Load-velocity Relationship Research Articles

Using the bar-velocity to predict the one-repetition maximum in the power clean from the knee

This study investigated the predictive validity and reliability of the load-velocity relationship with the one-repetition maximum test (1RM) in power clean from the knee exercise (PC). Initially, 12 healthy young males, with no PC experience, underwent eight sessions to learn the PC technique. After the learning period, the participants visited the laboratory on four more occasions with intervals between the visits from 72 to 96 h. The first two sessions were dedicated to the actual 1RM tests, while the last two sessions were performed to measure the barbell’s load-velocity relationship at 30%, 45%, 60%, 75%, and 90% of PC 1RM. The highest peak velocity recorded at each load was used to establish the linear regression equation and, consequently, to predict 1RM values. As a result, a low validity was observed between the highest actual 1RM value and the predicted 1RM in sessions 1 and 2 (typical errors = 3.6 to 5.0 kg, coefficients of variation = 6.03 to 8.21%, effect sizes = -1.23 to -1.00, and Bland-Altman bias = 8.5 to 11.7 kg). For reliability, higher measurement errors (intraclass correlation coefficient, typical error, coefficient of variation, and width of limits of agreement at 95%) were observed for the predicted 1RM compared to the actual 1RM test. In conclusion, the load-velocity relationship was not able to predict the 1RM value with high accuracy in the PC from the knee. Moreover, the predicted 1RM presented inferior reliability than the actual 1RM test.

The load-velocity relationship in the jump squat exercise.

The purpose of this study was to test the load-velocity relationship in the jump squat (JS) exercise using three different velocity parameters (mean velocity [MV], mean propulsive velocity [MPV], and peak velocity [PV]). Twenty-six male rugby union players (24.3 ± 3.9 years; 1.81 ± 0.09 m; 101.3 ± 15.4 kg) performed a progressive loading test in the JS with loads corresponding to 20, 40, 60, and 80% of the half-squat 1RM (equivalent to 24, 46, 70, and 94% of the estimated JS-1RM). MV, MPV, and PV were continuously recorded during all attempts using a linear velocity transducer. Linear regression models were used to determine the relationships between JS loads and MV, MPV, and PV. Bar-velocity outputs demonstrated high levels of consistency and reliability (coefficient of variation ≤ 5% and intraclass correlation coefficient ≥ 0.90). The predictive power of MV, MPV, and PV were ≥ 91%, for all tested variables (P < 0.0001). The equations and bar-velocity values provided in this study can be used by coaches to precisely determine and prescribe JS training loads, from verylight to heavy loading conditions (i.e., ~20-100% JS 1RM).

Free weight training vs. elastic band training

The aim of this study was to assess the effectiveness of two resistance training (RT) programs (free weight [FW] and elastic band [EB]) on velocity variables (handball throwing velocity [HTV] and maximal theoretical velocity [V0]) using load-velocity (L-V) relationship modelling. Both programs lasted 6 weeks and consisted of performing bench press and overarm dumbbell pull-over using free weights (FW group) or elastic bands (EB group). Nineteen male sports science students were randomly assigned to EB (n=10) or FW group (n=9). Both RT programs increased HTV and V0, although the increment was greater in the FW (&amp;gt;2 m·s-1) compared to the EB group (&amp;lt;1 m·s-1). RT programs had selective effects on the strength variables being FW more effective in increasing 1-repetition maximum, while EB in increasing maximal isometric force. Very large correlations were observed between two-point (L-V relationship modelled through two pairs of L and V data) and multiple-point methods (L-V relationship modelled through six pairs of L and V data) (V0: r=0.96; HTV: r=0.93). All coefficients of variation showed high validity both for V0 and HTV (≤6.2%). Altogether, FW training should be used for increasing the velocity of the throwing performance, while the two-point method for following training-induced changes.

