Individual Load-velocity Relationships Research Articles

Hexagonal barbell deadlift one-repetition maximum estimation using velocity recordings.

This study aimed to determine whether the optimal minimal velocity threshold (MVT) provides more precise estimates of one-repetition maximum (1RM) in the hexagonal barbell deadlift (HBD) than the general and individual MVTs. The 1RM of 27 resistance-trained males were predicted using three types of MVT: (i) General MVT: averaged across subjects' velocity of the 1RM trial (0.25 m·s-1), (ii) individual MVT: velocity attained during the 1RM trial, and (iii) Optimal MVT: MVT that eliminated the differences between the actual and predicted 1RM. Two individual load-velocity relationships were modelled considering five (30-50-70-80%1RM) or six (30-50-70-80-90%1RM) loading conditions. Negligible differences (Effect size < 0.20), low absolute errors (< 5% of the actual 1RM), and extremely high correlations (r > 0.90) were observed between the actual and six predicted 1RMs. The only significant difference was the lower raw errors for the 90%1RM condition (0.60 ± 7.34 kg) compared to the 80%1RM condition (2.27 ± 7.54 kg; p = 0.013). These results suggest that the individual load-velocity relationship offers an accurate estimation of the HBD 1RM in resistance-trained males, and these estimates could maintain similar levels of precision across different types of MVT (general, individual, and optimal) and final tested loads (80%1RM and 90%1RM).

Estimating the one-repetition maximum on the leg-press exercise in female breast cancer survivors.

We examined the accuracy of twelve different velocity-based methods for predicting the bilateral leg-press exercise one-repetition maximum (1RM) in breast cancer survivors. Twenty-one female breast cancer survivors (age 50.2 ± 10.8 years) performed an incremental loading test up to the 1RM. Individual load-velocity relationships were modeled by linear and quadratic polynomial regression models considering the mean velocity (MV) and peak velocity (PV) values recorded at five incremental loads (~45-55-65-75-85% of 1RM) (multiple-point methods) and by a linear regression model considering only the two distant loads (~45-85% of 1RM) (two-point method). The 1RM was always estimated through these load-velocity relationships as the load associated with a general (MV: 0.24 m/s; PV: 0.60 m/s) and an individual (MV and PV of the 1RM trial) minimal velocity threshold (MVT). Compared to the actual 1RM, the 1RMs estimated by all linear regression models showed trivial differences (Hedge's g ranged from 0.08 to 0.17), very large to nearly perfect correlations (r ranged from 0.87 to 0.95), and no heteroscedasticity of the errors (coefficient of determination (r2) < 0.10 obtained from the relationship of the raw differences between the actual and predicted 1RMs with their average value). Given the acceptable and comparable accuracy for all 1RM linear prediction methods, the two-point method and a general MVT could be recommended to simplify the testing procedure of the bilateral leg-press 1RM in breast cancer survivors.

Influence of sex and strength differences on the load–velocity relationship of the Smith-machine back squat

PurposeWe aimed at determining whether the load–velocity relationship of the Smith machine concentric-back squat differs between sexes and persons with different levels of strength.MethodsThirty-two participants (16 males: 23.3 ± 3.8 years and 16 females: 26.1 ± 2.7 years) were included. Load and mean concentric velocity (MCV) were obtained individually during an incremental test (30–90% one-repetition maximum—1RM).ResultsWe obtained strong linear relationships between the individual MCV and relative load (R2>\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${R}^{2}>$$\\end{document} 0.95). Overall, relatively strong persons reached faster MCVs throughout the full range of relative loads (effect size [ES]: 0.48–0.93), except at 1RM. We also obtained steeper slopes and higher velocity intercepts (y intercepts) in relatively strong participants (ES: 0.05 and 0.83, respectively; p < 0.01). Finally, we found that males attained steeper load–velocity relationships (ES favoring relatively strong and weak males: 2.8 and 1.4, respectively) and higher velocity intercepts (ES favoring relatively strong and weak males: 2.0 and 1.0, respectively) than females (p < 0.0001).ConclusionMCV can be used to estimate relative load on the Smith machine concentric-back squat in males and females with different levels of muscle strength; however, the load–velocity relationship is affected by muscle strength and sex. Therefore, the extraction of individual load–velocity relationships is advisable instead of computing group estimations.

