Load-velocity Profiles Change after Training Programs with Different Set Configurations

Assessment of muscle function deterioration in aging populations: Insights from the load-velocity relationship during the loaded sit-to-stand test

Muscle power is a better indicator of musculoskeletal health and functional capacity than muscle strength. The Load-Velocity (L-V) relationship provides a method for assessing muscle function during dynamic multi-joint movements, making it valuable for identifying age-related neuromuscular decline. This study aimed to examine the relationship between variables derived from the L-V relationship (L0, V0, and Aline) obtained during the loaded sit-to-stand test and various muscle performance indices, including knee extension peak force (KEPF) and various muscle quality indices (MQI). A total of 113 participants (49 middle-aged adults and 64 older adults; age = 61 ± 9.92 years) performed the loaded 5-Sit-To-Stand using Functional Electromechanical Dynamometry. L-V variables were calculated, and their relationships with indicators of muscle performance and quality were analyzed. The impact of age on these variables was also evaluated. The results showed a high positive correlation between Aline and KEPF, MQIEquation1, MQIEquation2 and MQIEquation3 (rs = 0.56-0.59, p ≤0.001-0.01), and between V0 and KEFP (rs = 0.51, p < 0.001). Older adults exhibited significantly lower L0 compared to middle-aged adults (76.86 ± 29.74 kg vs. 94.62 ± 35.69 kg, p = 0.007), as well as lower V0 (0.92 ± 0.28 m·s-1 vs. 1.22 ± 0.19 m·s-1, p < 0.001) and Aline values (35.39 ± 18.95 kg·m·s-1 vs. 57.75 ± 23.84 kg·m·s-1, p < 0.001). These findings suggest that L-V variables are valuable indicators for assessing muscle function deterioration and guiding training interventions, providing a more comprehensive and sensitive assessment of muscle quality and functional status in aging populations.

Effects of Different Ranges of Loads on Physical Performance Using Velocity-Based Resistance Training

(1) Background: The range of loads is defined as the difference between the highest and the lowest relative load (i.e., %1RM) used throughout a resistance training program. However, the optimal range of loads has not been studied yet. Thus, the aim of this study was to compare the effects of different ranges of load (from 50 to 85% 1RM (R50-85), from 55 to 75% 1RM (R55-75), and from 60 to 70% 1RM (R60-70) on physical performance using velocity-based resistance training (VBT). (2) Methods: Thirty-eight men (mean ± standard deviation; age: 23.3 ± 3.6 years, body mass: 76.5 ± 8.3 kg, and height: 1.77 ± 0.04 m) were randomly assigned to R50-85, R55-75 and R60-70 groups and followed an 8-week VBT intervention using the full squat (SQ) exercise. All groups trained with similar mean relative intensity (65% 1RM) and total volume (240 repetitions). Pre- and post-training measurements included the following: in the SQ exercise, 1RM load, the average velocity attained for all absolute loads common to pre-tests and post-tests (AV), and the average velocity for those loads that were moved faster (AV > 1) and slower (AV < 1) than 1 m·s-1 at Pre-training tests. Moreover, countermovement jump (CMJ) height and 10 m (T10), 20 m (T20), and 10-20 m (T10-20) running sprint times were measured. (3) Results: Significant group x time interactions were observed in AV (p ≤ 0.01), where R50-85 obtained significantly greater gains than R60-70 (p ≤ 0.05). All groups attained significant increases in 1RM, AV, AV > 1, AV < 1, and CMJ (p ≤ 0.001-0.005). Significant improvements were observed in running sprint for R60-70 in T10-20 and R60-70 in T20 and T10-20 (p ≤ 0.05), but not for R50-85. (4) Conclusions: Different ranges of loads induce distinct strength adaptions. Greater ranges of loads resulted in greater strength gains in the entire load-velocity spectrum. However, in high-velocity actions, such as sprinting, significant enhancements were observed only for smaller ranges of loads. Coaches and strength and conditioning professionals could use a range of loads according to the time-related criterion (i.e., proximity or number of future competitions), enabling better adaptation and increasing physical performance at a specific time.

Cluster Versus Rest-Redistribution Training: Similar Improvements in Neuromuscular Capacities in Female Team-Sport Athletes

PURPOSE

This study's purpose was to investigate the midterm effects of alternative set configurations (cluster [CL] and rest redistribution [RR]) on lower- and upper-body neuromuscular capacities in female athletes.

