Validity of Various Methods for Determining Velocity, Force, and Power in the Back Squat

2017 ◽  
Vol 12 (9) ◽  
pp. 1170-1176 ◽  
Author(s):  
Harry G. Banyard ◽  
Ken Nosaka ◽  
Kimitake Sato ◽  
G. Gregory Haff
Keyword(s):  
Peak Power ◽  
Peak Velocity ◽  
Force Plate ◽  
Testing Device ◽  
Mean Power ◽  
Mean Velocity ◽  
Repetition Maximum ◽  
Back Squat ◽  
Free Weight ◽  
Criterion Variables

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.

scholarly journals Assessment of Back-Squat Performance at Submaximal Loads: Is the Reliability Affected by the Variable, Exercise Technique, or Repetition Criterion?

2021 ◽  
Vol 18 (9) ◽  
pp. 4626
Author(s):  
Alejandro Pérez-Castilla ◽  
Danica Janicijevic ◽  
Zeki Akyildiz ◽  
Deniz Senturk ◽  
Amador García-Ramos
Keyword(s):  
Peak Power ◽  
Peak Velocity ◽  
Average Score ◽  
Experimental Session ◽  
Mean Power ◽  
Mean Velocity ◽  
Repetition Maximum ◽  
Performance Variables ◽  
Back Squat ◽  
Squat Exercise

This study aimed to compare the between-session reliability of different performance variables during 2 variants of the Smith machine back-squat exercise. Twenty-six male wrestlers performed 5 testing sessions (a 1-repetition maximum [1RM] session, and 4 experimental sessions [2 with the pause and 2 with the rebound technique]). Each experimental session consisted of performing 3 repetitions against 5 loads (45–55–65–75–85% of the 1RM). Mean velocity (MV), mean power (MP), peak velocity (PV), and peak power (PP) variables were recorded by a linear position transducer (GymAware PowerTool). The best and average scores of the 3 repetitions were considered for statistical analyses. The coefficient of variation (CV) ranged from 3.89% (best PV score at 55% 1 RM using the pause technique) to 10.29% (average PP score at 85% 1 RM using the rebound technique). PP showed a lower reliability than MV, MP, and PV (CVratio ≥ 1.26). The reliability was comparable between the exercise techniques (CVratio = 1.08) and between the best and average scores (CVratio = 1.04). These results discourage the use of PP to assess back-squat performance at submaximal loads. The remaining variables (MV, MP, or PV), exercise techniques (pause or rebound), and repetition criteria (best score or average score) can be indistinctly used due to their acceptable and comparable reliability.

Effectiveness of Accentuated Eccentric Loading: Contingent on Concentric Load

2021 ◽  
Vol 16 (1) ◽  
pp. 66-72
Author(s):  
Justin J. Merrigan ◽  
James J. Tufano ◽  
Michael Falzone ◽  
Margaret T. Jones
Keyword(s):  
Peak Power ◽  
Performance Enhancement ◽  
Force Plate ◽  
Relative Difference ◽  
Peak Force ◽  
Acute Effects ◽  
Mean Power ◽  
Mean Velocity ◽  
Eccentric Load ◽  
Back Squat

Purpose: To identify acute effects of a single accentuated eccentric loading (AEL) repetition on subsequent back-squat kinetics and kinematics with different concentric loads. Methods: Resistance-trained men (N = 21) participated in a counterbalanced crossover design and completed 4 protocols (sets × repetitions at eccentric/concentric) as follows: AEL65, 3 × 5 at 120%/65% 1-repetition maximum (1-RM); AEL80, 3 × 3 at 120%/80% 1-RM; TRA65, 3 × 5 at 65%/65% 1-RM; and TRA80, 3 × 3 at 80%/80% 1-RM. During AEL, weight releasers disengaged from the barbell after the eccentric phase of the first repetition and remained off for the remaining repetitions. All repetitions were performed on a force plate with linear position transducers attached to the barbell, from which eccentric and concentric peak and mean velocity, force, and power were derived. Results: Eccentric peak velocity (−0.076 [0.124] m·s−1; P = .01), concentric peak force (187.8 [284.4] N; P = .01), eccentric mean power (−145.2 [62.0] W; P = .03), and eccentric peak power (−328.6 [93.7] W; P < .01) during AEL65 were significantly greater than TRA65. When collapsed across repetitions, AEL65 resulted in slower eccentric velocity and power during repetition 1 but faster eccentric and concentric velocity and power in subsequent repetitions (P ≤ .04). When comparing AEL80 with TRA80, concentric peak force (133.8 [56.9] N; P = .03), eccentric mean power (−83.57 [38.0] W; P = .04), and eccentric peak power (−242.84 [67.3] W; P < .01) were enhanced. Conclusions: Including a single supramaximal eccentric phase of 120% 1-RM increased subsequent velocity and power with concentric loads of 65% 1-RM, but not 80% 1-RM. Therefore, AEL is sensitive to the magnitude of concentric loads, which requires a large relative difference to the eccentric load, and weight releasers may not need to be reloaded to induce performance enhancement.