Modeling and Simulation of Electric Thrust Reverser Actuator Control Based on Simulink

According to the structural characteristics and working principle of the electric actuator system of the aircraft thrust reverser, the mathematical control model of the thrust reverser actuator is proposed for a certain type of electric thrust reverser actuator system. The model is established and simulated by the modular modeling method based on Simulink software. The actuator’s load force, transmission, displacement, and velocity relationship are analyzed. The simulation results show that the model can simulate the deployment and stow of the actuator under different conditions and provide a platform for the control logic design, force analysis, and fault diagnosis of the electric thrust reverse actuator system.

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.

Specific Adaptations to 0%, 15%, 25%, and 50% Velocity-Loss Thresholds During Bench Press Training.

To compare the effect of 4 velocity-loss (VL) thresholds-0% (VL0), 15% (VL15), 25% (VL25), and 50% (VL50)-on strength gains, neuromuscular adaptations, and muscle hypertrophy during the bench press (BP) exercise using intensities ranging from 55% to 70% of 1-repetition maximum (1RM). Fifty resistance-trained men were randomly assigned to 4 groups that followed an 8-week (16 sessions) BP training program at 55% to 70% 1RM but differed in the VL allowed in each set (VL0, VL15, VL25, and VL50). Assessments performed before (pre) and after (post) the training program included (1)cross-sectional area of pectoralis major muscle, (2)maximal isometric test, (3)progressive loading test, and (4)fatigue test in the BP exercise. A significant group × time interaction was found for 1RM (P = .01), where all groups except VL0 showed significant gains in 1RM strength (P < .001). The VL25 group attained the greatest gains in 1RM strength and most load-velocity relationship parameters analyzed. A significant group × time interaction was observed for EMG root mean square in pectoralis major (P = .03) where only the VL25 group showed significant increases (P = .02). VL50 showed decreased EMG root mean square in triceps brachii (P = .006). Only the VL50 group showed significant increases in cross-sectional area (P < .001). These findings indicate that a VL threshold of about 25% with intensities from 55% to 70% 1RM in BP provides an optimal training stimulus to maximize dynamic strength performance and neuromuscular adaptations, while higher VL thresholds promote higher muscle hypertrophy.

Effect of intra-session exercise sequence on the load–velocity relationship variables after a concurrent sprint interval and resistance training program

This study aimed to examine the effects of altering the intra-session exercise sequence of a concurrent training program on the load–velocity relationship variables obtained from different compound exercises. Physically active subjects ( n = 24, age = ∼21 years) were assigned to one group that performed sprint interval training (sprints: 4–6; intensity: all-out; duration: 30 s; rest: 4 min) followed by resistance training (exercises: back squat and bench press; sets per exercise: 4–6; load: 60–80% of the one-repetition maximum; repetition in reserve: 6–1; rest: 2 min) (SIT + RT) or another group that performed the opposite sequence (RT + SIT). Exercises modes were separated by 10 min. Both groups trained three times per week over an eight-week period. The individualized load–velocity relationships were assessed before and after training through an incremental loading test during the back squat and bench press exercises and three variables were subsequently calculated: load-axis intercept ( L0), velocity-axis intercept ( v0), and area under the line ( Aline = L0⋅ v0/2). Regardless of exercise sequence, both groups increased L0 (ES range = 0.78–0.91) and Aline (ES range = 0.50–0.55) but decreased v0 (ES range = −0.36 to −0.46) during the back squat exercise, while all load–velocity relationship variables were increased (ES range = 0.04–2.20) during the bench press exercise. The SIT + RT group showed a moderately greater bench press v0 increase compared to the RT + SIT group (ES = −1.07). These results indicate that both intra-session exercise sequences can induce comparable improvements in the load–velocity relationship variables after an eight-week concurrent training program.

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.

