Pérez-Castilla, A, Piepoli, A, Delgado-García, G, Garrido-Blanca, G, and García-Ramos, A. Reliability and concurrent validity of seven commercially available devices for the assessment of movement velocity at different intensities during the bench press. J Strength Cond Res 33(5): 1258–1265, 2019—The aim of this study was to compare the reliability and validity of 7 commercially available devices to measure movement velocity during the bench press exercise. Fourteen men completed 2 testing sessions. One-repetition maximum (1RM) in the bench press exercise was determined in the first session. The second testing session consisted of performing 3 repetitions against 5 loads (45, 55, 65, 75, and 85% of 1RM). The mean velocity was simultaneously measured using an optical motion sensing system (Trio-OptiTrack; “gold-standard”) and 7 commercially available devices: 1 linear velocity transducer (T-Force), 2 linear position transducers (Chronojump and Speed4Lift), 1 camera-based optoelectronic system (Velowin), 1 smartphone application (PowerLift), and 2 inertial measurement units (IMUs) (PUSH band and Beast sensor). The devices were ranked from the most to the least reliable as follows: (a) Speed4Lift (coefficient of variation [CV] = 2.61%); (b) Velowin (CV = 3.99%), PowerLift (3.97%), Trio-OptiTrack (CV = 4.04%), T-Force (CV = 4.35%), and Chronojump (CV = 4.53%); (c) PUSH band (CV = 9.34%); and (d) Beast sensor (CV = 35.0%). A practically perfect association between the Trio-OptiTrack system and the different devices was observed (Pearson's product-moment correlation coefficient (r) range = 0.947–0.995; p < 0.001) with the only exception of the Beast sensor (r = 0.765; p < 0.001). These results suggest that linear velocity/position transducers, camera-based optoelectronic systems, and the smartphone application could be used to obtain accurate velocity measurements for restricted linear movements, whereas the IMUs used in this study were less reliable and valid.

The quick, fatigue-free, and practical 2-point method was able to predict the BP 1RM with high reliability and practically perfect validity, and therefore, the authors recommend its use over generalized group equations.

These results highlight the need for obtaining specific equations for each BP variant and the existence of individual load-velocity profiles.

García-Ramos, A, Pestaña-Melero, FL, Pérez-Castilla, A, Rojas, FJ, and Haff, GG. Mean velocity vs. mean propulsive velocity vs. peak velocity: which variable determines bench press relative load with higher reliability? J Strength Cond Res 32(5): 1273-1279, 2018-This study aimed to compare between 3 velocity variables (mean velocity [MV], mean propulsive velocity [MPV], and peak velocity [PV]): (a) the linearity of the load-velocity relationship, (b) the accuracy of general regression equations to predict relative load (%1RM), and (c) the between-session reliability of the velocity attained at each percentage of the 1-repetition maximum (%1RM). The full load-velocity relationship of 30 men was evaluated by means of linear regression models in the concentric-only and eccentric-concentric bench press throw (BPT) variants performed with a Smith machine. The 2 sessions of each BPT variant were performed within the same week separated by 48-72 hours. The main findings were as follows: (a) the MV showed the strongest linearity of the load-velocity relationship (median r = 0.989 for concentric-only BPT and 0.993 for eccentric-concentric BPT), followed by MPV (median r = 0.983 for concentric-only BPT and 0.980 for eccentric-concentric BPT), and finally PV (median r = 0.974 for concentric-only BPT and 0.969 for eccentric-concentric BPT); (b) the accuracy of the general regression equations to predict relative load (%1RM) from movement velocity was higher for MV (SEE = 3.80-4.76%1RM) than for MPV (SEE = 4.91-5.56%1RM) and PV (SEE = 5.36-5.77%1RM); and (c) the PV showed the lowest within-subjects coefficient of variation (3.50%-3.87%), followed by MV (4.05%-4.93%), and finally MPV (5.11%-6.03%). Taken together, these results suggest that the MV could be the most appropriate variable for monitoring the relative load (%1RM) in the BPT exercise performed in a Smith machine.

Pérez-Castilla, A, García-Ramos, A, Padial, P, Morales-Artacho, AJ, and Feriche, B. Load-velocity relationship in variations of the half-squat exercise: influence of execution technique. J Strength Cond Res XX(X): 000-000, 2017-Previous studies have revealed that the velocity of the bar can be used to determine the intensity of different resistance training exercises. However, the load-velocity relationship seems to be exercise dependent. This study aimed to compare the load-velocity relationship obtained from 2 variations of the half-squat exercise (traditional vs. ballistic) using 2 execution techniques (eccentric-concentric vs. concentric-only). Twenty men performed a submaximal progressive loading test in 4 half-squat exercises: eccentric-concentric traditional-squat, concentric-only traditional-squat, countermovement jump (i.e., ballistic squat using the eccentric-concentric technique), and squat jump (i.e., ballistic squat using the concentric-only technique). Individual linear regressions were used to estimate the 1 repetition maximum (1RM) for each half-squat exercise. Thereafter, another linear regression was applied to establish the relationship between the relative load (%RM) and mean propulsive velocity (MPV). For all exercises, a strong relationship was observed between %RM and MPV: eccentric-concentric traditional-squat (R = 0.949), concentric-only traditional-squat (R = 0.920), countermovement jump (R = 0.957), and squat jump (R = 0.879). The velocities associated with each %RM were higher for the ballistic variation and the eccentric-concentric technique than for the traditional variation and concentric-only technique, respectively. Differences in velocity among the half-squat exercises decreased with the increment in the relative load. These results demonstrate that the MPV can be used to predict exercise intensity in the 4 half-squat exercises. However, independent regressions are required for each half-squat exercise because the load-velocity relationship proved to be task specific.

No abstract

Objective: 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. 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. Results: 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. Conclusions: 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.

This study aimed to explore the strength of the force-velocity (F-V) relationship of lower limb muscles and the reliability of its parameters (maximum force [F], slope [a], maximum velocity [V], and maximum power [P]). Twenty-three men were tested in two different jump types (squat and countermovement jump: SJ and CMJ), performed under two different loading conditions (free weight and Smith machine: Free and Smith) with 0, 17, 30, 45, 60, and 75 kg loads. The maximum and averaged values of F and V were obtained for the F-V relationship modelling. All F-V relationships were strong and linear independently whether observed from the averaged across the participants (r ≥ 0.98) or individual data (r = 0.94-0.98), while their parameters were generally highly reliable (F [CV: 4.85%, ICC: 0.87], V [CV: 6.10%, ICC: 0.82], a [CV: 10.5%, ICC: 0.81], and P [CV: 3.5%, ICC: 0.93]). Both the strength of the F-V relationships and the reliability of their parameters were significantly higher for (1) the CMJ over the SJ, (2) the Free over the Smith loading type, and (3) the maximum over the averaged F and V variables. In conclusion, although the F-V relationships obtained from all the jumps tested were linear and generally highly reliable, the less appropriate choice for testing the F-V relationship could be through the averaged F and V data obtained from the SJ performed either in a Free weight or in a Smith machine. Insubstantial differences exist among the other combinations tested.