Validity and Reliability of a Wearable Inertial Sensor to Measure Velocity and Power in the Back Squat and Bench Press

Validity of a Smartphone App Using Artificial Intelligence for the Real-Time Measurement of Barbell Velocity in the Bench Press Exercise

ABSTRACT

Balsalobre-Fernández, C, Xu, J, Jarvis, P, Thompson, S, Tannion, K, and Bishop, C. Validity of a smartphone app using artificial intelligence for the real-time measurement of barbell velocity in the bench press exercise. J Strength Cond Res 37(12): e640-e645, 2023-The purpose of this study was to explore the validity and within-session reliability of the newly developed My Jump Lab application (app), which uses artificial intelligence techniques to monitor barbell velocity in real time. Twenty-seven sport science students performed 5 repetitions at 50 and 75% of their self-reported bench press 1 repetition maximum (1RM) during a single testing session, whereas barbell velocity was concurrently measured using the app (installed on an iPhone 12 Pro) and the GymAware linear position transducer (LPT). A very high correlation was observed between devices at each loading condition (50% 1RM: r = 0.90 [0.82-0.97]; 75% 1RM: r = 0.92 [0.86-0.98]). Results showed trivial differences between the app and LPT at both 50% 1RM (g = -0.06) and 75% 1RM (g = -0.12). Bland-Altman analysis showed a bias estimate of -0.010 m·s-1 and -0.026 m·s-1 for the 50 and 75% 1RM, respectively. Finally, similar levels of reliability, as revealed by the coefficient of variation, were observed for both devices (50% 1RM: LPT = 6.52%, app = 8.17%; 75% 1RM: LPT = 12.10%, app = 13.55%). Collectively, the findings of this study support the use of My Jump Lab for the measurement of real-time barbell velocity in the bench press exercise.

Development and Evaluation of a Full-Waveform Resistance Training Monitoring System Based on a Linear Position Transducer

Recent advances in training monitoring are centered on the statistical indicators of the concentric phase of the movement. However, those studies lack consideration of the integrity of the movement. Moreover, training performance evaluation needs valid data on the movement. Thus, this study presents a full-waveform resistance training monitoring system (FRTMS) as a whole-movement-process monitoring solution to acquire and analyze the full-waveform data of resistance training. The FRTMS includes a portable data acquisition device and a data processing and visualization software platform. The data acquisition device monitors the barbell's movement data. The software platform guides users through the acquisition of training parameters and provides feedback on the training result variables. To validate the FRTMS, we compared the simultaneous measurements of 30-90% 1RM of Smith squat lifts performed by 21 subjects with the FRTMS to similar measurements obtained with a previously validated three-dimensional motion capture system. Results showed that the FRTMS produced practically identical velocity outcomes, with a high Pearson's correlation coefficient, intraclass correlation coefficient, and coefficient of multiple correlations and a low root mean square error. We also studied the applications of the FRTMS in practical training by comparing the training results of a six-week experimental intervention with velocity-based training (VBT) and percentage-based training (PBT). The current findings suggest that the proposed monitoring system can provide reliable data for refining future training monitoring and analysis.

Comparison of the PUSH Band 2.0 and Vicon Motion Capture to Measure Concentric Movement Velocity during the Barbell Back Squat and Bench Press

The purpose of this investigation was to compare concentric movement velocity (CMV) measured with the PUSH Band (v2.0) and a Vicon motion capture system (MC) during the back squat (SQ) and the bench press (BP) resistance exercises (RE). Twelve resistance-trained males (26.0 ± 5.5 years; 175.6 ± 4.9 cm; 96.3 ± 15.8 kg) completed ten repetitions at 50% of one-repetition maximum (1RM), and six repetitions at 75% 1RM for both BP and SQ. Four PUSH devices were utilized and attached to the subject’s right forearm, the center barbell, left and right sides of the barbell. MC markers were placed on top of each PUSH device. An overall analysis using a series of least-squares means contrasts suggested CMV did not differ (p > 0.05) between measurement technologies when position, RE, intensity and repetitions were combined. PUSH exhibited the highest Intraclass Correlation Coefficients (ICC = 0.835−0.961) and Pearson Product-Moment Correlation Coefficients (r = 0.742−0.949) at the arm and center barbell locations when compared with MC. The measurement of CMV between MC and PUSH compares favorably during moderate (i.e., 50%) and high (75%) intensity SQ and BP RE. These data indicate individuals can use the PUSH band v2.0 to accurately monitor CMV within a RE set for SQ and BP RE.