Evaluation of load-velocity relationships in the inclined leg press exercise: A comparison between genders

The objectives of this study were threefold: (i) to analyze the load-velocity relationships between mean propulsive velocity (MPV), mean velocity (MV), peak velocity (PV), and relative load during the inclined leg press exercise; (ii) to analyze the differences in the load-velocity relationships between males and females; and (iii) to determine gender-specific predictive equations for loads between 50%–100% one-repetition maximum (1RM) in a population of trained young college students. The load-velocity relationships of 15 males and 13 females were explored through a progressive loading test, up to the individual 1RM load. Gender-specific load-velocity relationships were plotted along with the individual relationships. High to very high associations were found for gender-specific load-MPV and load-MV relationships, whereas load-PV presented moderate associations. The gender-specific load-velocity relationships in males were steeper than in females for MPV, MV and PV. However, individual load-velocity relationships presented higher associations than gender-specific relationships for all subjects. Finally, the predicted velocity outcomes for each %1RM load were always significantly higher in males than in females, except for PV at 95% and 100% 1RM load. Taken collectively, the findings from the present study support the application of subject-specific and gender-specific load-velocity relationships, highlighting the disparities between male and female relationships. Les objectifs de cette étude étaient triples : (i) analyser les relations force vitesse entre la vitesse de propulsion moyenne (MPV), la vitesse moyenne (VM), la vitesse de pointe (PV) et la charge relative pendant l’exercice de presse a cuisses inclinée ; (ii) analyser les différences dans les relations force-vitesse entre les hommes et les femmes ; et (iii) déterminer des équations prédictives spécifiques à chaque sexe pour des charges comprises entre 50 % et 100 % maximum d’une répétition (1RM) dans une population de jeunes étudiants entraînés. Les relations force-vitesse de 15 garçons et 13 filles ont été examinées grâce à un test de charge progressive, jusqu’à la charge individuelle 1RM. Les relations force-vitesse spécifiques au sexe ont été comparée aux relations individuelles. Des associations élevées à très élevées ont été trouvées pour les relations charge-MPV et charge-VM spécifiques au sexe, tandis que charge-PV présentait des associations modérées. Les relations force-vitesse spécifiques au sexe chez les hommes présentaient une pente plus prononcée que chez les femmes pour MPV, MV et PV. Cependant, les relations charge-vitesse individuelles présentaient des associations plus élevées que les relations spécifiques au sexe pour tous les sujets. Enfin, les résultats de vitesse prédits pour chaque charge %1RM étaient toujours significativement plus élevés chez les hommes que chez les femmes, à l’exception de PV à 95 % et 100 % de charge 1RM. Au total, les résultats de la présente étude plaident pour l’utilisation de relations force-vitesse personnalisées en fonction des caractéristiques du sujet et de son sexe, montrant une différence nette entre garçons et filles.

Association of the load-velocity relationship variables with 2000-m rowing ergometer performance

ABSTRACT This study aimed to compare the maximal mechanical variables derived from the load-velocity (L-V) relationship and 2000-meter rowing ergometer performance between rowers of different age categories, and to identify the L-V relationship variables more closely related to 2000-meter rowing ergometer performance. Nineteen competitive rowers (15 males and four females) aged between 15 and 25 years were evaluated during the national 2000-meter rowing ergometer competition organised by the Chilean Rowing Federation. Thereafter, the L-V relationship variables (load-axis intercept [L 0], velocity-axis intercept [v 0], and area under the L-V relationship line [A line]) were determined on separate occasions during the squat jump and prone bench pull exercises. Rowers were classified according to their chronological age for comparative purposes (under 16 years [U16] vs. over 16 years [O16]). L 0 and A line were always higher for O16 than for U16 (p ≤ 0.046; ES range = 0.99–1.79), while v 0 was generally comparable for both age categories (p ≥ 0.038; ES range = 0.07–1.03). Furthermore, the O16 revealed a greater performance (i.e. shorter total time) during the 2000-meter rowing ergometer competition (p = 0.011; ES = −1.31). In general, significant correlations were obtained between rowing performance and the L-V relationship variables obtained during the squat jump (r or ρ range = −0.294 to −0.922) and prone bench pull (r or ρ range = −0.322 to −0.928). These results support the L-V relationship as a sensitive procedure to evaluate the maximal mechanical capacities of lower- and upper-body muscles in competitive rowers. Highlights The load-velocity relationship variables are sensitive enough to differentiate between rowers of different age categories (U16 vs. O16). The load-velocity variables are significantly associated with 2000-meter rowing ergometer performance (total time). This novel testing methodology can provide practitioners and coaches with a simpler and more precise alternative to comprehensively assess a rower's maximal neuromuscular profiles.