Perception of Bar Velocity Loss in Resistance Exercises: Accuracy Across Loads and Velocity Loss Thresholds in the Bench Press

Velocity-based training is used to prescribe and monitor resistance training based on velocity outputs measured with tracking devices. When tracking devices are unavailable or impractical to use, perceived velocity loss (PVL) can be used as a substitute, assuming sufficient accuracy. Here, we investigated the accuracy of PVL equal to 20% and 40% relative to the first repetition in the bench-press exercise. Following a familiarization session, 26 resistance-trained men performed 4 sets of the bench-press exercise using 4 different loads based on their individual load-velocity relationships (∼40%-90% of 1-repetition maximum [1RM]), completed in a randomized order. Participants verbally reported their PVL at 20% and 40% velocity loss during the sets. PVL accuracy was calculated as the absolute difference between the timing of reporting PVL and the actual repetition number corresponding to 20% and 40% velocity loss measured with a linear encoder. Linear mixed-effects model analysis revealed 4 main findings. First, across all conditions, the absolute average PVL error was 1 repetition. Second, the PVL accuracy was not significantly different between the PVL thresholds (β = 0.16, P = .267). Third, greater accuracy was observed in loads corresponding to the midportion of the individual load-velocity relationships (∼50%-60% 1RM) compared with lighter (<50% 1RM, β = 0.89, P < .001) and heavier loads (>60% 1RM, 0.63 ≤ β ≤ 0.84, all P values < .001). Fourth, PVL accuracy decreased with consecutive repetitions (β = 0.05, P = .017). PVL can be implemented as a monitoring and prescription method when velocity-tracking devices are impractical or absent.

Velocity-Based Method in Free-Weight and Machine-Based Training Modalities: The Degree of Freedom Matters.

Hernández-Belmonte, A, Buendía-Romero, Á, Pallares, JG, and Martínez-Cava, A. Velocity-based method in free-weight and machine-based training modalities: the degree of freedom matters. J Strength Cond Res 37(9): e500-e509, 2023-This study aimed to analyze and compare the load-velocity relationships of free-weight and machine-based modalities of 4 resistance exercises. Moreover, we examined the influence of the subject's strength level on these load-velocity relationships. Fifty men completed a loading test in the free-weight and machine-based modalities of the bench press, full squat, shoulder press, and prone bench pull exercises. General and individual relationships between relative intensity (%1RM) and velocity variables were studied through the coefficient of determination ( R2 ) and standard error of the estimate ( SEE ). Moreover, the velocity attained to each %1RM was compared between both modalities. Subjects were divided into stronger and weaker to study whether the subject's strength level influences the mean test (mean propulsive velocity [MPV Test ]) and 1RM (MPV 1RM ) velocities. For both modalities, very close relationships ( R2 ≥ 0.95) and reduced estimation errors were found when velocity was analyzed as a dependent ( SEE ≤ 0.086 m·s -1 ) and independent ( SEE ≤ 5.7% 1RM) variable concerning the %1RM. Fits were found to be higher ( R2 ≥ 0.995) for individual load-velocity relationships. Concerning the between-modality comparison, the velocity attained at each intensity (from 30 to 100% 1RM) was significantly faster for the free-weight variant. Finally, nonsignificant differences were found when comparing MPV Test (differences ≤ 0.02 m·s -1 ) and MPV 1RM (differences ≤ 0.01 m·s -1 ) between stronger and weaker subjects. These findings prove the accuracy and stability of the velocity-based method in the free-weight and machine-based variants but highlight the need to use the load-velocity relationship (preferably the individual one) specific to each training modality.

Optimal Minimum Velocity Threshold to Estimate the 1-Repetition Maximum: The Case of the Smith Machine Bench Press Exercise.