Validation of an Automatic Inertial Sensor-Based Methodology for Detailed Barbell Velocity Monitoring during Maximal Paralympic Bench Press

Current technologies based on inertial measurement units (IMUs) are considered valid and reliable tools for monitoring barbell velocity in strength training. However, the extracted outcomes are often limited to a few velocity metrics, such as mean or maximal velocity. This study aimed at validating a single IMU-based methodology to automatically obtain the barbell velocity full profile as well as key performance metrics during maximal Paralympic bench press. Seven Paralympic powerlifters (age: 30.5 ± 4.3 years, sitting height: 71.6 ± 6.8 cm, body mass: 72.5 ± 16.4 kg, one-repetition maximum: 148.4 ± 38.6 kg) performed four attempts of maximal Paralympic bench press. The barbell velocity profile and relevant metrics were automatically obtained from IMU linear acceleration through a custom-made algorithm and validated against a video-based reference system. The mean difference between devices was 0.00 ± 0.04 m·s−1 with low limits of agreement (<0.09 m·s−1) and moderate-to-good reliability (ICC: 0.55−0.90). Linear regression analysis showed large-to-very large associations between paired measurements (r: 0.57−0.91, p < 0.003; SEE: 0.02−0.06 m·s−1). The analysis of velocity curves showed a high spatial similarity and small differences between devices. The proposed methodology provided a good level of agreement, making it suitable for different applications in barbell velocity monitoring during maximal Paralympic bench press.

A comparison of muscle activation and concomitant intermuscular coupling of antagonist muscles among bench presses with different instability degrees in untrained men

The aim of this study was to analyze and compare the muscle activation and concomitant intermuscular coupling of antagonist muscles among bench presses with different instability degrees. Twenty-nine untrained male college students performed bench press exercises at an intensity of 60% 1 RM on three conditions: small unstable bench press with Smith machine (SBP), medium unstable bench press of free weight (FWBP), and large unstable bench press with increased instability by suspending the load with elastic bands (IIBP). One-way repeated measures analysis of variance was used to compare integrated EMG activity values of the biceps brachii (BB), posterior deltoid (PD), long head of the triceps brachii (TB), anterior deltoid (AD), upper portion of the pectoralis major (PM) muscles, and phase synchronization index (PSI) of BB-TB and PD-AD antagonist muscle pairs. A higher integrated EMG of BB muscle was found during bench press with a more unstable condition. IIBP showed a higher integrated EMG of prime movers (TB, AD, and PM) and stabilizing of BB than SBP and FWBP. PSI between muscle pairs of BB-TB in the gamma frequency band was higher in SBP than the other bench presses with unstable conditions, which may be related to the optimal “internal model” for antagonist muscles during bench press exercise. Therefore, IIBP training may be an effective accessory exercise to maintain a higher level of muscle activation across primary and stabilizing muscles with a lighter load for untrained men, while SBP may be a suitable bench press exercise for untrained participants who have not developed the neuromuscular adaptations necessary for correct stabilization of the elbow joint.

Concurrent Validity of Field-Based Diagnostic Technology Monitoring Movement Velocity in Powerlifting Exercises

ABSTRACT

Mitter, B, Hölbling, D, Bauer, P, Stöckl, M, Baca, A, and Tschan, H. Concurrent validity of field-based diagnostic technology monitoring movement velocity in powerlifting exercises. J Strength Cond Res 35(8): 2170-2178, 2021-The study was designed to investigate the validity of different technologies used to determine movement velocity in resistance training. Twenty-four experienced powerlifters (18 male and 6 female; age, 25.1 ± 5.1 years) completed a progressive loading test in the squat, bench press, and conventional deadlift until reaching their 1 repetition maximum. Peak and mean velocity were simultaneously recorded with 4 field-based systems: GymAware (GA), FitroDyne (FD), PUSH (PU), and Beast Sensor (BS). 3D motion capturing was used to calculate specific gold standard trajectory references for each device. GA provided the most accurate output across exercises (r = 0.99-1, ES = -0.05 to 0.1). FD showed similar results for peak velocity (r = 1, standardized mean bias [ES] = -0.1 to -0.02) but considerably less validity for mean velocity (r = 0.92-0.95, ES = -0.57 to -0.29). Reasonably valid to highly valid output was provided by PU in all exercises (r = 0.91-0.97, ES = -0.5 to 0.28) and by BS in the bench press and for mean velocity in the squat (r = 0.87-0.96, ES = -0.5 to -0.06). However, BS did not reach the thresholds for reasonable validity in the deadlift and for peak velocity in the squat, mostly due to high standardized mean bias (ES = -0.78 to -0.63). In conclusion, different technologies should not be used interchangeably. Practitioners who require negligible measurement error in their assessment of movement velocity are advised to use linear position transducers over inertial sensors.