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.

Velocity-Based Resistance Training in Soccer: Practical Applications and Technical Considerations

ABSTRACT Since 2010, the velocity-based approach (VBT) has been established as a reliable method to be used during resistance training (RT) interventions. VBT lies in the monitoring of the barbell velocity during the concentric phase of an exercise, which is a direct consequence of the force applied by the athlete to the external load. VBT offers coaches and physical trainers of soccer teams a wide spectrum of practical applications. Considering the close association between the barbell velocity and the relative intensity (i.e., load-velocity relationship), practitioners could ensure “on the go” that players train very close to the programmed load in each training set. Methodologies derived from the VBT, such as the velocity loss or the “level of effort,” allow to plan and control the intraset fatigue to be incurred by the soccer players during RT. Incorporating the barbell velocity monitoring into the testing routine would permit the determination of the changes in strength across the entire spectrum of loads and offer a valid and practical proposal to evaluate the neuromuscular recovery status. The current article aimed to review in-depth the above-mentioned practical applications and some technological and technical aspects to consider when implementing the VBT in soccer.

Load-Velocity Relationship Variables to Assess the Maximal Neuromuscular Capacities During the Back-Squat Exercise.

The relationship between the external load lifted and movement velocity can be modeled by a simple linear regression, and the variables derived from the load-velocity (L-V) relationship were recently used to estimate the maximal neuromuscular capacities during 2 variants of the back-squat exercise. The L-V relationship variables will be highly reliable and will be highly associated with the traditional tests commonly used to evaluate the maximal force and power. Twenty-four male wrestlers performed 5 testing sessions (a 1-repetition maximum [1RM] session, and 4 experimental sessions [2 with the concentric-only back-squat and 2 with the eccentric-concentric back-squat]). Each experimental session consisted of performing 3 repetitions against 5 loads (45%-55%-65%-75%-85% of the 1RM), followed by single 1RM attempts. Level 3. Individual L-V relationships were modeled from the mean velocity collected under all loading conditions from which the following 3 variables were calculated: load-axis intercept (L0), velocity-axis intercept (v0), and area under the line (Aline = L0·v0/2). The back-squat 1RM strength and the maximum power determined as the apex of the power-velocity relationship (Pmax) were also determined as traditional measures of maximal force and power capacities, respectively. The between-session reliability was high for the Aline (coefficient of variation [CV] range = 2.58%-4.37%; intraclass correlation coefficient [ICC] range = 0.98-0.99) and generally acceptable for L0 and v0 (CV range = 5.08%-9.01%; ICC range = 0.45-0.96). Regarding the concurrent validity, the correlations were very large between L0 and the 1RM strength (rrange = 0.87-0.88) and nearly perfect between Aline and Pmax (r = 0.98-0.99). The load-velocity relationship variables can be obtained with a high reliability (L0, v0, and Aline) and validity (L0 and Aline) during the back-squat exercise. The load-velocity relationship modeling represents a quick and simple procedure to estimate the maximal neuromuscular capacities of lower-body muscles.

Using the Load-Velocity Profile for Predicting the 1RM of the Hexagonal Barbell Deadlift Exercise.

