Bilateral and unilateral load-velocity profiling in a machine-based, single-joint, lower body exercise

被引:8
作者
Balsalobre-Fernandez, Carlos [1 ]
Cardiel-Garcia, Mario [2 ]
Jimenez, Sergio L. [2 ]
机构
[1] Autonomous Univeris Madrid, Dept Phys Educ Sport & Human Movement, Madrid, Spain
[2] European Univ Madrid, Sch Sports Sci, Madrid, Spain
关键词
MOVEMENT VELOCITY; INTENSITY;
D O I
10.1371/journal.pone.0222632
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background To analyze the goodness of fit of the load-velocity relationship in a machine-based, single joint exercise performed both in a bilateral and unilateral manner, as well as to study its accuracy to estimate one repetition maximum (1-RM). Methods Fifteen resistance trained males performed an incremental test in the bilateral and unilateral leg extension exercise up to the 1-RM in two separate occasions. Mean vertical velocity of the weight plates in the leg extension machine was measured for every repetition using a smartphone application (My Lift). Results Linear regression analyses showed a high goodness of fit (R-2 > 0.93) and small standard errors of estimate (SEE < 5%1-RM) both in the bilateral and unilateral leg extension when individual load-velocity regressions for each participant were computed. Unilateral load velocity relationships showed significant differences in the intercept of the regression line with the Y-axis and the velocity at each percentage of the 1-RM (Cohen's d>1.0, p<0.05). Finally, non-significant differences were observed between actual and estimated 1-RM from the load-velocity relationships (r=0.88.0-96, Cohen's d<0.2, p>0.05). Conclusions This proof of concept highlights that computing load-velocity relationships in a machine based, single-joint, angular exercise can be appropriately performed by measuring the mean vertical velocity of the weight plates. These results could help strength and conditioning researchers and coaches who wish to analyze load-velocity relationship in other common machine-based exercises.
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页数:10
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