METHOD

Twenty team-sport female athletes were randomly assigned to a CL (n = 10) or RR (n = 10) training group. The study protocol comprised 2 pretests, 12 training sessions, and a posttest. Both groups engaged in identical exercises (squat and bench press), load intensity (75% of 1-repetition maximum), and volume (18 repetitions per exercise). The distinction between the groups lay in the total session rest time: The CL group had 23 minutes (3 sets of 6 repetitions with 30 s of intraset rest every 2 repetitions and 3 min of interset rest), whereas the RR group had 17 minutes (9 sets of 2 repetitions with 45 s of interset rest). Countermovement-jump height and load-velocity relationship variables (load-intercept, velocity-intercept, and area under the load-velocity relationship line) were assessed during the squat and bench-press exercises.

RESULTS

All dependent variables revealed greater values at posttest compared with pretest (P ≤ .040; averaged Hedges g = 0.35 for CL and 0.60 for RR), but time × group interactions never reached statistical significance (P ≥ .144). Likewise, the comparison of the magnitude of changes between the 2 groups revealed only trivial differences, except for a small greater change in bench-press area under the load-velocity relationship line for RRG (Hedges g = 0.40).

CONCLUSIONS

RR is a more efficient strategy than CL for inducing strength gains in female athletes.

Comparative Effects of the Free Weights and Smith Machine Squat and Bench Press: The Important Role of Specificity for Strength Adaptations

PURPOSE

Although previous studies have compared strength-training adaptations between free weights (FW) and machine-guided exercises, those studies did not use a Smith machine (SM), which most closely replicates the exercises performed with FW. Thus, the aim of the present study was to investigate the chronic effects of strength-focused, velocity-based training regimens using FW versus SM.

METHODS

Thirty-seven sport-science students (14 female) were assigned, balanced by sex and relative strength, to either an FW or SM training group. The training program lasted 8 weeks (2 sessions/wk), and participants performed 4 sets per exercise (back squat and bench press) at 70% of their 1-repetition maximum with moderate effort levels (20%-25% velocity loss). Load-velocity profile parameters (load-axis intercept, velocity-axis intercept, and area under the load-velocity relationship line), cross-sectional areas of the vastus lateralis and pectoralis major muscles, and the number of repetitions to failure in the bench-press exercise were assessed before and after the training program. Mechanical variables were assessed using both FW and SM.

RESULTS

All variables, with the exception of back-squat velocity-axis intercept (P = .124), improved in both training groups. The changes in load-axis intercept and area under the load-velocity relationship line were more pronounced when the training and testing conditions matched. Failure in the bench-press exercise and cross-sectional areas of the vastus lateralis and pectoralis major showed comparable improvements for both training groups, while velocity-axis intercept tended to improve more in the SM group.

CONCLUSIONS

The general population, unconcerned with the specificity of strength adaptations, can choose a training modality (FW or SM) based on personal preferences.

Variability in the Relationship Between Velocity Loss and Percentage of Completed Repetitions During Horizontal Leg Press and Bench Press in Postmenopausal Women

ABSTRACT

Iglesias-Soler, E, Rial-Vázquez, J, Nine, I, Fariñas, J, Revuelta-Lera, B, and García-Ramos, A. Variability in the relationship between velocity loss and percentage of completed repetitions during horizontal leg press and bench press in postmenopausal women. J Strength Cond Res 38(9): 1576-1583, 2024-This study aimed to analyze the intersubject variability in the relationship between percentage of velocity loss (%VL) and percentage of repetitions performed out of maximum possible (%MNR) in postmenopausal women. Thirty-five postmenopausal active women (58 ± 3 years) performed sets leading to muscular failure, completing 10-13 repetitions, in both leg press (LP) and bench press (BP). Mean lift velocity of each repetition was expressed as a percentage of the fastest repetition, and repetitions were quantified as a percentage of the maximum number of repetitions completed in the set. Given the hierarchical structure of the data, %VL-%MNR relationships were fitted by linear mixed model regressions. A significant intersubject variability in the intercept (i.e., %MNR associated with 0%VL) was detected ( p < 0.001 in both LP and BP), even when centered values of the completed repetitions were included in the models. The estimated variance in the intercept for LP (117.39; SE : 45.41) was almost double that for BP (67.47; SE : 20.27). The variability observed in the intercept entailed variability in the estimated %MNR for specific %VL values. The use of velocity loss thresholds for estimating the intensity of effort in active postmenopausal women does not overcome uncertainty of more traditional methods.

