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

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.

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.


Sports ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 94
Author(s):  
Steve W. Thompson ◽  
David Rogerson ◽  
Harry F. Dorrell ◽  
Alan Ruddock ◽  
Andrew Barnes

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.


2018 ◽  
Vol 13 (5) ◽  
pp. 737-742 ◽  
Author(s):  
Amador García-Ramos ◽  
Alejandro Pérez-Castilla ◽  
Fernando Martín

The objective of this study was to explore the reliability and concurrent validity of the Velowin optoelectronic system to measure movement velocity during the free-weight back squat exercise. Thirty-one men (age = 27.5 ± 3.2 years; body height = 1.76 ± 0.15 m; body mass: 78.3 ± 7.6 kg) were evaluated in a single session against five different loads (20, 40, 50, 60 and 70 kg) and three velocity variables (mean velocity, mean propulsive velocity and maximum velocity) were recorded simultaneously by a linear velocity transducer (T-Force; gold-standard) and a camera-based optoelectronic system (Velowin). The main findings revealed that (1) the three velocity variables were determined with a high and comparable reliability by both the T-Force and Velowin systems (median coefficient of variation of the five loads: T-Force: mean velocity = 4.25%, mean propulsive velocity = 4.49% and maximum velocity = 3.45%; Velowin: mean velocity = 4.29%, mean propulsive velocity = 4.60% and maximum velocity = 4.44%), (2) the maximum velocity was the most reliable variable when obtained by the T-force ( p < 0.05), but no significant differences in the reliability of the variables were observed for the Velowin ( p > 0.05) and (3) high correlations were observed for the values of mean velocity ( r = 0.976), mean propulsive velocity ( r = 0.965) and maximum velocity ( r = 0.977) between the T-Force and Velowin systems. Collectively, these results support the Velowin as a reliable and valid system for the measurement of movement velocity during the free-weight back squat exercise.


Author(s):  
Steve W. Thompson ◽  
David Rogerson ◽  
Alan Ruddock ◽  
Harry G. Banyard ◽  
Andrew Barnes

Purpose: This study compared pooled against individualized load–velocity profiles (LVPs) in the free-weight back squat and power clean. Methods: A total of 10 competitive weightlifters completed baseline 1-repetition maximum assessments in the back squat and power clean. Three incremental LVPs were completed, separated by 48 to 72 hours. Mean and peak velocity were measured via a linear-position transducer (GymAware). Linear and nonlinear (second-order polynomial) regression models were applied to all pooled and individualized LVP data. A combination of coefficient of variation (CV), intraclass correlation coefficient, typical error of measurement, and limits of agreement assessed between-subject variability and within-subject reliability. Acceptable reliability was defined a priori as intraclass correlation coefficient > .7 and CV < 10%. Results: Very high to practically perfect inverse relationships were evident in the back squat (r = .83–.96) and power clean (r = .83–.89) for both regression models; however, stronger correlations were observed in the individualized LVPs for both exercises (r = .85–.99). Between-subject variability was moderate to large across all relative loads in the back squat (CV = 8.2%–27.8%) but smaller in the power clean (CV = 4.6%–8.5%). The power clean met our criteria for acceptable reliability across all relative loads; however, the back squat revealed large CVs in loads ≥90% of 1-repetition maximum (13.1%–20.5%). Conclusions: Evidently, load–velocity characteristics are highly individualized, with acceptable levels of reliability observed in the power clean but not in the back squat (≥90% of 1-repetition maximum). If practitioners want to adopt load–velocity profiling as part of their testing and monitoring procedures, an individualized LVP should be utilized over pooled LVPs.


Author(s):  
Alejandro Pérez-Castilla ◽  
Danica Janicijevic ◽  
Zeki Akyildiz ◽  
Deniz Senturk ◽  
Amador García-Ramos

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.