Reducing the Loss of Velocity and Power in Women Athletes via Rest Redistribution

2020 ◽  
Vol 15 (2) ◽  
pp. 255-261 ◽  
Author(s):  
Justin J. Merrigan ◽  
James J. Tufano ◽  
Jonathan M. Oliver ◽  
Jason B. White ◽  
Jennifer B. Fields ◽  
...  
Keyword(s):  
Confidence Interval ◽  
Repeated Measures ◽  
Peak Power ◽  
Force Plate ◽  
Mean Power ◽  
Mean Velocity ◽  
Back Squat ◽  
Percentage Loss ◽  
Repeated Measures Analysis ◽  
Training History

Purpose: To examine rest redistribution (RR) effects on back squat kinetics and kinematics in resistance-trained women. Methods: Twelve women from strength and college sports (5.0 [2.2] y training history) participated in the randomized crossover design study with 72 hours between sessions (3 total). Participants completed 4 sets of 10 repetitions using traditional sets (120-s interset rest) and RR (30-s intraset rest in the middle of each set; 90-s interset rest) with 70% of their 1-repetition maximum. Kinetics and kinematics were sampled via force plate and 4 linear position transducers. The greatest value of repetitions 1 to 3 (peak repetition) was used to calculate percentage loss, [(repetition 10–peak repetition)/(peak repetition) × 100], and maintenance, {100–[(set mean–peak repetition)/(peak repetition)] × 100}, of velocity and power for each set. Repeated-measures analysis of variance was used for analyses (P < .05). Results: Mean and peak force did not differ between conditions. A condition × repetition interaction existed for peak power (P = .049) but not for peak velocity (P = .110). Peak power was greater in repetitions 7 to 9 (P < .05; d = 1.12–1.27) during RR. The percentage loss of velocity (95% confidence interval, –0.22% to –7.22%; P = .039) and power (95% confidence interval, –1.53% to –7.87%; P = .008) were reduced in RR. Mean velocity maintenance of sets 3 (P = .036; d = 1.90) and 4 (P = .015; d = 2.30) and mean power maintenance of set 4 (P = .006; d = 2.65) were greater in RR. Conclusion: By redistributing a portion of long interset rest into the middle of a set, velocity and power were better maintained. Therefore, redistributing rest may be beneficial for reducing fatigue in resistance-trained women.

The Reliability of Individualized Load–Velocity Profiles

2018 ◽  
Vol 13 (6) ◽  
pp. 763-769 ◽  
Author(s):  
Harry G. Banyard ◽  
Kazunori Nosaka ◽  
Alex D. Vernon ◽  
G. Gregory Haff
Keyword(s):  
Linear Regression ◽  
Peak Velocity ◽  
Intraclass Correlation ◽  
Velocity Profiles ◽  
Mean Velocity ◽  
Movement Velocity ◽  
Repetition Maximum ◽  
Back Squat ◽  
Free Weight ◽  
Order Polynomial