Validation of a Single-Session Protocol to Determine the Load-Velocity Profile and One-Repetition Maximum for the Back Squat Exercise

ABSTRACT

Gomes, M, Fitas, A, Santos, P, Pezarat-Correia, P, and Mendonca, GV. Validation of a single session protocol to determine the load-velocity profile and one-repetition maximum for the back squat exercise. J Strength Cond Res 38(6): 1013-1018, 2024-We investigated whether a single session of absolute incremental loading is valid to obtain the individual load-velocity profile (LVP) and 1 repetition maximum (1RM) for the free-weight parallel back squat. Twenty strength-trained male subjects completed 3 testing sessions, including a baseline 1RM session and 2 LVP sessions (LVP rel based on incremental relative loads and LVP abs based on absolute load increments until 1RM). The 1RM load was compared between the baseline and LVP abs . The load at zero velocity (load-axis intercept [L 0 ]), maximal velocity capacity (velocity-axis intercept [V 0 ]), slope, and area under the load-velocity relationship line (A line ) were compared between the LVP rel and LVP abs using equivalence testing through 2 one-sided t -tests. Measurement accuracy was calculated using the absolute percent error. The 1RM measured at baseline and LVP abs was equivalent and presented a low absolute percent error (1.2%). The following LVP parameters were equivalent between LVP rel and LVP abs : 1RM, L 0 , and A line because the mean difference between sessions was close to zero and the Bland-Altman limits of agreement (1RM:5.3 kg; L 0 :6.8 kg; A line : 9.5 kg·m -1 ·s -1 ) were contained within the a priori defined ± equivalent margins (5% for 1RM and L 0 and 10% for A line ). The aforementioned variables presented a low absolute percent error. However, slope and V 0 were not equivalent between sessions. In conclusion, a single session of absolute incremental loading is a valid approach to obtain the L 0 and A line of the individual LVP and 1RM, and can be used to efficiently track the magnitude of neuromuscular adaptations throughout the training cycles for the free-weight back squat.

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.

Effects of 4 Different Velocity-Based Resistance-Training Programming Models on Physical Performance

PURPOSE

To examine the effects of 4 programming models (linear [LP], undulating [UP], reverse [RP], and constant [CP]) on physical performance.

METHODS

Forty-eight moderately strength-trained men were randomly assigned to LP, UP, RP, and CP groups according to their 1-repetition maximum (1RM) in the full-squat exercise (SQ) and followed an 8-week training intervention using the SQ and monitoring movement velocity for every repetition. All groups trained with similar mean relative intensity (65% 1RM), number of repetitions (240), sets (3), and interset recovery (4 min) throughout the training program. Pretraining and posttraining measurements included, in the SQ, 1RM load, the average velocity attained for all absolute loads common to pretests and posttests (AV), and the average velocity for loads that were moved faster (AV > 1) and slower (AV < 1) than 1 m·s-1 at pretraining tests. Moreover, countermovement jump height and 20-m running sprint time were measured.

RESULTS

A significant time effect was found for all variables analyzed (P < .05), except for 20-m running sprint time. Significant group × time interactions were observed for 1RM, AV > 1, and AV (P < .05). After training, all groups attained significant strength gains on 1RM, AV, AV > 1, and AV < 1 (P < .001-.01). LP and RP groups improved their countermovement jump height (P < .01), but no significant changes were observed for UP and CP. No significant improvements were achieved in 20-m running sprint time for any groups.

CONCLUSIONS

These different programming models are all suitable for improving physical performance. LP and RP induce similar or greater gains in physical performance than UP and CP.