Lopes dos Santos, M, Mann, JB, Berton, R, Alvar, B, Lockie, RG, and Dawes, JJ. Using the load-velocity profile for predicting the 1RM of the hexagonal barbell deadlift exercise. J Strength Cond Res 37(1): 220-223, 2023-The aim of this study was to determine whether bar velocity can be used to estimate the 1 repetition maximum (1RM) on the hexagonal bar deadlift (HBD). Twenty-two National Collegiate Athletic Association Division I male ice hockey players (age = 21.0 ± 1.5 years, height = 182.9 ± 7.3 cm, and body mass = 86.2 ± 7.3 kg) completed a progressive loading test using the HBD at maximum intended velocity to determine their 1RM. The mean concentric velocity was measured for each load through a linear position transducer. The a priori alpha level of significance was set at p = 0.05. The mean concentric velocity showed a very strong relationship to %1RM (R2 = 0.85). A nonsignificant difference and a trivial effect size (ES) were observed between the actual and predicted 1RM (p = 0.90, ES = -0.08). Near-perfect correlations were also discovered between the actual and predicted 1RM (R = 0.93) with low typical error and coefficient of variation (5.11 kg and 2.53%, respectively). This study presented results that add the HBD to the list of exercises with established load-velocity relationships. The predictive ability for 1RM HBD indicates that this is a viable means of prediction of 1RM.

Development of Multi-purpose Resistance Training Device and 1RM Estimation based on Load-Velocity Relationship

Development of Multi-purpose Resistance Training Device and 1RM Estimation based on Load-Velocity Relationship

Feasibility of the 2-point method to determine the load−velocity relationship variables during the countermovement jump exercise

PurposeThis study aimed to examine the reliability and validity of load−velocity (L–V) relationship variables obtained through the 2-point method using different load combinations and velocity variables. MethodsTwenty men performed 2 identical sessions consisting of 2 countermovement jumps against 4 external loads (20 kg, 40 kg, 60 kg, and 80 kg) and a heavy squat against a load linked to a mean velocity (MV) of 0.55 m/s (load0.55). The L–V relationship variables (load-axis intercept (L0), velocity-axis intercept (v0), and area under the L–V relationship line (Aline)) were obtained using 3 velocity variables (MV, mean propulsive velocity (MPV), and peak velocity) by the multiple-point method including (20–40–60–80–load0.55) and excluding (20–40–60–80) the heavy squat, as well as from their respective 2-point methods (20–load0.55 and 20–80). ResultsThe L–V relationship variables were obtained with an acceptable reliability (coefficient of variation (CV) ≤ 7.30%; intra-class correlation coefficient ≥ 0.63). The reliability of L0 and v0 was comparable for both methods (CVratio (calculated as higher value/lower value): 1.11–1.12), but the multiple-point method provided Aline with a greater reliability (CVratio = 1.26). The use of a heavy squat provided the L–V relationship variables with a comparable or higher reliability than the use of a heavy countermovement jump load (CVratio: 1.06–1.19). The peak velocity provided the load–velocity relationship variables with the greatest reliability (CVratio: 1.15–1.86) followed by the MV (CVratio: 1.07–1.18), and finally the MPV. The 2-point methods only revealed an acceptable validity for the MV and MPV (effect size ≤ 0.19; Pearson's product-moment correlation coefficient ≥ 0.96; Lin's concordance correlation coefficient ≥ 0.94). ConclusionThe 2-point method obtained from a heavy squat load and MV or MPV is a quick, safe, and reliable procedure to evaluate the lower-body maximal neuromuscular capacities through the L–V relationship.

