scholarly journals Velocity Loss Thresholds Reliably Control Kinetic and Kinematic Outputs during Free Weight Resistance Training

Author(s):  
Madison Pearson ◽  
Amador García-Ramos ◽  
Matthew Morrison ◽  
Carlos Ramirez-Lopez ◽  
Nicholas Dalton-Barron ◽  
...  

Exercise velocity and relative velocity loss thresholds (VLTs) are commonly used in velocity-based resistance training. This study aims to quantify the between-day reliability of 10%, 20%, and 30% VLTs on kinetic and kinematic outputs, changes in external load, and repetition characteristics in well-trained athletes. Using a repeated, counter-balanced crossover design, twelve semi-professional athletes completed five sets of the back squat with an external load corresponding to a mean concentric velocity of ~0.70 m·s−1 and a VLT applied. The testing sessions were repeated after four weeks of unstructured training to assess the long-term reliability of each VLT. A coefficient of variation (CV) <10% was used to classify outputs as reliable. Kinetic and kinematic outputs and external load were largely reliable, with only peak power during sets 2–5 within the 10% VLT condition demonstrating a CV >10% (CV: 11.14–14.92%). Alternatively, the repetitions completed within each set showed large variation (CV: 18.92–67.49%). These findings demonstrate that by utilizing VLTs, kinetic and kinematic outputs can be prescribed and replicated across training mesocycles. Thus, for practitioners wishing to reliably control the kinetic and kinematic stimulus that is being applied to their athletes, it is advised that a velocity-based approach is used.

2020 ◽  
Vol 15 (2) ◽  
pp. 180-188 ◽  
Author(s):  
Jonathon Weakley ◽  
Carlos Ramirez-Lopez ◽  
Shaun McLaren ◽  
Nick Dalton-Barron ◽  
Dan Weaving ◽  
...  

Purpose: Prescribing resistance training using velocity loss thresholds can enhance exercise quality by mitigating neuromuscular fatigue. As little is known regarding performance during these protocols, we aimed to assess the effects of 10%, 20%, and 30% velocity loss thresholds on kinetic, kinematic, and repetition characteristics in the free-weight back squat. Methods: Using a randomized crossover design, 16 resistance-trained men were recruited to complete 5 sets of the barbell back squat. Lifting load corresponded to a mean concentric velocity (MV) of ∼0.70 m·s−1 (115 [22] kg). Repetitions were performed until a 10%, 20%, or 30% MV loss was attained. Results: Set MV and power output were substantially higher in the 10% protocol (0.66 m·s−1 and 1341 W, respectively), followed by the 20% (0.62 m·s−1 and 1246 W) and 30% protocols (0.59 m·s−1 and 1179 W). There were no substantial changes in MV (−0.01 to −0.02 m·s−1) or power output (−14 to −55 W) across the 5 sets for all protocols, and individual differences in these changes were typically trivial to small. Mean set repetitions were substantially higher in the 30% protocol (7.8), followed by the 20% (6.4) and 10% protocols (4.2). There were small to moderate reductions in repetitions across the 5 sets during all protocols (−39%, −31%, −19%, respectively), and individual differences in these changes were small to very large. Conclusions: Velocity training prescription maintains kinetic and kinematic output across multiple sets of the back squat, with repetition ranges being highly variable. Our findings, therefore, challenge traditional resistance training paradigms (repetition based) and add support to a velocity-based approach.


Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7156
Author(s):  
Borja Sañudo ◽  
Moisés de Hoyo ◽  
G Gregory Haff ◽  
Alejandro Muñoz-López

This study aimed to compare the post-activation potentiation performance enhancement (PAPE) response to the acute inertial flywheel (FW) and free weight resistance training (TRA) on subsequent countermovement jump (CMJ) and sprint performance (10 m sprint). This study used a randomized crossover design including twenty-eight healthy males that were divided into strong (relative one-repetition maximum (1RM) back squat > 2.0 × body mass) and weak (relative 1RM back squat < 2.0 × body mass) groups. All participants performed the following: (a) three reps at 90% of their 1RM back squat (TRA) and (b) three reps on an inertial FW (plus one repetition to initiate flywheel movement) with an intensity that generated a mean propulsive velocity equal to that achieved with 90% of the 1RM back squat. Before and after the conditioning activity, participants performed two CMJs and two 10 m sprints. Within-group analyses showed significantly greater CMJ (d > 0.9, p < 0.001) and sprint performance (d > 0.5, p < 0.05) in the FW and the TRA group. Between-group analysis showed that sprint changes were significantly greater in the FW-strong group when compared with the TRA (F1,18 = 5.11, p = 0.036, η2p = 0.221—large) group. These results suggest that using a squat activation protocol on a FW may lead to an acute positive effect on jump and sprint performance, especially in stronger individuals.


2021 ◽  
Vol 78 (1) ◽  
pp. 263-269
Author(s):  
Michael H. Haischer ◽  
Daniel M. Cooke ◽  
Joseph P. Carzoli ◽  
Trevor K. Johnson ◽  
Amber M. Shipherd ◽  
...  

