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Assessment of the load-velocity profile in the free-weight prone bench pull exercise through different velocity variables and regression models.

ABSTRACT: This aims of this study were (I) to determine the velocity variable and regression model which best fit the load-velocity relationship during the free-weight prone bench pull exercise, (II) to compare the reliability of the velocity attained at each percentage of the one-repetition maximum (1RM) between different velocity variables and regression models, and (III) to compare the within- and between-subject variability of the velocity attained at each %1RM. Eighteen men (14 rowers and four weightlifters) performed an incremental test during the free-weight prone bench pull exercise in two different sessions. General and individual load-velocity relationships were modelled through three velocity variables (mean velocity [MV], mean propulsive velocity [MPV] and peak velocity [PV]) and two regression models (linear and second-order polynomial). The main findings revealed that (I) the general (Pearson's correlation coefficient [r] range = 0.964-0.973) and individual (median r = 0.986 for MV, 0.989 for MPV, and 0.984 for PV) load-velocity relationships were highly linear, (II) the reliability of the velocity attained at each %1RM did not meaningfully differ between the velocity variables (coefficient of variation [CV] range = 2.55-7.61% for MV, 2.84-7.72% for MPV and 3.50-6.03% for PV) neither between the regression models (CV range = 2.55-7.72% and 2.73-5.25% for the linear and polynomial regressions, respectively), and (III) the within-subject variability of the velocity attained at each %1RM was lower than the between-subject variability for the light-moderate loads. No meaningful differences between the within- and between-subject CVs were observed for the MV of the 1RM trial (6.02% vs. 6.60%; CVratio = 1.10), while the within-subject CV was lower for PV (6.36% vs. 7.56%; CVratio = 1.19). These results suggest that the individual load-MV relationship should be determined with a linear regression model to obtain the most accurate prescription of the relative load during the free-weight prone bench pull exercise.

SUBMITTER: Garcia-Ramos A

PROVIDER: S-EPMC6392250 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Assessment of the load-velocity profile in the free-weight prone bench pull exercise through different velocity variables and regression models.

García-Ramos Amador A Ulloa-Díaz David D Barboza-González Paola P Rodríguez-Perea Ángela Á Martínez-García Darío D Quidel-Catrilelbún Mauricio M Guede-Rojas Francisco F Cuevas-Aburto Jesualdo J Janicijevic Danica D Weakley Jonathon J

PloS one 20190227 2

This aims of this study were (I) to determine the velocity variable and regression model which best fit the load-velocity relationship during the free-weight prone bench pull exercise, (II) to compare the reliability of the velocity attained at each percentage of the one-repetition maximum (1RM) between different velocity variables and regression models, and (III) to compare the within- and between-subject variability of the velocity attained at each %1RM. Eighteen men (14 rowers and four weight ...[more]

PMID: 30811432

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Project description:ObjectiveThe intensity of barbell bench press exercise is generally prescribed as the load to be lifted for a specific number of repetitions; however, other factors (e.g., execution velocity) can affect bench press exercise intensity. Moreover, no study assessed whether load distribution (i.e., the distance between the disc stacks on the two sides of the barbell) affects exercise intensity. The present study aims to assess how different combinations of load, velocity, and barbell load distribution affect the number of repetitions to failure (REPfailure), and rating of perceived exertion (RPEfatigue) and number of repetitions (REPfatigue) at fatigue onset.MethodsTen males (age 23.3±1.8 years) performed bench press exercises to exhaustion using random combinations of three loads (50%, 65%, and 80% of 1 repetition maximum), three execution velocities (50%, 70%, and 90% of maximal concentric velocity), and two load distributions (narrow and wide). Three separate three-way repeated-measures ANOVAs were performed to assess the effect of load, velocity, and load distribution on REPfailure, RPEfatigue, and REPfatigue expressed as a percentage of REPfailure.ResultsREPfailure was affected by load (p<0.001), velocity (p<0.001), and distribution (p = 0.005). The interactions between load and velocity (p<0.001) and load and distribution (p = 0.004) showed a significant effect on REPfailure, whereas the interaction between velocity and distribution was not significant (p = 0.360). Overall, more REPfailure were performed using lower loads, higher velocities, and a wider distribution. RPEfatigue and REPfatigue were affected by load (p<0.001 and p = 0.007, respectively) and velocity (p<0.001 and p<0.001, respectively), and not by distribution (p = 0.510 and p = 0.571, respectively) or the two-way interaction effects. Overall, using higher loads yielded higher RPEfatigue but lower REPfatigue, while RPEfatigue and REPfatigue were higher when slower velocities were used.ConclusionThe current investigation shows that not only load but also velocity and barbell load distribution may influence bench press training volume and perceived exertion.