Uphill sprinting load– and force–velocity profiling: Assessment and potential applications

ABSTRACT This study aimed to quantify the validity and reliability of load–velocity (LV) relationship of hill sprinting using a range of different hill gradients and to describe the effect of hill gradient on sprint performance. Twenty-four collegiate-level athletes performed a series of maximal sprints on either flat terrain or hills of gradients 5.2, 8.8 and 17.6%. Velocity–time curves were recorded using a radar device. LV relationships were established using the maximal velocity achieved in each sprinting condition, whilst force–velocity–power (FVP) profiles were established using only the flat terrain sprint. LV profiles were shown to be valid (R2 = 0.99) and reliable (TE < 4.4%). For every 1-degree increase in slope, subjects’ velocity decreased by 1.7 ± 0.1% on average. All the slopes used represented low resistance relative to the entire LV spectrum (<25% velocity loss). Subjects who exhibited greater horizontal force output at higher velocities on flat terrain were most affected by the gradient of the hill. Hills of gradients up to 17.6% do not provide sufficient resistance to optimize power development. However, such hills could be used to develop late-stage technical ability, due to the prolonged horizontally oriented body position that occurs as subjects attempt to overcome the acceleration due to gravity.

Relationship between Swimming Performance, Biomechanical Variables and the Calculated Predicted 1-RM Push-up in Competitive Swimmers.

One repetition maximum (1RM) push-ups, based upon the load–velocity relationship, are able to predict the maximum upper body strength. The aim of the present study was to examine the relationship between the predicted 1RM push-up based upon the load–velocity relationship and swimming performance and kinematical variables in competitive swimmers. Thirty-three competitive male swimmers (age = 16.46 ± 0.59 years, body mass = 72.82 ± 8.41 kg, body height = 180.56 ± 5.69 cm) performed push-up exercises without a weight vest and with a 10, 20 and 30 kg weight vests. A load–velocity relationship was established as a product of the load and velocity of the push-up per participant, and the equation was used to establish a predicted 1RM. Our findings showed a predicted 1RM push-up of 82.98 ± 9.95 kg. Pearson correlations revealed a nearly perfect relationship between the 1RM push-up and the 25 or 50 m front crawl (r = −0.968, r = −0.955), and between 1RM push-up and the 25 or 50 m front crawl with arms (r = −0.955, r = x0.941). Similarly, our results revealed significant near-perfect correlations between 1RM push-up and kinematical variables (r = 0.93–0.96) except the stroke index, which had a large relationship (r = 0.56). This study suggests that swimming performance and kinematical variables are correlated with the predicted 1RM push-up. The 1RM push-up based upon the load–velocity relationship is a low cost and time-effective alternative for swimmers and coaches to predict maximum upper body strength to optimize swimming performance in short races.

Load-Velocity Relationship in Bench Press and Effects of a Strength-Training Program in Wheelchair Basketball Players: A Team Study.

Performance in wheelchair basketball is determined by capabilities, such as strength and power. The study has two aims: first, to analyze the association between speed and acceleration variables (collected in the bench press (BP) exercise) and the distinct percentages of one-repetition maximum (1RM); second, to analyze the effect of a strength training protocol on wheelchair basketball (WB) players according to their functional impairments. Ten Spanish male WB players volunteered to participate in the study. The players did a pretest and posttest (1RM in bench press) with 6-week muscle strength intervention program. The results showed a high association between the %1RM and the mean propulsive velocity (MPV) and the maximum velocity (Vmax), both in the total of the participants, and in each separate group of athletes. After implementing the strength training program, both the players of the IWBF (International Wheelchair Basketball Federation) < 2.5 group and those of IWBF > 2.5 group improved their 1RM (p < 0.01, ES = 0.20 to 0.23). However, the program produced positive effects at submaximal intensities in the MPV reached with 30, 40, 70, and 80 kg and in time to maximum velocity (TVmax) with 30, 40, and 70 kg (ES = −3.24 to 1.32) only in players with greater functional impairments. The high association between %1RM and MPV and Vmax can allow for determination the %1RM of the WB players in the BP using the MPV and the Vmax. The training program was effective in improving 1RM in both groups, while improvements in submaximal values only occurred in the IWBF < 2.5 group.