Comparison of the FitroDyne and GymAware Rotary Encoders for Quantifying Peak and Mean Velocity During Traditional Multijointed Exercises

Validity and Concordance of a Linear Position Transducer (Vitruve) for Measuring Movement Velocity during Resistance Training

This study aimed to analyze the intra-device agreement of a new linear position transducer (Vitruve, VT) and the inter-device agreement with a previously validated linear velocity transducer (T-Force System, TF) in different range of velocities. A group of 50 healthy, physically active men performed a progressive loading test during a bench press (BP) and full-squat (SQ) exercise with a simultaneous recording of two VT and one TF devices. The mean propulsive velocity (MPV) and peak of velocity (PV) were recorded for subsequent analysis. A set of statistics was used to determine the degree of agreement (Intraclass correlation coefficient [ICC], Lin's concordance correlation coefficient [CCC], mean square deviation [MSD], and variance of the difference between measurements [VMD]) and the error magnitude (standard error of measurement [SEM], smallest detectable change [SDC], and maximum errors [ME]) between devices. The established velocity ranges were as follows: >1.20 m·s-1; 1.20-0.95 m·s-1; 0.95-0.70 m·s-1; 0.70-0.45 m·s-1; ≤0.45 m·s-1 for BP; and >1.50 m·s-1; 1.50-1.25 m·s-1; 1.25-1.00 m·s-1; 1.00-0.75 m·s-1; and ≤0.75 m·s-1 for SQ. For the MPV, the VT system showed high intra- and inter-device agreement and moderate error magnitude with pooled data in both exercises. However, the level of agreement decreased (ICC: 0.790-0.996; CCC: 0.663-0.992) and the error increased (ME: 2.8-13.4% 1RM; SEM: 0.035-0.01 m·s-1) as the velocity range increased. For the PV, the magnitude of error was very high in both exercises. In conclusion, our results suggest that the VT system should only be used at MPVs below 0.45 m·s-1 for BP and 0.75 m·s-1 for SQ in order to obtain an accurate and reliable measurement, preferably using the MPV variable instead of the PV. Therefore, it appears that the VT system may not be appropriate for objectively monitoring resistance training and assessing strength performance along the entire spectrum of load-velocity curve.

Validity and reliability of linear position transducers and linear velocity transducers: a systematic review

This systematic review aimed to summarise and analyse the evidence on the reliability and validity of linear tranducers (LTs) in exercises of different nature and different modes of execution. This systematic review was carried out under PRISMA guidelines, and was carried out using three databases (PubMed, Web of Sciences, and Scopus). Of the 351 initially found, 21 were included in the qualitative synthesis. The results reflected that linear position transducers (LPTs) were valid and reliable in monitoring movement velocity in non-plyometric exercises. However, precision and reliability were lower in execution protocols without isometric phase and in the execution of exercises in multiple planes of movement, with greater measurement errors at higher sampling frequencies. On the other hand, linear velocity transducers (LVTs) proved to be valid and reliable in measuring velocity during plyometric and non-plyometric exercises performed on the Smith machine, with less variation in measurement in the latter. Finally, the use of peak values is recommended, since they are less dependent on the technological errors of LTs. Therefore, the performance of non-plyometric exercises, carried out in the Smith machine and with an isometric phase in the execution of the movement, will help to minimise the technological error of the LTs.

Resistance Training Intensity Prescription Methods Based on Lifting Velocity Monitoring

Resistance training intensity is commonly quantified as the load lifted relative to an individual's maximal dynamic strength. This approach, known as percent-based training, necessitates evaluating the one-repetition maximum (1RM) for the core exercises incorporated in a resistance training program. However, a major limitation of rigid percent-based training lies in the demanding nature of directly testing the 1RM from technical, physical, and psychological perspectives. A potential solution that has gained popularity in the last two decades to facilitate the implementation of percent-based training involves the estimation of the 1RM by recording the lifting velocity against submaximal loads. This review examines the three main methods for prescribing relative loads (%1RM) based on lifting velocity monitoring: (i) velocity zones, (ii) generalized load-velocity relationships, and (iii) individualized load-velocity relationships. The article concludes by discussing a number of factors that should be considered for simplifying the testing procedures while maintaining the accuracy of individualized L-V relationships to predict the 1RM and establish the resultant individualized %1RM-velocity relationship: (i) exercise selection, (ii) type of velocity variable, (iii) regression model, (iv) number of loads, (v) location of experimental points on the load-velocity relationship, (vi) minimal velocity threshold, (vii) provision of velocity feedback, and (viii) velocity monitoring device.