Validity of Different Velocity-Based Methods and Repetitions-to-Failure Equations for Predicting the 1 Repetition Maximum During 2 Upper-Body Pulling Exercises

ABSTRACT

Pérez-Castilla, A, Suzovic, D, Domanovic, A, Fernandes, JFT, and García-Ramos, A. Validity of different velocity-based methods and repetitions-to-failure equations for predicting the 1 repetition maximum during 2 upper-body pulling exercises. J Strength Cond Res 35(7): 1800-1808, 2021-This study aimed to compare the accuracy of different velocity-based methods and repetitions-to-failure equations for predicting the 1 repetition maximum (i.e., maximum load that can be lifted once; 1RM) during 2 upper-body pulling exercises. Twenty-three healthy subjects (twelve men and eleven women) were tested in 2 sessions during the lat pull-down and seated cable row exercises. Each session consisted of an incremental loading test until reaching the 1RM followed by a set of repetitions-to-failure against the 80% 1RM load. The 1RM was estimated from the individual load-velocity relationships modeled through 4 (∼40, 55, 70, and 85% 1RM; multiple-point method) or 2 loads (∼40 and 85% 1RM; 2-point method). Mean velocity was recorded with a linear position transducer and a Smartphone application. Therefore, 4 velocity-based methods were used as a result of combining the 2 devices and the 2 methods. Two repetitions-to-failure equations (Mayhew and Wathen) were also used to predict the 1RM from the load and number of repetitions completed. The absolute differences with respect to the actual 1RM were higher for the repetitions-to-failure equations than velocity-based methods during the seated cable row exercise (p = 0.004), but not for the lat pull-down exercise (p = 0.200). The repetitions-to-failure equations significantly underestimated the actual 1RM (p < 0.05; range: -6.65 to -2.14 kg), whereas no systematic differences were observed for the velocity-based methods (range: -1.75 to 1.65 kg). All predicted 1RMs were highly correlated with the actual 1RM (r ≥ 0.96). The velocity-based methods provide a more accurate estimate of the 1RM than the Mayhew and Wathen repetitions-to-failure equations during the lat pull-down and seated cable row exercises.

The Effectiveness of Two Methods of Prescribing Load on Maximal Strength Development: A Systematic Review

Background

Optimal prescription of resistance exercise load (kg) is essential for the development of maximal strength. Two methods are commonly used in practice with no clear consensus on the most effective approach for the improvement of maximal strength.

Objective

The primary aim of this review was to compare the effectiveness of percentage 1RM (% 1RM) and repetition maximum targets (RM) as load prescription methods for the development of maximal strength.

Methods

Electronic database searches of MEDLINE, SPORTDiscus, Scopus, and CINAHL Complete were conducted in accordance with PRISMA guidelines. Studies were eligible for inclusion if a direct measure of maximal strength was used, a non-training control group was a comparator, the training intervention was > 4 weeks in duration and was replicable, and participants were defined as healthy and between the ages of 18–40. Methodological quality of the studies was evaluated using a modified Downs and Black checklist. Percentage change (%) and 95% confidence intervals (CI) for all strength-based training groups were calculated. Statistical significance (p < 0.05) was reported from each study.

Results

Twenty-two studies comprising a total of 761 participants (585 males and 176 females) were found to meet the inclusion criteria. 12 studies were returned for % 1RM, with 10 for RM. All studies showed statistically significant improvements in maximal strength in the training groups (31.3 ± 21.9%; 95% CI 33.1–29.5%). The mean quality rating for all studies was 17.7 ± 2.3. Four studies achieved a good methodological rating, with the remainder classified as moderate.