To compare the accuracy in the estimation of the Smith machine bench press 1-repetition maximum (1RM) when using a novel minimum velocity threshold (MVT) called optimal MVT (MVT that minimizes the differences between the actual and predicted 1RM in a preliminary session) with respect to using the 2 standard MVTs (general and individual MVTs). A total of 126 young men (Smith machine bench press 1RM = 80.7 [13.6]kg) completed 2 identical sessions consisting of an incremental loading test until reaching the 1RM load. Four individual load-velocity relationships were modeled in each session considering all loading conditions until reaching the load that showed the closest mean velocity to 0.60, 0.50, 0.40, and 0.30m·s-1. The first testing session was used to determine the preindividual MVT and 4 optimal MVTs (1 for each final test velocity), while the second testing session was used to estimate the 1RM using 4 types of MVT (general MVT, preindividual MVT, actual-individual MVT, and optimal MVT). The absolute errors in the prediction of the 1RM were significantly lower for the optimal MVT (2.94 [2.40]kg) compared to the general MVT (3.66 [2.99]kg), preindividual MVT (3.80 [3.15]kg), and actual-individual MVT (4.02 [3.21]kg). The optimal MVT (intraclass correlation coefficient [ICC] ranged from .56 to .62) was always more reliable than the individual MVT (ICC = .34). The optimal MVT provides more accurate estimates of the Smith machine bench press 1RM than the standard MVTs previously used in scientific research (general and individual MVTs).

Load–Velocity Relationship to Estimate the One-Repetition Maximum in the Hexagonal Bar Deadlift Exercise in Women

In this study, we examined the load–velocity relationship in the hexagonal bar deadlift exercise in women. Twenty-seven resistance-trained women were recruited. Participants performed a progressive load test up to the one-repetition maximum (1RM) load for determining the individual load–velocity relationship in the hexagonal bar deadlift exercise. Bar velocity was measured in every repetition through a linear encoder. A very strong and negative relationship was found between the %1RM and bar velocity for the linear (R2 = .94; standard error of the estimation = 5.43% 1RM) and second-order polynomial (R2 = .95) regression models. The individual load–velocity relationship provided even better adjustments (R2 = .98; coefficient of variation = 1.77%) than the general equation. High agreement level and low bias were found between actual and predicted 1RM for the general load–velocity relationship (intraclass correlation coefficient = .97 and 95% confidence interval [0.90, 0.99]; bias = −2.59 kg). In conclusion, bar velocity can be used to predict 1RM with high accuracy during hexagonal bar deadlift exercise in resistance-trained women.

Neuromuscular Fatigue and Metabolic Stress during the 15 Minutes of Rest after Carrying Out a Bench Press Exercise Protocol.

