The purpose of this study was to analyze the validity, reliability, and accuracy of new wearable and smartphone-based technology for the measurement of barbell velocity in resistance training exercises. To do this, 10 highly trained powerlifters (age = 26.1 ± 3.9 years) performed 11 repetitions with loads ranging 50–100% of the 1-Repetition maximum in the bench-press, full-squat, and hip-thrust exercises while barbell velocity was simultaneously measured using a linear transducer (LT), two Beast wearable devices (one placed on the subjects' wrist –BW–, and the other one directly attached to the barbell –BB–) and the iOS PowerLift app. Results showed a high correlation between the LT and BW (r = 0.94–0.98, SEE = 0.04–0.07 m•s−1), BB (r = 0.97–0.98, SEE = 0.04–0.05 m•s−1), and the PowerLift app (r = 0.97–0.98, SEE = 0.03–0.05 m•s−1) for the measurement of barbell velocity in the three exercises. Paired samples T-test revealed systematic biases between the LT and BW, BB and the app in the hip-thrust, between the LT and BW in the full-squat and between the LT and BB in the bench-press exercise (p < 0.001). Moreover, the analysis of the linear regression on the Bland-Altman plots showed that the differences between the LT and BW (R2 = 0.004–0.03), BB (R2 = 0.007–0.01), and the app (R2 = 0.001–0.03) were similar across the whole range of velocities analyzed. Finally, the reliability of the BW (ICC = 0.910–0.988), BB (ICC = 0.922–0.990), and the app (ICC = 0.928–0.989) for the measurement of the two repetitions performed with each load were almost the same than that observed with the LT (ICC = 0.937–0.990). Both the Beast wearable device and the PowerLift app were highly valid, reliable, and accurate for the measurement of barbell velocity in the bench-press, full-squat, and hip-thrust exercises. These results could have potential practical applications for strength and conditioning coaches who wish to measure barbell velocity during resistance training.

The purpose of this study was to analyse the validity and reliability of a novel iPhone app (named: PowerLift) for the measurement of mean velocity on the bench-press exercise. Additionally, the accuracy of the estimation of the 1-Repetition maximum (1RM) using the load-velocity relationship was tested. To do this, 10 powerlifters (Mean (SD): age = 26.5 ± 6.5 years; bench press 1RM · kg = 1.34 ± 0.25) completed an incremental test on the bench-press exercise with 5 different loads (75-100% 1RM), while the mean velocity of the barbell was registered using a linear transducer (LT) and Powerlift. Results showed a very high correlation between the LT and the app (r = 0.94, SEE = 0.028 m · s) for the measurement of mean velocity. Bland-Altman plots (R = 0.011) and intraclass correlation coefficient (ICC = 0.965) revealed a very high agreement between both devices. A systematic bias by which the app registered slightly higher values than the LT (P < 0.05; mean difference (SD) between instruments = 0.008 ± 0.03 m · s). Finally, actual and estimated 1RM using the app were highly correlated (r = 0.98, mean difference (SD) = 5.5 ± 9.6 kg, P < 0.05). The app was found to be highly valid and reliable in comparison with a LT. These findings could have valuable practical applications for strength and conditioning coaches who wish to measure barbell velocity in the bench-press exercise.

The very high load-velocity, force-velocity, and power-velocity relationships enables estimation of 1-RM by measuring movement velocity, as well as determination of maximal force, velocity, and power capabilities. This information could be of great interest to strength and conditioning coaches who wish to monitor pull-up performance.

Balsalobre-Fernández, C, Muñoz-López, M, Marchante, D, and García-Ramos, A. Repetitions in reserve and rate of perceived exertion increase the prediction capabilities of the load-velocity relationship. J Strength Cond Res 35(3): 724–730, 2021—This study aimed to (a) analyze the relationships between relative load (i.e., %1 repetition maximum; 1RM) and movement velocity, repetitions in reserve (RIR) and rate of perceived exertion (RPE) in competitive powerlifters and (b) examine whether a multiple linear regression model with the movement velocity, RIR, and RPE as predictor variables could improve the goodness of fit of the load-velocity relationship. Ten competitive powerlifters performed an incremental loading test (from 50 to 100% 1RM) on the full-squat, hip-thrust, and bench press exercises. Barbell velocity was measured using a linear position transducer, while RIR and RPE were registered immediately after each set. Velocity (r 2: 0.747–0.887), RIR (r 2: 0.857–0.928), and RPE (r 2: 0.908–0.933) were moderately to highly related to relative load. A higher amount of variance of the relative load was explained when the RIR and RPE were added to velocity in a multiple regression model in comparison with the load-velocity relationship (r 2: 0.924–0.947). Moreover, it was observed that, in all cases, individual load-velocity, load-RIR, and load-RPE relationships had higher r 2 scores than the generalized load-velocity relationship. Incorporating the RIR and RPE as predictors of the relative load along with movement velocity into a multiple linear regression was shown to provide better estimations of the %1RM than using a linear load-velocity relationship.