Pérez-Castilla Alejandro, Piepoli Antonio, Garrido-Blanca Gabriel, Delgado-García Gabriel, Balsalobre-Fernández Carlos, García-Ramos Amador
Int J Sports Physiol Perform. 2019 Nov 1;14(10):1442-1446. doi: 10.1123/ijspp.2018-0801.
To compare the accuracy of different devices to predict the bench-press 1-repetition maximum (1RM) from the individual load-velocity relationship modeled through the multiple- and 2-point methods.
Eleven men performed an incremental test on a Smith machine against 5 loads (45-55-65-75-85%1RM), followed by 1RM attempts. The mean velocity was simultaneously measured by 1 linear velocity transducer (T-Force), 2 linear position transducers (Chronojump and Speed4Lift), 1 camera-based optoelectronic system (Velowin), 2 inertial measurement units (PUSH Band and Beast Sensor), and 1 smartphone application (My Lift). The velocity recorded at the 5 loads (45-55-65-75-85%1RM), or only at the 2 most distant loads (45-85%1RM), was considered for the multiple- and 2-point methods, respectively.
An acceptable and comparable accuracy in the estimation of the 1RM was observed for the T-Force, Chronojump, Speed4Lift, Velowin, and My Lift when using both the multiple- and 2-point methods (effect size ≤ 0.40; Pearson correlation coefficient [r] ≥ .94; standard error of the estimate [SEE] ≤ 4.46 kg), whereas the accuracy of the PUSH (effect size = 0.70-0.83; r = .93-.94; SEE = 4.45-4.80 kg), and especially the Beast Sensor (effect size = 0.36-0.84; r = .50-.68; SEE = 9.44-11.2 kg), was lower.
These results highlight that the accuracy of 1RM prediction methods based on movement velocity is device dependent, with the inertial measurement units providing the least accurate estimate of the 1RM.
通过多点法和两点法建立个体负荷-速度关系模型,比较不同设备预测卧推1次最大重复量(1RM)的准确性。
11名男性在史密斯机上针对5种负荷(45%-55%-65%-75%-85% 1RM)进行递增测试,随后进行1RM尝试。同时通过1个线性速度传感器(T-Force)、2个线性位置传感器(Chronojump和Speed4Lift)、1个基于摄像头的光电系统(Velowin)、2个惯性测量单元(PUSH Band和Beast Sensor)以及1个智能手机应用程序(My Lift)测量平均速度。分别采用多点法和两点法时,考虑在5种负荷(45%-55%-65%-75%-85% 1RM)下或仅在2种最远负荷(45%-85% 1RM)下记录速度。
使用多点法和两点法时,T-Force、Chronojump、Speed4Lift、Velowin和My Lift在1RM估计方面观察到可接受且可比的准确性(效应量≤0.40;皮尔逊相关系数[r]≥0.94;估计标准误差[SEE]≤4.46 kg),而PUSH的准确性较低(效应量=0.70 - 0.83;r = 0.93 - 0.94;SEE = 4.45 - 4.80 kg),尤其是Beast Sensor(效应量=0.36 - 0.84;r = 0.50 - 0.68;SEE = 9.44 - 11.2 kg)。
这些结果表明,基于运动速度的1RM预测方法的准确性取决于设备,惯性测量单元对1RM的估计最不准确。