Simple SummaryVelocity loss can help to determine neuromuscular fatigue after carrying out an exercise protocol with a load that is initially moved at a mean propulsive velocity of 1 m·s−1. Few studies have measured the time required to recover the pre-exercise velocity values after performing an exercise, with the aim of knowing the optimal recovery times. Therefore, the aim of this study was to analyse muscular fatigue and metabolic stress during the 15 min that follow the execution of a bench press exercise protocol. The results show that mean propulsive velocity was recovered from minute 10 of rest; however, the blood lactate levels were still high (>5 mmol·L−1). Therefore, although the capacity to apply a maximum mean propulsive velocity peak was recovered, the same could not be said for the capacity to maintain those strength levels to reproduce another exercise protocol involving the same muscle groups. Moreover, analysing the velocities and metabolic stress before and after the exercise protocol by different strength level groups, similar results were obtained.Background: Velocity loss (VL) at 1 m·s−1 can help to determine neuromuscular fatigue after performing an exercise protocol. The aim of this study was to analyse muscle fatigue and metabolic stress during the 15 min that follow the execution of a bench press (BP) exercise protocol. Methods: Forty-four healthy male students of sports science performed two exercise sessions separated by one week of rest. In the first week, the participants carried out a test with progressive loads in the (BP) exercise until reaching the one-repetition maximum (1RM) in order to obtain the load–velocity relationship of each participant. In the second week, each participant conducted three BP exercise sets at an intensity of 70% of 1RM, determining this load through the mean propulsive velocity (MPV) obtained from the individual load–velocity relationship, with the participants performing the maximum number of repetitions (MNR) to muscle failure. Two minutes of rest were allocated between sets. MPV at 1 m·s−1 and blood lactate concentrations were recorded before executing the exercise and at minute 0, 5, 10 and 15 after performing the exercise protocol. Results: A two-factor repeated measures ANOVA was performed. MPV at 1 m·s−1 in minute 0 post-exercise was −33.3% (p < 0.05), whereas in minute 10 and 15 post-exercise, it was ≈−9% (p > 0.05). Regarding the blood lactate levels, significant differences were observed in all measurements before and after the exercise protocol (p < 0.001), obtaining ≈7 mmol·L−1 at minute 10 post-exercise and 4.3 mmol·L−1 after 15 min of recovery. Conclusions: MPV with medium or moderate loads shows a certain recovery from minute 10 of rest. However, the blood lactate levels are still high (>5 mmol·L−1). Therefore, although there seem to be certain conditions to reach a similar maximum MPV peak, the residual fatigue at the neuromuscular level and the non-recovery of metabolic homeostasis would hinder the reproduction of these protocols, both at the level of applied stimulus and from a methodological perspective, since a long recovery time would be required between sets and exercises.

Reproducibility and Applicability of Traditional Strength Training Prescription Recommendations.

Simple SummaryOne of the main problems that exercise professionals face is controlling and quantifying the real load of resistance training in an objective manner. Several authors have made recommendations aimed at improving strength for different populations. However, it is necessary to verify whether these recommendations can be implemented, completing them in their entirety. Therefore, the aim of this study was to verify the reproducibility of a resistance training protocol in the bench press exercise, based on traditional recommendations, analysing the effect of the muscle fatigue of each set and of the whole exercise protocol. Thirty participants performed a bench press exercise protocol of three sets with the maximum number of repetitions possible to muscle failure (with 2 min rests between sets), using a relative load corresponding to 70% 1RM determined through the mean propulsive velocity obtained from the individual load–velocity relationship. The conclusions of the study were that it was not possible to complete the same number of repetitions in each set for the same absolute load. Moreover, the level of fatigue generated through each set and its relationship with the capacity to recover in the established time could be different in each individual, showing an important coefficient of variation in each of the sets.Background: The aim of this study was to verify the reproducibility of a resistance training protocol in the bench press (BP) exercise, based on traditional recommendations, analysing the effect of the muscle fatigue of each set and of the whole exercise protocol. Methods: In this cross-sectional study, thirty male physical education students were divided into three groups according to their relative strength ratio (RSR), and they performed a 1RM BP test (T1). In the second session (T2), which was one week after T1, the participants performed a BP exercise protocol of three sets with the maximum number of repetitions (MNR) possible to muscle failure, using a relative load corresponding to 70% 1RM determined through the mean propulsive velocity (MPV) obtained from the individual load–velocity relationship, with 2 min rests between sets. Two weeks later, a third session (T3) identical to the second session (T2) was performed. The MPV of each repetition of each set and the blood lactate level after each set were calculated, and mechanical fatigue was quantified through the velocity loss percentage of the set (% loss MPV) and in a pre-post exercise test with an individual load that could be lifted at ~1 m·s−1 of MPV. Results: The number of repetitions performed in each set was significantly different (MNR for the total group of participants: set 1 = 12.50 ± 2.19 repetitions, set 2 = 6.06 ± 1.98 repetitions and set 3 = 4.20 ± 1.99 repetitions), showing high variation coefficients in each of the sets and between groups according to RSR. There were significant differences also in MPVrep Best (set 1 = 0.62 ± 0.10 m·s−1, set 2 = 0.42 ± 0.07 m·s−1, set 3 = 0.36 ± 0.10 m·s−1), which significantly reduced the % loss MPV of all sets (set 1 = 77.4%, set 2 = 64%, set 3 = 54.2%). The lactate levels increased significantly (p < 0.05) (set 1 = 4.9 mmo·L−1, set 2 = 6 mmo·L−1, set 3 = 6.5 mmo·L−1), and MPV loss at 1 m·s−1 after performing the three sets was 36% in T2 and 34% in T3, with acceptable intrasubject variability (MPV at 1 m·s−1 pre-exercise: SEM ≤ 0.09 m·s−1, CV = 9.8%; MPV at 1 m·s−1 post-exercise: SEM ≤ 0.07 m·s−1, CV = 11.7%). Conclusions: These exercise propositions are difficult to reproduce and apply. Moreover, the number of repetitions performed in each set was significantly different, which makes it difficult to define and control the intensity of the exercise. Lastly, the fatigue generated in each set could have an individual response depending on the capacity of each subject to recover from the preceding maximum effort.

