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根据重复速度和速度损失预测深蹲总重复次数

Predicting Total Back Squat Repetitions from Repetition Velocity and Velocity Loss.

作者信息

Haischer Michael H, Carzoli Joseph P, Cooke Daniel M, Pelland Joshua C, Remmert Jacob F, Zourdos Michael C

机构信息

Department of Exercise Science and Health Promotion, Muscle Physiology Laboratory, Florida Atlantic University, Boca Raton, FL, USA.

出版信息

J Hum Kinet. 2023 Apr 20;87:167-178. doi: 10.5114/jhk/162021. eCollection 2023 Apr.

Abstract

The purpose of this investigation was to determine if average concentric velocity (ACV) of a single repetition at 70% of one-repetition maximum (1RM), ACV of the first repetition of a set to failure at 70% of 1RM, or the velocity loss during the set could predict the number of repetitions performed in the back squat. Fifty-six resistance-trained individuals participated in the study (male = 41, age = 23 ± 3 yrs, 1RM = 162.0 ± 40.0 kg; female = 15, age = 21 ± 2 yrs, 1RM = 81.5 ± 12.5 kg). After 1RM testing, participants performed single repetition sets with 70% of 1RM and a set to failure with 70% of 1RM. ACV was recorded on all repetitions. Regression model comparisons were performed, and Akaike Information Criteria (AIC) and Standard Error of the Estimate (SEE) were calculated to determine the best model. Neither single repetition ACV at 70% of 1RM (R = 0.004, p = 0.637) nor velocity loss (R = 0.011, p = 0.445) were predictive of total repetitions performed in the set to failure. The simple quadratic model using the first repetition of the set to failure () was identified as the best and most parsimonious model (R = 0.259, F = 9.247, p < 0.001) due to the lowest AIC value (311.086). A SEE of 2.21 repetitions was identified with this model. This average error of ~2 repetitions warrants only cautious utilization of this method to predict total repetitions an individual can perform in a set, with additional autoregulatory or individualization strategies being necessary to finalize the training prescription.

摘要

本研究的目的是确定在一次重复最大值(1RM)的70%时单次重复的平均向心速度(ACV)、在1RM的70%时一组重复至力竭的第一次重复的ACV,或者该组重复过程中的速度损失,是否能够预测后深蹲练习中完成的重复次数。56名经过抗阻训练的个体参与了该研究(男性41名,年龄 = 23 ± 3岁,1RM = 162.0 ± 40.0千克;女性15名,年龄 = 21 ± 2岁,1RM = 81.5 ± 12.5千克)。在进行1RM测试后,参与者进行了1RM的70%的单次重复组以及1RM的70%的重复至力竭组练习。记录了所有重复动作的ACV。进行了回归模型比较,并计算了赤池信息准则(AIC)和估计标准误差(SEE)以确定最佳模型。1RM的7向心速度(R = 0.004,p = 0.637)和速度损失(R = 0.011,p = 0.445)均不能预测重复至力竭组中完成的总重复次数。使用重复至力竭组的第一次重复的简单二次模型()被确定为最佳且最简约的模型(R = 0.259,F = 9.247,p < 0.001),因为其AIC值最低(311.086)。该模型的SEE为2.21次重复。这种约2次重复的平均误差表明,仅谨慎使用此方法来预测个体在一组中能够完成的总重复次数是必要的,还需要额外的自动调节或个体化策略来最终确定训练方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6033/10203840/03606af8bc30/JHK-87-162021-g001.jpg

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