Is two-point method a valid and reliable method to predict 1RM? A systematic review

This systematic review aimed to evaluate the reliability and validity of the two-point method in predicting 1RM compared to the direct method, as well as analyze the factors influencing its accuracy. A comprehensive search of PubMed, Web of Science, Scopus, and SPORTDiscus databases was conducted. Out of the 88 initially identified studies, 16 were selected for full review, and their outcome measures were analyzed. The findings of this review indicated that the two-point method slightly overestimated 1RM (effect size = 0.203 [95%CI: 0.132, 0.275]; P < 0.001); It showed that test-retest reliability was excellent as long as the test loads were chosen reasonably (Large difference between two test loads). However, the reliability of the two-point method needs to be further verified because only three studies have tested its reliability. Factors such as exercise selection, velocity measurement device, and selection of test loads were found to influence the accuracy of predicting 1RM using the two-point method. Additionally, the choice of velocity variable, 1RM determination method, velocity feedback, and state of fatigue were identified as potential influence factors. These results provide valuable insights for practitioners in resistance training and offer directions for future research on the two-point method.

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.

Validity of using perceived exertion to assess muscle fatigue during back squat exercise

The rating of perceived exertion (RPE) scale has been found to reflect physiological responses, and this study aimed to assess the validity of using the Borg CR-10 scale and velocity loss to evaluate muscle fatigue quantified by surface electromyography during back squat (BS) exercise. A total of 15 collegiate male athletes underwent three non-explosive BS tasks comprising low, medium, and high volumes at 65% of their one-repetition maximum. RPEs, spectral fatigue index (SFI), and velocity loss during BS exercise were assessed throughout the trials. Significant differences in overall RPE (p < 0.001) and average SFI (p < 0.05) were observed between the conditions, whereas no significant difference was observed in average velocity loss. Significant increases in RPE and SFI (p < 0.001) were observed within the exercise process, whereas a significant increase in velocity loss was not observed. Correlation analyses indicated a significant correlation between RPE and SFI obtained during exercise (r = 0.573, p < 0.001). However, no significant correlation was observed between velocity loss and SFI. These results demonstrated that RPE could be used as a muscle fatigue predictor in BS exercise, but that velocity loss may not reflect muscle fatigue correctly when participants cannot and/or are not required to perform BS explosively. Furthermore, practitioners should not use velocity loss as a muscle fatigue indicator in some resistance exercise situations, such as rehabilitation, beginner, and hypertrophy programs.

Validity of using perceived exertion to assess muscle fatigue during resistance exercises

BACKGROUND

The rating of perceived exertion (RPE) is correlated with physiological variables. The purpose of this study was to assess the validity of using the Borg CR-10 scale and velocity to predict muscle fatigue assessed by surface electromyography during single joint resistance exercises.

METHODS

Fifteen healthy males underwent different fatigue levels of unilateral elbow flexion (EF) and knee extension (KE), consisting of low, medium, and high volumes at 65% of their one-repetition maximum. The RPEs, spectral fatigue index (SFI), and mean velocity of the experimental exercises were assessed throughout the trials.

RESULTS

Significant differences in overall RPE (p < 0.001) and average SFI (p < 0.001) were observed between the conditions in both exercises. Significant changes in RPE and SFI (p < 0.001) were observed throughout the EF, whereas a SFI increase (p < 0.001) was only observed at the end point of KE. Multiple regression analyses revealed two significant models (p < 0.001) for the prediction of muscle fatigue during EF (R² = 0.552) and KE (R² = 0.377).

CONCLUSIONS

Muscle fatigue resulted in similar increases in perceptual responses, demonstrating that RPE is useful for assessing fatigue when resistance exercise is performed. However, velocity changes may not reflect muscle fatigue correctly when exercise is no longer performed in an explosive manner. We recommend combining RPE responses with velocity changes to comprehensively assess muscle fatigue during clinical and sports situations.

Training for Muscular Strength: Methods for Monitoring and Adjusting Training Intensity

Linear loading, the two-for-two rule, percent of one repetition maximum (1RM), RM zones, rate of perceived exertion (RPE), repetitions in reserve, set-repetition best, autoregulatory progressive resistance exercise (APRE), and velocity-based training (VBT) are all methods of adjusting resistance training intensity. Each method has advantages and disadvantages that strength and conditioning practitioners should be aware of when measuring and monitoring strength characteristics. The linear loading and 2-for-2 methods may be beneficial for novice athletes; however, they may be limited in their capacity to provide athletes with variation and detrimental if used exclusively for long periods of time. The percent of 1RM and RM zone methods may provide athletes with more variation and greater potential for strength-power adaptations; however, they fail to account for daily changes in athlete's performance capabilities. An athlete's daily readiness can be addressed to various extents by both subjective (e.g., RPE, repetitions in reserve, set-repetition best, and APRE) and objective (e.g., VBT) load adjustment methods. Future resistance training monitoring may aim to include a combination of measures that quantify outcome (e.g., velocity, load, time, etc.) with process (e.g., variability, coordination, efficiency, etc.) relevant to the stage of learning or the task being performed. Load adjustment and monitoring methods should be used to supplement and guide the practitioner, quantify what the practitioner 'sees', and provide longitudinal data to assist in reviewing athlete development and providing baselines for the rate of expected development in resistance training when an athlete returns to sport from injury or large training load reductions.