Analysis of the Use and Applicability of Different Variables for the Prescription of Relative Intensity in Bench Press Exercise.

Simple SummaryThe aim of this research is to analyze the different variables that influence the prescription of resistance training (one-repetition maximum (1RM) and number of maximal repetitions (xRM)) through the velocity of execution, with the aim of approaching the precise definition and control of intensity in bench press exercise. Fifty male physical education students were divided into four groups according to their relative strength ratio (RSR) and performed a 1RM bench press test, and two maximum number of repetitions (MNR) tests one week apart, using a relative load corresponding to 70% 1RM determined through the mean propulsive velocity (MPV) obtained from the individual load–velocity relationship. Regarding MPV, the best (fastest) repetition of the set values were similar between groups (0.62 m·s−1–0.64 m·s−1). The average MNR was 12.38 ± 2.51, with significant variation between groups with regards to MNR (CV:13–29%), and greater variability in the group corresponding to the lowest RSR values (CV: 29%). The use of variables such as the 1RM or a MNR do not allow an adequate degree of precision to prescribe and control the relative intensity of resistance training. Besides, execution velocity control can offer an adequate alternative to guarantee an accurate prescription of intensity with regard to resistance training.Background: The aim of the study was to analyze the use of variables such as % of one-repetition maximum (1RM) and number of maximal repetitions (xRM) with execution velocity to define and control the intensity of resistance training in bench press exercise. Hence, exercise professionals will achieve better control of training through a greater understanding of its variables. Methods: In this cross-sectional study, fifty male physical education students were divided into four groups according to their relative strength ratio (RSR) and performed a 1RM bench press test (T1). In the second test, participants performed repetitions to exhaustion (T2), using a relative load corresponding to 70% 1RM determined through the mean propulsive velocity (MPV) obtained from the individual load–velocity relationship. This same test was repeated a week later (T3). Tests were monitored according to the MPV of each repetition and blood lactate values (LACT). Results: Regarding MPV, the best (fastest) repetition of the set (MPVrep Best) values were similar between groups (0.62 m·s−1–0.64 m·s−1), with significant differences in relation to the high RSR group (p < 0.001). The average maximum number of repetitions (MNR) was 12.38 ± 2.51, with no significant differences between the RSR groups. Nonetheless, significant variation existed between groups with regards to MNR (CV: 13–29%), with greater variability in the group corresponding to the lowest RSR values (CV: 29%). The loss of velocity in the MNR test in the different groups was similar (p > 0.05). Average LACT values (5.72 mmol·L−1) showed significant differences between the Medium RSR and Very Low RSR groups. No significant differences were found (p > 0.05) between T2 and T3 with regards to MNR, MPVrep Best, or MPVrep Last, with little variability seen between participants. Conclusions: The use of variables such as the 1RM, estimated using an absolute load value, or an MNR do not allow an adequate degree of precision to prescribe and control the relative intensity of resistance training. Besides, execution velocity control can offer an adequate alternative to guarantee an accurate prescription of intensity with regard to resistance training.

