在性能稳定之外的实践增加了对拦截任务中不可预测干扰的在线调整的使用
Crislaine Rangel Couto1, Cláudio Manoel Ferreira Leite2, Carlos Eduardo Campos1
1Sports Department, Universidade Federal de Minas Gerais-UFMG, Belo Horizonte, Minas Gerais, Brazil.
PloS one
|November 5, 2025
概括
除了稳定之外的扩展实践可以提高拦截任务中的运动适应性. 超级稳定改进了在线反的使用,用于调整不可预测的目标变化.
科学领域:
- 运动控制和学习.
- 人类运动科学 人类运动科学
- 感知运动技能是什么
背景情况:
- 传统的运动学习研究往往侧重于可预测的环境.
- 新出现的证据表明,扩展实践改善了对不可预测性的适应.
- 了解练习的局限性对于技能提升至关重要.
研究的目的:
- 为了比较练习到性能稳定与超稳定对电机调整的影响.
- 为了调查适应能力,以应对在目标拦截期间不可预测的干扰.
- 测试超稳定增强对意外事件的运动调整的假设.
主要方法:
- 40名参与者执行了一个目标拦截任务.
- 根据实现性能稳定或超级稳定,分组进行了划分.
- 然后,参与者在不可预测的环境中进行了测试,目标速度发生了意想不到的变化.
主要成果:
- 超稳定组对扰动的调整 (N-cor) 显著增加.
- 这种增强的适应与更有效的在线反利用有关.
- 在性能稳定之前的实践没有产生类似的适应性益处.
结论:
- 运动学习超越了性能稳定,强调了持续练习的价值.
- 超稳定促进了对动态和不可预测的环境的卓越适应能力.
- 扩展的实践是有利于掌握运动技能在不同的背景下.
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