Purpose: To examine the reliability of peak velocity (PV), mean propulsive velocity (MPV), and mean velocity (MV) in the development of load–velocity profiles (LVP) in the full-depth free-weight back squat performed with maximal concentric effort. Methods: Eighteen resistance-trained men performed a baseline 1-repetition maximum (1-RM) back-squat trial and 3 subsequent 1-RM trials used for reliability analyses, with 48-h intervals between trials. 1-RM trials comprised lifts from 6 relative loads including 20%, 40%, 60%, 80%, 90%, and 100% 1-RM. Individualized LVPs for PV, MPV, or MV were derived from loads that were highly reliable based on the following criteria: intraclass correlation coefficient (ICC) >.70, coefficient of variation (CV) ≤10%, and Cohen d effect size (ES) <0.60. Results: PV was highly reliable at all 6 loads. MPV and MV were highly reliable at 20%, 40%, 60%, 80%, and 90% but not 100% 1-RM (MPV: ICC = .66, CV = 18.0%, ES = 0.10, SEM = 0.04 m·s−1; MV: ICC = .55, CV = 19.4%, ES = 0.08, SEM = 0.04 m·s−1). When considering the reliable ranges, almost perfect correlations were observed for LVPs derived from PV20–100% (r = .91–.93), MPV20–90% (r = .92–.94), and MV20–90% (r = .94–.95). Furthermore, the LVPs were not significantly different (P > .05) between trials or movement velocities or between linear regression versus 2nd-order polynomial fits. Conclusions: PV20–100%, MPV20–90%, and MV20–90% are reliable and can be utilized to develop LVPs using linear regression. Conceptually, LVPs can be used to monitor changes in movement velocity and employed as a method for adjusting sessional training loads according to daily readiness.

scholarly journals The Reliability and Validity of Current Technologies for Measuring Barbell Velocity in the Free-Weight Back Squat and Power Clean

Sports ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 94
Author(s):  
Steve W. Thompson ◽  
David Rogerson ◽  
Harry F. Dorrell ◽  
Alan Ruddock ◽  
Andrew Barnes
Keyword(s):  
Peak Velocity ◽  
Reliability And Validity ◽  
Systematic Bias ◽  
Mean Velocity ◽  
Validity Data ◽  
Back Squat ◽  
Free Weight ◽  
Device Reliability ◽  
Measurement Units ◽  
Power Clean

This study investigated the inter-day and intra-device reliability, and criterion validity of six devices for measuring barbell velocity in the free-weight back squat and power clean. In total, 10 competitive weightlifters completed an initial one repetition maximum (1RM) assessment followed by three load-velocity profiles (40–100% 1RM) in both exercises on four separate occasions. Mean and peak velocity was measured simultaneously on each device and compared to 3D motion capture for all repetitions. Reliability was assessed via coefficient of variation (CV) and typical error (TE). Least products regression (LPR) (R2) and limits of agreement (LOA) assessed the validity of the devices. The Gymaware was the most reliable for both exercises (CV < 10%; TE < 0.11 m·s−1, except 100% 1RM (mean velocity) and 90‒100% 1RM (peak velocity)), with MyLift and PUSH following a similar trend. Poorer reliability was observed for Beast Sensor and Bar Sensei (CV = 5.1–119.9%; TE = 0.08–0.48 m·s−1). The Gymaware was the most valid device, with small systematic bias and no proportional or fixed bias evident across both exercises (R2 > 0.42–0.99 LOA = −0.03–0.03 m·s−1). Comparable validity data was observed for MyLift in the back squat. Both PUSH devices produced some fixed and proportional bias, with Beast Sensor and Bar Sensei being the least valid devices across both exercises (R2 > 0.00–0.96, LOA = −0.36–0.46 m·s−1). Linear position transducers and smartphone applications could be used to obtain velocity-based data, with inertial measurement units demonstrating poorer reliability and validity.