Validation of a novel method to assess maximal neuromuscular capacities through the load-velocity relationship

This study was designed to elucidate whether the assessment of the load-velocity relationship during the bench press throw exercise can be used as an indicator of the maximal capacity of upper-body muscles to produce force at low and high velocities as well as doing work at a maximal rate. Twenty-four resistance-trained men (bench press one-repetition maximum [1RM] relative to body mass = 1.14 ± 0.17) performed two incremental loading tests from 14 kg until the 1RM during the bench press throw exercise 7 days apart. Individual load-velocity relationships were modelled from the mean velocity values collected under all loading conditions and three variables were calculated from the individual load-velocity relationships: load-axis intercept (L0), velocity-axis intercept (v0), and area under the line (Aline = L0·v0/2). The bench press 1RM strength, peak velocity achieved against 14 kg (PV14kg), and the maximum power determined as the apex of the power-velocity relationship (Pmax) were also determined as traditional measures of maximal neuromuscular capacities. The three load-velocity relationship variables showed a very high reliability (CV ≤ 2.36%; ICC ≥ 0.86). Regarding the concurrent validity of the load-velocity relationship variables, nearly perfect correlations were observed between L0 and 1RM strength (r = 0.98) and between Aline and Pmax (r = 0.96), while lower correlations were observed between v0 and PV14kg (r = 0.59). These results highlight that the three maximal mechanical capacities of upper-body muscles can be quickly estimated through the assessment of the load-velocity relationship during the bench press throw exercise.

Level of Effort: A Reliable and Practical Alternative to the Velocity-Based Approach for Monitoring Resistance Training.

Hernández-Belmonte, A, Courel-Ibáñez, J, Conesa-Ros, E, Martínez-Cava, A, and Pallarés, JG. Level of effort: A reliable and practical alternative to the velocity-based approach for monitoring resistance training. J Strength Cond Res 36(11): 2992-2999, 2022-This study analyzed the potential of the level of effort methodology as an accurate indicator of the programmed relative load (percentage of one-repetition maximum [%1RM]) and intraset volume of the set during resistance training in the bench press, full squat, shoulder press, and prone bench pull exercises, through 3 specific objectives: (a) to examine the intersubject and intrasubject variability in the number of repetitions to failure ( n RM) against the actual %1RM lifted (adjusted by the individual velocity), (b) to investigate the relationship between the number of repetitions completed and velocity loss reached, and (c) to study the influence of the subject's strength level on the aforementioned parameters. After determining their individual load-velocity relationships, 30 subjects with low ( n = 10), medium ( n = 10), and high ( n = 10) relative strength levels completed 2 rounds of n RM tests against their 65, 75, 85, and 95% 1RM in the 4 exercises. The velocity of all repetitions was monitored using a linear transducer. Intersubject and intrasubject variability analyses included the 95% confidence intervals (CIs) and the the standard error of measurement ( SEM ), respectively. Coefficient of determination (R 2 ) was used as the indicator of relationship. n RM showed a limited intersubject (CI ≤ 4 repetitions) and a very low intrasubject ( SEM ≤1.9 repetitions) variability for all the strength levels, %1RM, and exercises analyzed. A very close relationship ( R2 ≥ 0.97) between the number of repetitions completed and the percentage of velocity loss reached (from 10 to 60%) was found. These findings strengthen the level of effort as a reliable, precise, and practical strategy for programming resistance training.

Monitoring Training Volume Through Maximal Number of Repetitions or Velocity-Based Approach.