Conclusions

Both % 1RM and RM are effective tools for improving maximal strength. % 1RM appears to be a better prescriptive method than RM potentially due to a more sophisticated management of residual fatigue. However, large heterogeneity was present within this data. Lower body and multi-joint exercises appear to be more appropriate for developing maximal strength. Greater consensus is required in defining optimal training prescriptions, physiological adaptations, and training status.

Electronic supplementary material

The online version of this article (10.1007/s40279-019-01241-3) contains supplementary material, which is available to authorized users.

Auto-Regulation Method vs. Fixed-Loading Method in Maximum Strength Training for Athletes: A Systematic Review and Meta-Analysis

The auto-regulation method is a rising training strategy to improve strength and motor performance, and the Autoregulatory Progressive Resistance Exercise (APRE), Rating of Perceived Exertion program (RPE), and Velocity-Based Training (VBT) are the three common auto-regulation programs. However, whether the auto-regulation method is more effective than the traditional strength training (the fixed-loading method) in maximum strength training is still unclear. The present study searched the Pubmed, SPORTDiscus, Web of Science, Embase, EBSCO, Cochrane, CNKI, and CQVIP databases, and included eight related studies published between 2010 and 2020, with a total of 166 subjects including division 1 college players and athletes with at least 1-year training history, and interventions ranging from 5 to 10 weeks. A meta-analysis was performed to check the difference between the two training methods, and analyzed the differences in the existing auto-regulation programs' effectiveness. The overall results showed that the auto-regulation method was more effective than the fixed-loading method in maximum strength training (effect size = 0.64; P < 0.001; I² = 0%). In specific, the pooled results in subgroup analysis indicated that the auto-regulation method may effectively improve the strength performance in squat (effect size = 4.64; P < 0.05; I² = 54%) and bench press (effect size = 3.21; P < 0.05; I² = 62%). Greater benefits of the auto-regulation method on strength improvement could be achieved in an 8-week or even shorter training (effect size = 0.87; P < 0.001; I² = 0%) compared with those of 8–10 weeks (effect size = 0.32; P < 0.001; I² = 0%). The APRE is the most effective training program among the three auto-regulation programs (effect size = 0.78; P < 0.001; I² = 0%). In conclusion, the auto-regulation method could be more effective than the fixed-loading method in maximum strength training. The APRE is a convenient and effective training program that may be considered a practical training program to replace traditional training in athletes.

Pooled Versus Individualized Load-Velocity Profiling in the Free-Weight Back Squat and Power Clean

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.

Reliability and Validity of the iLOAD Application for Monitoring the Mean Set Velocity During the Back Squat and Bench Press Exercises Performed Against Different Loads

ABSTRACT

Pérez-Castilla, A, Boullosa, D, and García-Ramos, A. Reliability and validity of the iLOAD application for monitoring the mean set velocity during the back squat and bench press exercises performed against different loads. J Strength Cond Res 35(2S): S57-S65, 2021-This study aimed to evaluate the reliability and validity of a smartphone application (iLOAD) for the monitoring of mean concentric velocity (MV) during resistance training sets. Twenty males completed 2 identical sessions consisting of one set of 10 repetitions against 4 loads (25, 40, 55, 70% of the one repetition maximum [1RM]) during the back squat and bench press exercises. The MV of the 5 initial repetitions and for the whole set were determined simultaneously with the iLOAD application and a linear velocity transducer (LVT). Two independent researchers operated the iLOAD application during the experimental sessions to evaluate the interrater agreement for the assessment of MV. An acceptable but generally lower reliability was observed for iLOAD (coefficient of variation [CV] range: 5.61-9.79%) compared to the LVT (CV range: 4.51-8.18%) at 25-40-55% of 1RM, whereas the reliability at 75% of 1RM was acceptable for the LVT during the bench press (CV range: 6.37-8.26%), but it was unacceptable for the iLOAD during both exercises (CV range: 11.3-12.8%) and for the LVT during the back squat (CV range: 11.3-17.4%). Small to moderate differences (ES range: 0.24-1.04) and very high to practically perfect correlations (r range: 0.70-0.90) were observed between the iLOAD and the LVT. A very high agreement was observed between both raters for the recording of MV during the back squat and bench press exercises (r ≥ 0.98). Taken together, these results suggest that the iLOAD application can be confidently used to quantify the MV of training sets during the squat and bench press exercises not performed to failure.