Prediction of One Repetition Maximum Using Reference Minimum Velocity Threshold Values in Young and Middle-Aged Resistance-Trained Males

Background: This study determined the accuracy of different velocity-based methods when predicting one-repetition maximum (1RM) in young and middle-aged resistance-trained males. Methods: Two days after maximal strength testing, 20 young (age 21.0 ± 1.6 years) and 20 middle-aged (age 42.6 ± 6.7 years) resistance-trained males completed three repetitions of bench press, back squat, and bent-over-row at loads corresponding to 20–80% 1RM. Using reference minimum velocity threshold (MVT) values, the 1RM was estimated from the load-velocity relationships through multiple (20, 30, 40, 50, 60, 70, and 80% 1RM), two-point (20 and 80% 1RM), high-load (60 and 80% 1RM) and low-load (20 and 40% 1RM) methods for each group. Results: Despite most prediction methods demonstrating acceptable correlations (r = 0.55 to 0.96), the absolute errors for young and middle-aged groups were generally moderate to high for bench press (absolute errors = 8.2 to 14.2% and 8.6 to 20.4%, respectively) and bent-over-row (absolute error = 14.9 to 19.9% and 8.6 to 18.2%, respectively). For squats, the absolute errors were lower in the young group (5.7 to 13.4%) than the middle-aged group (13.2 to 17.0%) but still unacceptable. Conclusion: These findings suggest that reference MVTs cannot accurately predict the 1RM in these populations. Therefore, practitioners need to directly assess 1RM.

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.

Influence of Coaching Condition on the Magnitude and Reliability of Drop Jump Height in Men and Women

This study examined the effect of different coaching conditions on the magnitude and reliability of drop jump height in men and women. Nineteen collegiate sport sciences students (10 men) performed two sets of 10 drop jumps under four different coaching conditions: neutral, augmented feedback, external focus of attention, and a combination of augmented feedback and external focus of attention. The augmented feedback condition revealed a significantly higher jump height than the neutral condition (p = .002), while no significant differences were observed for the remaining conditions (p ≥ .38). The external focus of attention condition was more reliable than the neutral and augmented feedback conditions (coefficient of variationratio ≥ 1.15), while no differences were observed between the remaining conditions. These results suggest that both the magnitude and reliability of the drop jump height performance are influenced by the coaching condition.

Group versus Individualised Minimum Velocity Thresholds in the Prediction of Maximal Strength in Trained Female Athletes

This study examined the accuracy of different velocity-based methods in the prediction of bench press and squat one-repetition maximum (1RM) in female athletes. Seventeen trained females (age 17.8 ± 1.3 years) performed an incremental loading test to 1RM on bench press and squat with the mean velocity being recorded. The 1RM was estimated from the load-velocity relationship using the multiple- (8 loads) and two-point (2 loads) methods and group and individual minimum velocity thresholds (MVT). No significant effect of method, MVT or interaction was observed for the two exercises (p > 0.05). For bench press and squat, all prediction methods demonstrated very large to nearly perfect correlations with respect to the actual 1RM (r range = 0.76 to 0.97). The absolute error (range = 2.1 to 3.8 kg) for bench press demonstrated low errors that were independent of the method and MVT used. For squat, the favorable group MVT errors for the multiple- and two-point methods (absolute error = 7.8 and 9.7 kg, respectively) were greater than the individual MVT errors (absolute error = 4.9 and 6.3 kg, respectively). The 1RM can be accurately predicted from the load-velocity relationship in trained females, with the two-point method offering a quick and less fatiguing alternative to the multiple-point method.

Agreement between the Open Barbell and Tendo Linear Position Transducers for Monitoring Barbell Velocity during Resistance Exercise

To determine the agreement between the Open Barbell (OB) and Tendo weightlifting analyzer (TWA) for measuring barbell velocity, eleven men (19.4 ± 1.0 y) performed one set of 2–3 repetitions at four sub-maximal percentage loads, [i.e., 30, 50, 70, and 90% one-repetition maximum (1RM)] in the back (BS) and front squat (FS) exercises. During each repetition, peak and mean barbell velocity were recorded by OB and TWA devices, and the average of the 2–3 repetitions was used for analyses. Although the repeated measures analysis of variance revealed significantly (p ≤ 0.005) greater peak and mean velocity scores from OB across all intensities, high intraclass correlation coefficients (ICC_2,K = 0.790–0.998), low standard error of measurement (SEM_2,K = 0.040–0.119 m·s⁻¹), and coefficients of variation (CV = 2–4%) suggested consistency between devices. Positive (r = 0.491–0.949) Pearson correlations between averages and differences (between devices) in peak velocity, as well as associated Bland-Altman plots, showed greater differences occurred as the velocity increased, particularly at low-moderate intensity loads. OB consistently provides greater barbell velocity scores compared to TWA, and the differences between devices were more apparent as the peak velocity increased with low-to-moderate loads. Strength coaches and athletes may find better agreement between devices if the mean velocity scores are only considered.

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

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%; CV_ratio = 1.10), while the within-subject CV was lower for PV (6.36% vs. 7.56%; CV_ratio = 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.