This study aimed (1)to analyze the interindividual variability in the maximal number of repetitions (MNR) performed against a given relative load (percentage of 1-repetition maximum [%1RM]) and (2)to examine the relationship between the velocity loss (VL) magnitude and the percentage of completed repetitions with regard to the MNR (%Rep), when the %1RM is based on individual load-velocity relationships. Following an assessment of 1RM strength and individual load-velocity relationships, 14 resistance-trained men completed 5 MNR tests against loads of 50%, 60%, 70%, 80%, and 90% 1RM in the Smith machine bench-press exercise. The relative loads were determined from the individual load-velocity relationship. Individual relationships between load and velocity displayed coefficients of determination (R2) ranging from .986 to .998. The MNR showed an interindividual coefficient of variation ranging from 8.6% to 33.1%, increasing as the %1RM increased. The relationship between %Rep and the magnitude of VL showed a general R2 of .92 to .94 between 50% and 80% 1RM, which decreased to .80 for 90% 1RM. The mean individual R2 values were between .97 and .99 for all loading conditions. The %Rep when a given percentage of VL was reached showed interindividual coefficient of variation values ranging from 5% to 20%, decreasing as the %Rep increased in each load condition. Setting a number of repetitions had acceptable interindividual variability, with moderate relative loads being adjusted based on the individual load-velocity relationship. However, to provide a more homogeneous level of effort between athletes, the VL approach should be considered, mainly when using individual VL-%Rep relationships.

Effect of the Menstrual Cycle When Estimating 1 Repetition Maximum From the Load-Velocity Relationship During the Bench Press Exercise.

García-Pinillos, F, Lago-Fuentes, C, Bujalance-Moreno, P, and Pérez-Castilla, A. Effect of the menstrual cycle when estimating 1 repetition maximum from the load-velocity relationship during the bench press exercise. J Strength Cond Res 36(3): e55-e58, 2022-This study aimed to examine the effect of the ovulatory menstrual cycle (MC) when estimating the 1 repetition maximum (1RM) from the individual load-velocity relationship during the bench press (BP) exercise. Nine resistance-trained eumenorrheic women (age: 28.7 ± 3.6 years) were tested in 3 different phases across the MC: menstrual or early follicular phase (i.e., testing between days 1-3), follicular or late follicular phase (i.e., testing between days 7-10), and luteal or mid-luteal phase (i.e., testing between days 19-21). Each testing trial consisted of an incremental loading protocol against 4 loading conditions (≈50-70-80-90% 1RM) in the concentric-only BP exercise. A smartphone application (MyLift) was used to collect the mean velocity (MV) of all repetitions. The 1RM was estimated from the individual load-velocity relationship by applying a linear regression model as the load associated with an MV of 0.17 m·s-1. In addition, the MV obtained at each %1RM (i.e., from 20% 1RM to 80% 1RM in 20% increments), the load-velocity slope (i.e., the decrease in MV per each 1% of increment in the %1RM), and the y-intercept (i.e., the estimate of MV at 0% 1RM) were computed from the individual load-velocity relationships. No significant differences were observed between the 3 phases of the MC for any of the measured load-velocity relationship parameters (corrected p-value ≥0.495; effect size ≤0.24). The results suggest that the estimation of the BP 1RM from the load-velocity relationship seems not to vary over the 3 different phases of the MC (i.e., menstrual, follicular, and luteal phases).

Comparison of the bench press one-repetition maximum obtained by different procedures: Direct assessment vs. lifts-to-failure equations vs. two-point method

This study examined the differences in the bench press one-repetition maximum obtained by three different methods (direct method, lifts-to-failure method, and two-point method). Twenty young men were tested in four different sessions. A single grip width (close, medium, wide, or self-selected) was randomly used on each session. Each session consisted of an incremental loading test until reaching the one-repetition maximum, followed by a single set of lifts-to-failure against the 75% one-repetition maximum load. The last load lifted during the incremental loading test was considered the actual one-repetition maximum (direct method). The one-repetition maximum was also predicted using the Mayhew’s equation (lifts-to-failure method) and the individual load–velocity relationship modeled from two data points (two-point method). The actual one-repetition maximum was underestimated by the lifts-to-failure method (range: 1–2 kg) and overestimated by the two-point method (range: –3 to –1 kg), being these differences accentuated using closer grip widths. All predicted one-repetition maximums were practically perfectly correlated with the actual one-repetition maximum ( r ≥ 0.95; standard error of the estimate ≤ 4 kg). The one-repetition maximum was higher using the medium grip width (83 ± 3 kg) compared to the close (80 ± 3 kg) and wide (79 ± 3 kg) grip widths ( P ≤ 0.025), while no significant differences were observed between the medium and self-selected (81 ± 3 kg) grip widths ( P = 1.000). In conclusion, although both the Mayhew’s equation and the two-point method are able to predict the actual one-repetition maximum with an acceptable precision, the differences between the actual and predicted one-repetition maximums seem to increase when using close grip widths.