The Validity and Reliability of Commercially Available Resistance Training Monitoring Devices: A Systematic Review

Background

Monitoring resistance training has a range of unique difficulties due to differences in physical characteristics and capacity between athletes, and the indoor environment in which it often occurs. Traditionally, methods such as volume load have been used, but these have inherent flaws. In recent times, numerous portable and affordable devices have been made available that purport to accurately and reliably measure kinetic and kinematic outputs, potentially offering practitioners a means of measuring resistance training loads with confidence. However, a thorough and systematic review of the literature describing the reliability and validity of these devices has yet to be undertaken, which may lead to uncertainty from practitioners on the utility of these devices.

Objective

A systematic review of studies that investigate the validity and/or reliability of commercially available devices that quantify kinetic and kinematic outputs during resistance training.

Methods

Following PRISMA guidelines, a systematic search of SPORTDiscus, Web of Science, and Medline was performed; studies included were (1) original research investigations; (2) full-text articles written in English; (3) published in a peer-reviewed academic journal; and (4) assessed the validity and/or reliability of commercially available portable devices that quantify resistance training exercises.

Results

A total of 129 studies were retrieved, of which 47 were duplicates. The titles and abstracts of 82 studies were screened and the full text of 40 manuscripts were assessed. A total of 31 studies met the inclusion criteria. Additional 13 studies, identified via reference list assessment, were included. Therefore, a total of 44 studies were included in this review.

Conclusion

Most of the studies within this review did not utilise a gold-standard criterion measure when assessing validity. This has likely led to under or overreporting of error for certain devices. Furthermore, studies that have quantified intra-device reliability have often failed to distinguish between technological and biological variability which has likely altered the true precision of each device. However, it appears linear transducers which have greater accuracy and reliability compared to other forms of device. Future research should endeavour to utilise gold-standard criterion measures across a broader range of exercises (including weightlifting movements) and relative loads.

Electronic supplementary material

The online version of this article (10.1007/s40279-020-01382-w) contains supplementary material, which is available to authorized users.

Is the OUTPUT Sports Unit Reliable and Valid When Estimating Back Squat and Bench Press Concentric Velocity?

ABSTRACT

Merrigan, JJ and Martin, JR. Is the OUTPUT sports unit reliable and valid when estimating back squat and bench press concentric velocity? J Strength Cond Res XX(X): 000-000, 2020-This study evaluated the reliability and concurrent validity of the OUTPUT sports inertial unit to measure concentric velocity of free-weight back squat and bench press exercises. Eleven men and women performed back squat and bench press 1 repetition maximum (1RM) testing. One week later, subjects performed 3 repetitions of each exercise with 35, 45, 55, 65, 75, and 85% 1RM (18 total repetitions). The OUTPUT and 4 cable extension transducers (criterion) simultaneously recorded the mean and peak velocity. The OUTPUT had acceptable reliability for all loads except 85% 1RM for back squat and bench press (intraclass correlation coefficient = 0.72-0.96, coefficient of variation = 0.03-0.12). High systematic biases existed for the mean and peak velocity for the back squat and bench press, according to Bland-Altman plot's wide limits of agreement and ordinary least products regressions. According to Bland-Altman plots, OUTPUT tended to overestimate bench press velocity and overestimate back squat velocity at slower velocities. Least products regression analyses determined proportional bias existed for the mean and peak velocity of the back squat and peak velocity of the bench press. In conclusion, researchers and practitioners are advised not to compare velocity estimates of the OUTPUT unit with criterion devices because these methods cannot be used interchangeably. However, because of the demonstrated reliability when estimating the mean and peak velocity, strength and conditioning practitioners may find the OUTPUT unit valuable for monitoring performance of the back squat and bench press exercises. Yet, caution should be taken when evaluating loads ≥85% 1RM.