Cluster Sets: Permitting Greater Mechanical Stress Without Decreasing Relative Velocity

2017 ◽  
Vol 12 (4) ◽  
pp. 463-469 ◽  
Author(s):  
James J. Tufano ◽  
Jenny A. Conlon ◽  
Sophia Nimphius ◽  
Lee E. Brown ◽  
Harry G. Banyard ◽  
...  
Keyword(s):  
Repeated Measures ◽  
Peak Velocity ◽  
Training Load ◽  
Mean Power ◽  
Mean Velocity ◽  
External Work ◽  
Back Squat ◽  
Mechanical Power Output ◽  
Cluster Sets ◽  
External Loads

Purpose:To determine the effects of intraset rest frequency and training load on muscle time under tension, external work, and external mechanical power output during back-squat protocols with similar changes in velocity.Methods:Twelve strength-trained men (26.0 ± 4.2 y, 83.1 ± 8.8 kg, 1.75 ± 0.06 m, 1.88:0.19 one-repetition-maximum [1RM] body mass) performed 3 sets of 12 back squats using 3 different set structures: traditional sets with 60% 1RM (TS), cluster sets of 4 with 75% 1RM (CS4), and cluster sets of 2 with 80% 1RM (CS2). Repeated-measures ANOVAs were used to determine differences in peak force (PF), mean force (MF), peak velocity (PV), mean velocity (MV), peak power (PP), mean power (MP), total work (TW), total time under tension (TUT), percentage mean velocity loss (%MVL), and percentage peak velocity loss (%PVL) between protocols.Results:Compared with TS and CS4, CS2 resulted in greater MF, TW, and TUT in addition to less MV, PV, and MP. Similarly, CS4 resulted in greater MF, TW, and TUT in addition to less MV, PV, and MP than TS did. There were no differences between protocols for %MVL, %PVL, PF, or PP.Conclusions:These data show that the intraset rest provided in CS4 and CS2 allowed for greater external loads than with TS, increasing TW and TUT while resulting in similar PP and %VL. Therefore, cluster-set structures may function as an alternative method to traditional strength- or hypertrophy-oriented training by increasing training load without increasing %VL or decreasing PP.

Power– and velocity–load relationships to improve resistance exercise performance

2018 ◽  
Vol 232 (4) ◽  
pp. 349-359 ◽  
Author(s):  
Manuel V Garnacho-Castaño ◽  
Arturo Muñoz-González ◽  
María A Garnacho-Castaño ◽  
José L Maté-Muñoz
Keyword(s):  
Power Output ◽  
Peak Power ◽  
Bench Press ◽  
Peak Velocity ◽  
Peak Power Output ◽  
Mean Power ◽  
Mean Velocity ◽  
Maximal Power Output ◽  
Power Load ◽  
The Military

Knowledge of the power– and velocity–load relationships is a key factor to guide loads during resistance training and optimize sports performance. This study compares mean velocity–, peak velocity– and power–load relationships, and determines the load which elicits maximal power output in the military press and bench press. Fifty-seven healthy, active men were randomly assigned to a bench press (n = 28) or military press (n = 29) group. In separate test sessions, concentric-only or eccentric-concentric sequences of each exercise were performed in random order as incremental isoinertial load tests. Both mean velocity and peak velocity were highly related with the load lifted (% 1RM) in both bench press and military press (mean velocity: R2 = 0.94 and 0.95; peak velocity: R2 = 0.93 and 0.93, respectively). The loads maximizing mean power and peak power output were similar for the eccentric-concentric versus concentric sequences in bench press and military press. The loads maximizing mean power and peak power were between 54% and 57.5% 1RM for the bench press and 59.8%–63.1% 1RM for the military press. For the bench press, no significant differences were observed in mean power from 30% to 80% 1RM and peak power from 30% to 95% 1RM. For the military press, no significant differences were observed in mean power from 40% to 80% 1RM and peak power from 30% to 90%/95% 1RM. The close relationship detected between mean velocity or peak velocity and load means that the % 1RM can be estimated according to mean velocity and peak velocity. In both exercises, a broad range of relative intensities could be used at which power output is not significantly different than that at maximized power output (mean = 30%/40%–80% 1RM; peak = 30%–90%/95%). Mean velocity lower than approximately 0.33 m s−1 for bench press and 0.4 m s−1 for military press, as well as peak velocity lower than approximately 0.4 m s−1 for bench press and 0.5 m s−1 for military press do not optimize power output responses. The eccentric action was a determining factor for increasing power output only in bench press.