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

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. 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. 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] ≤ 4.46kg), whereas the accuracy of the PUSH (effect size = 0.70-0.83; r = .93-.94; SEE = 4.45-4.80kg), and especially the Beast Sensor (effect size = 0.36-0.84; r = .50-.68; SEE = 9.44-11.2kg), was lower. 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.

Using Load-Velocity Relationships to Quantify Training-Induced Fatigue.

Hughes, LJ, Banyard, HG, Dempsey, AR, Peiffer, JJ, and Scott, BR. Using load-velocity relationships to quantify training-induced fatigue. J Strength Cond Res 33(3): 762-773, 2019-The purpose of this study was to investigate using load-velocity relationships to quantify fluctuations in maximal strength (1 repetition maximum [1RM]), which occur as a result of training-induced fatigue. The 19 well-trained men (age: 24.3 ± 2.9 years, height: 180.1 ± 5.9 cm, body mass: 84.2 ± 10.5 kg, and squat 1RM: 151.1 ± 25.7 kg) who were recruited for this study attended 5 sessions. After baseline strength testing, individual load-velocity relationships were established using mean concentric velocity during visits 2, 4, and 5, with visit 3 consisting of a bout of fatiguing exercise (5 sets of squats performed to muscular failure with 70% 1RM). Predicted 1RM values were calculated using the minimal velocity threshold (1RMMVT), load at zero velocity (1RMLD0), and force-velocity (1RMFV) methods. Measured 1RM, maximal voluntary contractions, and perceived muscle soreness were used to examine the effects of fatigue in relation to the predicted 1RM scores. The 1RMMVT and 1RMLD0 demonstrated very strong and strong correlations with measured 1RM during each of the sessions (r = 0.90-0.96 and r = 0.77-0.84, respectively), while no strong significant correlations were observed for the 1RMFV. Further analysis using Bland-Altman plots demonstrated substantial interindividual variation associated with each method. These results suggest that load-velocity-based 1RM predictions are not accurate enough to be used for daily training load prescription, as has been previously suggested. Nevertheless, these predictions are practical to implement during an individual's warm-up and may be useful to indicate general fluctuations in performance potential, particularly if used in conjunction with other common monitoring methods.

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

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

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 load-velocity profile differs more between men and women than between individuals with different strength levels

This study aimed to determine the suitability of the load-velocity relationship to prescribe the relative load (%1RM) in women, as well as to compare the load-velocity profile between sexes and participants with different strength levels. The load-velocity relationship of 14 men (1RM: 1.17 ± 0.19) and 14 women (1RM: 0.66 ± 0.13) were evaluated in the bench press exercise. The main findings revealed that: (I) the load-velocity relationship was always strong and linear (R2 range: 0.987–0.993), (II) a steeper load-velocity profile was observed in men compared to women (Effect size [ES]: 1.09), with men showing higher velocities for light loads (ES: − 0.81 and − 0.40 for the y-intercept and 30%1RM, respectively), but women reporting higher velocities for the heavy loads (ES: 1.14 and 1.50 at 90%1RM and 100%1RM, respectively); and (III) while the slope of the load-velocity profile was moderately steeper for weak men compared to their strong counterpart (ES: 1.02), small differences were observed between strong and weak women (ES: − 0.39). While these results support the use of the individual load-velocity relationship to prescribe the %1RM in the bench press exercise for women, they also highlight the large disparities in their load-velocity profile compared to men.