Project description:PurposeThis study aimed to examine the reliability and validity of load-velocity (L-V) relationship variables obtained through the 2-point method using different load combinations and velocity variables.MethodsTwenty men performed 2 identical sessions consisting of 2 countermovement jumps against 4 external loads (20 kg, 40 kg, 60 kg, and 80 kg) and a heavy squat against a load linked to a mean velocity (MV) of 0.55 m/s (load0.55). The L-V relationship variables (load-axis intercept (L0), velocity-axis intercept (v0), and area under the L-V relationship line (Aline)) were obtained using 3 velocity variables (MV, mean propulsive velocity (MPV), and peak velocity) by the multiple-point method including (20-40-60-80-load0.55) and excluding (20-40-60-80) the heavy squat, as well as from their respective 2-point methods (20-load0.55 and 20-80).ResultsThe L-V relationship variables were obtained with an acceptable reliability (coefficient of variation (CV) ≤ 7.30%; intra-class correlation coefficient ≥ 0.63). The reliability of L0 and v0 was comparable for both methods (CVratio (calculated as higher value/lower value): 1.11-1.12), but the multiple-point method provided Aline with a greater reliability (CVratio = 1.26). The use of a heavy squat provided the L-V relationship variables with a comparable or higher reliability than the use of a heavy countermovement jump load (CVratio: 1.06-1.19). The peak velocity provided the load-velocity relationship variables with the greatest reliability (CVratio: 1.15-1.86) followed by the MV (CVratio: 1.07-1.18), and finally the MPV. The 2-point methods only revealed an acceptable validity for the MV and MPV (effect size ≤ 0.19; Pearson's product-moment correlation coefficient ≥ 0.96; Lin's concordance correlation coefficient ≥ 0.94).ConclusionThe 2-point method obtained from a heavy squat load and MV or MPV is a quick, safe, and reliable procedure to evaluate the lower-body maximal neuromuscular capacities through the L-V relationship.

Project description:BackgroundHigh load (HL: > 85% of one repetition maximum (1RM)) squats with maximal intended velocity contractions (MIVC) combined with football sessions can be considered a relevant and time-efficient practice for maintaining and improving high velocity movements in football. Flywheel (FW) resistance exercise (RE) have recently emerged with promising results on physical parameters associated with football performance.MethodsIn this randomized controlled trial over 6 weeks, 38 recreationally active male football players randomly performed RE with MIVCs two times per week as either 1) FW squats (n = 13) or 2) barbell free weight (BFW) HL squats (n = 13), where a third group served as controls (n = 12). All three groups conducted 2-3 football sessions and one friendly match a week during the intervention period. Pre- to post changes in 10-m sprint, countermovement jump (CMJ) and 1RM partial squat were assessed with univariate analyses of variance.ResultsThe FW and BFW group equally improved their 10-m sprint time (2 and 2%, respectively, within group: both p < 0.001) and jump height (9 and 8%, respectively, within group: both p < 0.001), which was superior to the control group's change (between groups: both p < 0.001). The BFW group experienced a larger increase (46%) in maximal squat strength than the FW group (17%, between groups: p < 0.001), which both were higher than the control group's change (both p < 0.001).ConclusionSquats carried out with FWs or BFWs where both are performed with MIVCs and combined with football sessions, were equally effective in improving sprint time and jump height in football players. The BFW group experienced a more than two-fold larger increase in maximal partial squat strength than the FW group in maximal partial squat strength. This presents FW RE as an alternative to BFW HL RE for improving high velocity movements in football.Trial registrationClinicalTrials.gov Identifier: NCT04113031 (retrospectively registered, date: 02.10.2019).

Dataset Information

Assessment of the load-velocity profile in the free-weight prone bench pull exercise through different velocity variables and regression models.

Publications

Assessment of the load-velocity profile in the free-weight prone bench pull exercise through different velocity variables and regression models.

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