键词:
耐力训练是一种耐力训练.强度分布 强度分布机器学习是机器学习.马拉松比赛的表现个性化培训 个性化培训培训优化培训的优化

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科学领域:

  • 运动生理学 运动生理学
  • 运动科学 运动科学 运动科学
  • 运动中的机器学习

背景情况:

  • 马拉松跑者对训练强度分布的个体反应在马拉松跑者中存在显著差异.
  • 了解这些个体差异对于优化性能至关重要.
  • 当前的培训处方往往缺乏个性化.

研究的目的:

  • 为了比较马拉松选手的金字塔式和偏振式训练方法.
  • 利用机器学习来识别个性化的训练强度分配策略.
  • 根据运动员的特点预测最佳的训练方法.

主要方法:

  • 120名休马拉松跑者被随机分配到16周的金字塔式或两极化训练组.
  • 机器学习模型使用消费者级监测数据分析了个人训练反应.
  • 运动员的特征被用来预测最有效的训练方法.

主要成果:

  • 与金字塔式训练 (8.7分钟) 相比,两极化训练带来了更好的马拉松性能改善 (11.3分钟),提高了30%的效果.
  • 确定了四个不同的响应集群:两极分化的响应者 (31.5%),金字塔式响应者 (31.9%),双响应者 (18.7%) 和非响应者 (17.9%).
  • 训练经验是有效性最强的预测指标 (r=0.72),新手更喜欢金字塔式训练,经验丰富的跑步者更喜欢两极化训练.

结论:

  • 显著的个体间变异性需要个性化训练强度分布,而不是通用方法.
  • 机器学习成功地使用可访问的运动员数据预测了最佳训练方法.
  • 这为基于证据的,个性化的马拉松准备提供了实际框架.