WORKLOAD CHARACTERISTICS IN THE FITNESS TRAINING OF CHINESE ATHLETES

ABSTRACT Introduction: In modern gymnastics, there are high demands for the physical quality of Chinese athletes. Objectives: This paper mainly studies whether the workload of Chinese gymnasts can support the corresponding high-intensity training in the training process. Methods: Experimental scientific research methods and statistical analysis are used to conduct a long-term study on dozens of gymnasts in Chinese schools and draw the workload curves of these gymnasts during gymnastic exercises. We try to determine the effective correlation between the athlete's body load and physical training and body shape. Results: During the training of gymnasts, heart rates can briefly exceed 190 beats per minute. Conclusion: In the training process of different gymnasts, the gymnasts’ heart rates show obvious differences. Therefore, the use of scientific and reasonable training strategies can effectively improve the ability of athletes’ hearts to withstand high-intensity exercise loads and help improve the gymnast's performance. Level of evidence II; Therapeutic studies - investigation of treatment results.

Strength and Athletic Adaptations Produced by 4 Programming Models: A Velocity-Based Intervention Using a Real-Context Routine

PURPOSE

To compare the strength and athletic adaptations induced by 4 programming models.

METHODS

Fifty-two men were allocated into 1 of the following models: linear programming (intensity increased while intraset volume decreased), undulating programming (intensity and intraset volume were varied in each session or set of sessions), reverse programming (intensity decreased while intraset volume increased), or constant programming (intensity and intraset volume kept constant throughout the training plan). All groups completed a 10-week resistance-training program made up of the free-weight bench press, squat, deadlift, prone bench pull, and shoulder press exercises. The 4 models used the same frequency (2 sessions per week), number of sets (3 per exercise), interset recoveries (4 min), and average intensity throughout the intervention (77.5%). The velocity-based method was used to accurately adjust the planned intensity for each model.

RESULTS

The 4 programming models exhibited significant pre-post changes in most strength variables analyzed. When considering the effect sizes for the 5 exercises trained, we observed that the undulating programming (mean effect size = 0.88-2.92) and constant programming (mean effect size = 0.61-1.65) models induced the highest and lowest strength enhancements, respectively. Moreover, the 4 programming models were found to be effective to improve performance during shorter (jump and sprint tests) and longer (upper- and lower-limb Wingate test) anaerobic tasks, with no significant differences between them.

CONCLUSION

The linear, undulating, reverse, and constant programming models are similarly effective to improve strength and athletic performance when they are implemented in a real-context routine.

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

AbstractThis 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 [L₀], velocity-axis intercept [v₀], 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]). L₀ and A_line were always higher for O16 than for U16 (p ≤ 0.046; ES range = 0.99 to 1.79), while v₀ was generally comparable for both age categories (p ≥ 0.038; ES range = 0.07 to 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.

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

BACKGROUND

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.

HYPOTHESIS

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.

STUDY DESIGN

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 OF EVIDENCE

Level 3.

METHODS

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 (A_line = L₀·v₀/2). The back-squat 1RM strength and the maximum power determined as the apex of the power-velocity relationship (P_max) were also determined as traditional measures of maximal force and power capacities, respectively.

RESULTS

The between-session reliability was high for the A_line (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 (r_range = 0.87-0.88) and nearly perfect between A_line and P_max (r = 0.98-0.99).

CONCLUSION

The load-velocity relationship variables can be obtained with a high reliability (L₀, v₀, and A_line) and validity (L₀ and A_line) during the back-squat exercise.

CLINICAL RELEVANCE

The load-velocity relationship modeling represents a quick and simple procedure to estimate the maximal neuromuscular capacities of lower-body muscles.

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

PURPOSE

This 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.

METHODS

Twenty 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 (load_0.55). The L-V relationship variables (load-axis intercept (L₀), velocity-axis intercept (v₀), and area under the L-V relationship line (A_line)) were obtained using 3 velocity variables (MV, mean propulsive velocity (MPV), and peak velocity) by the multiple-point method including (20-40-60-80-load_0.55) and excluding (20-40-60-80) the heavy squat, as well as from their respective 2-point methods (20-load_0.55 and 20-80).

RESULTS

The 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 (CV_ratio (calculated as higher value/lower value): 1.11-1.12), but the multiple-point method provided A_line with a greater reliability (CV_ratio = 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 (CV_ratio: 1.06-1.19). The peak velocity provided the load-velocity relationship variables with the greatest reliability (CV_ratio: 1.15-1.86) followed by the MV (CV_ratio: 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).

CONCLUSION

The 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.