Abstract Grit has been previously presented as a personality trait that reflects an individual’s perseverance of effort and consistency of interest for achieving their long-term goals. In resistance training this could mean that a “grittier” individual may perform more repetitions at a given intensity as they are better able to overcome metabolic and neuromuscular fatigue. Thus, the purpose of this study was to examine if grit was related to back squat muscular endurance performance. Fifty-eight resistance-trained males and females volunteered for participation (age = 23±3 yrs; body height = 172.53 ± 8.64 cm; body mass = 80.64 ± 6.49 kg). The grit of each participant was assessed via the Short Grit Scale (GRIT-S), and muscular endurance performance was tested via completion of a back squat set to volitional failure at 70% of the participant’s one-repetition maximum. Spearman rho or Pearson’s correlations, depending on normality, were used with 1000 bootstrapped replicate samples and revealed no relationship between GRIT-S scores (3.78 ± 0.52) and repetitions performed (14 ± 4) in a combined cohort of all 58 individuals (ρ = -0.051), males only (r = 0.057) or females only (ρ = -0.441). Supplementary investigation of the data also showed that the five “best” performers (i.e. the five individuals who performed the most repetitions) tended to have lower GRIT-S scores than the five “worst” performers. The results of the current study suggest that the GRIT-S has limited value in the context of muscular endurance performance. The skewed range of GRIT-S scores (2.75-5.0) observed in this investigation, also highlights the potential for social desirability to bias one’s self-perception of grit.


2017 ◽  
Vol 12 (9) ◽  
pp. 1170-1176 ◽  
Author(s):  
Harry G. Banyard ◽  
Ken Nosaka ◽  
Kimitake Sato ◽  
G. Gregory Haff

Purpose:To examine the validity of 2 kinematic systems for assessing mean velocity (MV), peak velocity (PV), mean force (MF), peak force (PF), mean power (MP), and peak power (PP) during the full-depth free-weight back squat performed with maximal concentric effort. Methods:Ten strength-trained men (26.1 ± 3.0 y, 1.81 ± 0.07 m, 82.0 ± 10.6 kg) performed three 1-repetition-maximum (1RM) trials on 3 separate days, encompassing lifts performed at 6 relative intensities including 20%, 40%, 60%, 80%, 90%, and 100% of 1RM. Each repetition was simultaneously recorded by a PUSH band and commercial linear position transducer (LPT) (GymAware [GYM]) and compared with measurements collected by a laboratory-based testing device consisting of 4 LPTs and a force plate. Results:Trials 2 and 3 were used for validity analyses. Combining all 120 repetitions indicated that the GYM was highly valid for assessing all criterion variables while the PUSH was only highly valid for estimations of PF (r = .94, CV = 5.4%, ES = 0.28, SEE = 135.5 N). At each relative intensity, the GYM was highly valid for assessing all criterion variables except for PP at 20% (ES = 0.81) and 40% (ES = 0.67) of 1RM. Moreover, the PUSH was only able to accurately estimate PF across all relative intensities (r = .92–.98, CV = 4.0–8.3%, ES = 0.04–0.26, SEE = 79.8–213.1 N). Conclusions:PUSH accuracy for determining MV, PV, MF, MP, and PP across all 6 relative intensities was questionable for the back squat, yet the GYM was highly valid at assessing all criterion variables, with some caution given to estimations of MP and PP performed at lighter loads.


1994 ◽  
Vol 26 (Supplement) ◽  
pp. S90
Author(s):  
N. McCartney ◽  
A. L. Hicks ◽  
J. Martin

2016 ◽  
Vol 47 (5) ◽  
pp. 843-855 ◽  
Author(s):  
Paulo Gentil ◽  
James Fisher ◽  
James Steele

1997 ◽  
Vol 47 (3) ◽  
pp. 385-398 ◽  
Author(s):  
Joseph J. Plaud ◽  
George A. Gaither ◽  
Susan Amato Henderson ◽  
Mary K. Devitt

Author(s):  
Paulo Eduardo Carnaval Pereira da Rocha ◽  
Vladimir Schuindt da Silva ◽  
Luiz Antonio Bastos Camacho ◽  
Ana Glória Godoi Vasconcelos

Studies assessed the beneficial effects of aerobic exercise on blood pressure (BP); however, few studies have evaluated the effects of long-term resistance training on variations of this response. The aim of the study was to verify through a systematic review, the long-term effect of resistance training on BP. Searches were made on Medline through Pubmed, Science Direct, Scopus, Web of Science and Lilacs databases. Overall, 751 articles were found, of which 22 were further analyzed. The analysis followed the PRISMA checklist (Statement for Reporting Systematic Reviews and Meta-Analyses of Studies) and was divided according to two resistance training models: traditional resistance training (TRT), resistance training alone; or combined resistance training (CRT), resistance training associated with aerobic exercise. Greater BP reductions occurred for CRT compared to TRT. However, further studies are needed to better explicit the resistance training variables (number of exercises, repetitions, number of sets, intervals, speed of execution and load intensity), in order to identify the best training model and improve the methodological quality of experiments in an attempt to reduce the risk of bias.


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