平均最佳最小速度值:一个实际的变量,以提高在自由重量背 squat期间一次重复的最大估计的准确性
Afonso Fitas1, Miguel Gomes1,2, Paulo Santos1,2
1Neuromuscular Research Lab, Faculdade de Motricidade Humana, Universidade de Lisboa, Dafundo, Portugal.
Journal of sports sciences
|October 2, 2024
概括
使用负载-速度关系 (LVR) 预测一次重复最大值 (1RM) 是力量训练的关键. 使用最佳最小速度值 (MVT) 提高了准确性,尽管实际应用仍然面临着精确性挑战.
科学领域:
- 运动科学 运动科学 运动科学
- 生物力学 生物力学
- 强度和适应条件 强度和适应条件
背景情况:
- 负载-速度关系 (LVR) 在强度和调节方面对预测一次重复最大值 (1RM) 至关重要.
- 已提出最佳最小速度值 (MVT),以提高1RM预测的准确性.
- 实际应用需要评估平均最佳MVT对估计的实用性.
研究的目的:
- 为了比较1RM预测的准确性,使用平均实际MVP与平均最佳MVP.
- 评估选择的负载数量对LVR参数和1RM预测准确性的影响.
- 评估预测错误对跟踪1RM变化的实际影响.
主要方法:
- 在两个会议中收集了53名参与者的自由体重背的LVR数据.
- 使用多点和两点方法来获得LVR.
- 通过使用平均实际MVP和平均最佳MVP进行1RM估计,并通过离开一项分析进行交叉验证.
主要成果:
- 使用平均最佳MVT的预测显示出更高的准确性 (约. 6%的绝对百分比误差) 与平均实际的MVP相比 (大约. 8%) 的比例.
- 使用的负载数量没有显著影响LVR斜率,拦截,最佳MVT或预测准确度.
- 广泛的95%的协议限制 (大约. 13% (1RM) 在两个预测方法中都被观察到.
结论:
- 平均最佳MVP提供了比平均实际MVP更准确的1RM估计.
- 尽管精度提高了,但大量的预测错误限制了微小的1RM波动的精确跟踪.
- 可能需要进一步的研究来完善更精确的1RM监测方法.
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