2021 ◽  
Vol 6 (2) ◽  
pp. 32
Author(s):  
Conor McNeill ◽  
C. Martyn Beaven ◽  
Daniel T. McMaster ◽  
Nicholas Gill

Eccentric strength characteristics have been shown to be important factors in physical performance. Many eccentric tests have been performed in isolation or with supramaximal loading. The purpose of this study was to investigate within- and between- session reliability of an incremental eccentric back squat protocol. Force plates and a linear position transducer captured force-time-displacement data across six loading conditions, separated by at least seven days. The reliability of eccentric specific measurements was assessed using coefficient of variation (CV), change in mean, and intraclass correlation coefficient (ICC). Eccentric peak force demonstrated good ICC (≥0.82) and TE (≤7.3%) for each load. Variables based on mean data were generally less reliable (e.g., mean rate of force development, mean force, mean velocity). This novel protocol meets acceptable levels of reliability for different eccentric-specific measurements although the extent to which these variables affect dynamic performance requires further research.


Author(s):  
Mike Siekman ◽  
David Helmer ◽  
Wontae Hwang ◽  
Gregory Laskowski ◽  
Ek Tsoon Tan ◽  
...  

RANS and time averaged URANS simulations of a pin bank are compared quantitatively and qualitatively to full 3D mean velocity field data obtained using magnetic resonance velocimetry (MRV). The ability of the CFD to match MRV velocity profiles through the pin bank is evaluated using the SST turbulence model. Quantitative comparisons of the velocity profiles showed an overprediction of peak velocity by the CFD at the first pin rows, and a smaller oscillatory error that diminishes as it moves through the pins, resulting in better matching towards the exit.


Sports ◽  
2019 ◽  
Vol 7 (9) ◽  
pp. 207 ◽  
Author(s):  
Roland van den Tillaar ◽  
Nick Ball

Background: The aim of this study was to compare the validity and reliability of a PUSH band device with a linear encoder to measure movement velocity with different loads during the push-up and bench press exercises. Methods: Twenty resistance-trained athletes performed push-up and bench press exercises with four different loads: without weight vest, 10-20-30 kg weight vest, bench press: 50–82% of their assumed 1 repetition maximum (1 RM) in steps of 10 kg. A linear encoder (Musclelab) and the PUSH band measured mean and peak velocity during both exercises. Several statistical analyses were used to investigate the validity and reliability of the PUSH band with the linear encoder. Results: The main findings of this study demonstrated only moderate associations between the PUSH band and linear encoder for mean velocity (r = 0.62, 0.70) and peak velocity (r = 0.46, 0.49) for both exercises. Furthermore, a good level of agreement (peak velocity: ICC = 0.60, 0.64; mean velocity: ICC = 0.77, 0.78) was observed between the two measurement devices. However, a significant bias was found with lower velocity values measured with the PUSH band in both exercises. In the push-up, both the linear encoder and PUSH band were deemed very reliable (ICC > 0.98; the coefficient of variation (CV): 5.9–7.3%). Bench press reliability decreased for the PUSH band (ICC < 0.95), and the coefficient of variance increased to (12.8–13.3%) for the velocity measures. Calculated 1 RM with the two devices was the same for the push-up, while in bench press the PUSH band under-estimated the 1 RM by 14 kg compared to the linear encoder. Conclusions: It was concluded that the PUSH band will show decreased reliability from velocity measures in a bench press exercise and underestimate load-velocity based 1 RM predictions. For training, the PUSH band can be used during push-ups, however caution is suggested when using the device for the purposes of feedback in bench press at increasing loads.


Sports ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 93
Author(s):  
John C. Abbott ◽  
John P. Wagle ◽  
Kimitake Sato ◽  
Keith Painter ◽  
Thaddeus J. Light ◽  
...  

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.


2017 ◽  
Vol 12 (4) ◽  
pp. 463-469 ◽  
Author(s):  
James J. Tufano ◽  
Jenny A. Conlon ◽  
Sophia Nimphius ◽  
Lee E. Brown ◽  
Harry G. Banyard ◽  
...  

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.


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