Maintenance of Velocity and Power With Cluster Sets During High-Volume Back Squats

2016 ◽  
Vol 11 (7) ◽  
pp. 885-892 ◽  
Author(s):  
James J. Tufano ◽  
Jenny A. Conlon ◽  
Sophia Nimphius ◽  
Lee E. Brown ◽  
Laurent B. Seitz ◽  
...  
Keyword(s):  
Peak Power ◽  
Peak Velocity ◽  
High Volume ◽  
Effect Sizes ◽  
Maximal Velocity ◽  
Mean Power ◽  
Mean Velocity ◽  
Cluster Set ◽  
Cluster Sets ◽  
Force Velocity

Purpose:To compare the effects of a traditional set structure and 2 cluster set structures on force, velocity, and power during back squats in strength-trained men.Methods:Twelve men (25.8 ± 5.1 y, 1.74 ± 0.07 m, 79.3 ± 8.2 kg) performed 3 sets of 12 repetitions at 60% of 1-repetition maximum using 3 different set structures: traditional sets (TS), cluster sets of 4 (CS4), and cluster sets of 2 (CS2).Results:When averaged across all repetitions, peak velocity (PV), mean velocity (MV), peak power (PP), and mean power (MP) were greater in CS2 and CS4 than in TS (P < .01), with CS2 also resulting in greater values than CS4 (P < .02). When examining individual sets within each set structure, PV, MV, PP, and MP decreased during the course of TS (effect sizes 0.28–0.99), whereas no decreases were noted during CS2 (effect sizes 0.00–0.13) or CS4 (effect sizes 0.00–0.29).Conclusions:These results demonstrate that CS structures maintain velocity and power, whereas TS structures do not. Furthermore, increasing the frequency of intraset rest intervals in CS structures maximizes this effect and should be used if maximal velocity is to be maintained during training.

scholarly journals Validation of Inertial Sensor to Measure Barbell Kinematics across a Spectrum of Loading Conditions

Sports ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 93
Author(s):  
John C. Abbott ◽  
John P. Wagle ◽  
Kimitake Sato ◽  
Keith Painter ◽  
Thaddeus J. Light ◽  
...  
Keyword(s):  
Effect Size ◽  
Peak Velocity ◽  
Inertial Sensor ◽  
Measurement Unit ◽  
Mean Velocity ◽  
Back Squat ◽  
Pearson Correlations ◽  
Internal Error ◽  
3D Motion Capture ◽  
Level Of Agreement

The aim of this study was to evaluate the level of agreement in measuring back squat kinematics between an inertial measurement unit (IMU) and a 3D motion capture system (3DMOCAP). Kinematic variables included concentric peak velocity (CPV), concentric mean velocity (CMV), eccentric peak velocity (EPV), eccentric mean velocity (EMV), mean propulsive velocity (MPV), and POP-100: a proprietary variable. Sixteen resistance-trained males performed an incrementally loaded one repetition maximum (1RM) squat protocol. A series of Pearson correlations, 2 × 4 RM ANOVA, Cohen’s d effect size differences, coefficient of variation (CV), and standard error of the estimate (SEE) were calculated. A large relationship existed for all variables between devices (r = 0.78–0.95). Between-device agreement for CPV worsened beyond 60% 1RM. The remaining variables were in agreement between devices with trivial effect size differences and similar CV magnitudes. These results support the use of the IMU, regardless of relative intensity, when measuring EMV, EPV, MPV, and POP-100. However, practitioners should carefully select kinematic variables of interest when using the present IMU device for velocity-based training (VBT), as certain measurements (e.g., CMV, CPV) do not possess practically acceptable reliability or accuracy. Finally, the IMU device exhibited considerable practical data collection concerns, as one participant was completely excluded and 13% of the remaining attempts displayed obvious internal error.

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

2020 ◽  
Vol 17 (18) ◽  
pp. 6509
Author(s):  
Madison Pearson ◽  
Amador García-Ramos ◽  
Matthew Morrison ◽  
Carlos Ramirez-Lopez ◽  
Nicholas Dalton-Barron ◽  
...  
Keyword(s):  
Resistance Training ◽  
Coefficient Of Variation ◽  
External Load ◽  
Relative Velocity ◽  
Peak Power ◽  
Crossover Design ◽  
Professional Athletes ◽  
Back Squat ◽  
Free Weight

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.

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