Using Velocity to Predict the Maximum Dynamic Strength in the Power Clean

The primary aim of the present study was to examine the commonly performed training exercise for athlete preparation. Twenty-two recreationally trained males (age: 26.3 ± 4.1 y, height: 1.80 ± 0.07 m; body mass (BM): 87.01 ± 13.75 kg, 1-repetitoon maximum(1-RM)/BM: 0.90 ± 0.19 kg) participated in the present study. All subjects had their 1-RM power clean tested with standard procedures. On a separate testing day, subjects performed three repetitions at 30% and 45%, and two repetitions at 70% and 80% of their 1-RM power clean. During all trials during both sessions, peak velocity (PV) and mean velocity (MV) were measured with the use of a GymAware device. There were no significant differences between the actual and estimated 1-RM power clean (p = 0.37, ES = −0.11) when the load-PV profile was utilized. There was a large typical error (TE) present for the load-PV- and load-MV-estimated 1-RM values. Additionally, the raw TE exceeded the smallest worthwhile change for both load-PV and load-MV profile results. Based upon the results of this study, the load-velocity profile is not an acceptable tool for monitoring power clean strength.

CONCURRENT VALIDITY OF INSTRUMENTS FOR MEASURING SPEED OF MOVEMENT IN LEG PRESS EXERCISES

ABSTRACT Introduction Adequate measurement of movement velocity in strength exercises can assist in the prescription and evaluation of training effects. Objective The objectives of the present study were to analyze the reliability (test-retest) and concurrent validity of the movement velocity measured by means of the electrogoniometer and accelerometer during horizontal leg press exercise at different intensities (40, 60, 80% of a maximum repetition - 1RM). Methods Eighteen young women attended the laboratory on five occasions. After determining the maximum dynamic force, two visits (separated by 48-72 hours) were used to verify the reliability (test-retest) for different speed variables in the three intensities. Results The mean propulsive velocity obtained by the goniometer showed higher Intraclass correlation coefficients (ICC) and lower coefficients of variation compared to the accelerometer. The same behavior was observed for both the mean velocity and the peak velocity. The propulsive time was more reproducible and with less variation for the accelerometer and bad CCI for both sensors were observed at 60% of 1RM. When the sensors are compared, the mean and average propulsive velocities presented moderate ratios with a large to very large standardized medium bias. Conclusion The potentiometer of the electrogoniometer can be used to estimate the velocity in the horizontal leg press exercise, especially for loads of 60 and 80%. The performance of the accelerometer was inferior to that of the potentiometer. Level of evidence II; Diagnostic studies.

The Reliability and Validity of Current Technologies for Measuring Barbell Velocity in the Free-Weight Back Squat and 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.

Effects of In-Season Velocity- Versus Percentage-Based Training in Academy Rugby League Players

PURPOSE

To compare the effects of velocity-based training (VBT) vs percentage-based training (PBT) on strength, speed, and jump performance in academy rugby league players during a 7-wk in-season mesocycle.

METHODS

A total of 27 rugby league players competing in the Super League U19s Championship were randomized to VBT (n = 12) or PBT (n = 15). Both groups completed a 7-wk resistance-training intervention (2×/wk) that involved the back squat. The PBT group used a fixed load based on a percentage of 1-repetition maximum (1-RM), whereas the VBT group used a modifiable load based on individualized velocity thresholds. Biomechanical and perceptual data were collected during each training session. Back-squat 1-RM, countermovement jump, reactive strength index, sprint times, and back-squat velocity at 40-90% 1-RM were assessed pretraining and posttraining.

RESULTS

The PBT group showed likely to most likely improvements in 1-RM strength and reactive strength index, whereas the VBT group showed likely to very likely improvements in 1-RM strength, countermovement jump height, and back-squat velocity at 40% and 60% 1-RM. Sessional velocity and power were most likely greater during VBT compared with PBT (standardized mean differences = 1.8-2.4), while time under tension and perceptual training stress were likely lower (standardized mean differences = 0.49-0.66). The improvement in back-squat velocity at 60% 1-RM was likely greater following VBT compared with PBT (standardized mean difference = 0.50).

CONCLUSION

VBT can be implemented during the competitive season, instead of traditional PBT, to improve training stimuli, decrease training stress, and promote velocity-specific adaptations.

Validity of various portable devices to measure sit-to-stand velocity and power in older adults

BACKGROUND

Movement velocity and power in a single STS are related to functional performance in older adults. Identifying accessible tools that provide valid measures of STS velocity/power would allow practitioners to evaluate physical function in clinical settings where time, space and finances are limited.

RESEARCH QUESTION

Does a linear position transducer (LPT), iPhone application (App), and inertial measurement unit (IMU) obtain valid measurements of velocity and power during a single STS compared with 3D motion capture?

METHODS

Twenty-seven community-dwelling older adults aged ≥60 years completed a single STS test with mean velocity and power simultaneously measured with 3D motion capture, an LPT, IMU and App. Acceptable validity was established if the Pearson correlation coefficient (r) was very high (≥0.7) and bias as a standardised effect size (ES) was small (<0.6). The relationship between STS velocity/power and 30s chair STS performance was also evaluated.

RESULTS

Measures of STS velocity obtained by the LPT (r = 0.94, ES = -0.21) and App (r = 0.89, ES = -0.19) were very highly valid when compared to 3D motion capture, and were very strongly related to 30s STS performance (r ≥0.74). The LPT (r = 0.87, ES = 0.13) and App (r = 0.74, ES = -0.12) also showed very high correlations and negligible bias for measuring STS power. Data collected by the IMU failed to meet our pre-determined threshold of acceptable validity for STS velocity (r = 0.72, ES = 1.00) or power (r = 0.61, ES = 0.34).

SIGNIFICANCE

The LPT and iPhone App, but not the IMU, are valid tools for measuring STS velocity and power in community-dwelling older adults. Clinicians can use STS velocity obtained by either the LPT or App as a simple and valid proxy for functional status, which could help identify patients at high-risk of incident disability.

Reliability and Criterion Validity of the Assess2Perform Bar Sensei

The Assess2Perform Bar Sensei is a device used to measure barbell velocity for velocity-based training that has not yet been validated. The purpose of this study was to determine criterion validity and reliability of the Assess2Perform Bar Sensei in barbell back squats by comparing it against the GymAware PowerTool, a previously validated instrument. Sixteen injury-free, resistance-trained subjects (eleven males and five females) were recruited. Subjects were tested for their back squat one repetition maximum (1RM). Then, on two separate days, subjects performed two sets of three repetitions at loads of 45%, 60% and 75% 1RM. The GymAware PowerTool and Bar Sensei were attached to the barbell in similar locations for concurrent collection of mean concentric velocity (MCV) and peak concentric velocity (PCV). The Bar Sensei and PowerTool showed generally fair to poor agreement for MCV and PCV when subjects lifted 45% of 1RM (intraclass correlation;ICC 0.4–0.59), and they showed poor agreement when subjects lifted 60% and 75% of 1RM (ICC 0.3–0.4). Inter-repetition/within-set reliability for the Bar Sensei ranged between ICC = 0.273–0.451 for MCV and PCV compared to the far more reliable PowerTool (ICC = 0.651–0.793). Currently, the Bar Sensei is not a reliable or valid tool for measuring barbell velocity in back squats.

Precision of 7 Commercially Available Devices for Predicting Bench-Press 1-Repetition Maximum From the Individual Load-Velocity Relationship

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.

Validity and Reliability of Kinematics Measured with PUSH Band vs. Linear Encoder in Bench Press and Push-Ups

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.

The reliability and validity of the bar-mounted PUSH BandTM 2.0 during bench press with moderate and heavy loads

The aim of this study was to assess the reliability and validity of the bar-mounted PUSH Band^TM 2.0 to determine peak and mean velocity during the bench press exercise with a moderate (60% one repetition maximum [1RM]) and heavy (90% 1RM) load. We did this by simultaneously recording peak and mean velocity using the PUSH Band^TM 2.0 and three-dimensional motion capture from participants bench pressing with 60% and 90% 1RM. We used ordinary least products regression to assess within-session reliability and whether the PUSH Band^TM 2.0 could accurately predict motion capture velocity. Results showed that PUSH Band^TM 2.0 and motion capture peak and mean velocity reliability was acceptable with both loads. While there was a tendency for the PUSH Band^TM 2.0 to slightly overestimate peak and mean velocity, there was no fixed bias. However, mean velocity with 60 and 90% 1RM demonstrated proportional bias (differences between predicted and motion capture values increase with magnitude). Therefore, PUSH Band^TM 2.0 peak velocity with 60 and 90% 1RM is valid, but mean velocity is not.