Jump peak power assessment through power prediction equations in different samples

The relationship between lower limb muscle volume and peak vertical jump power in children

BACKGROUND: Vertical jump is an index representing leg power. It is important to determine factors that influence the vertical jump to help athletes improve their leg power. OBJECTIVE: This study aimed to determine the relationship between lower limbs muscle volume and peak vertical jump (VJ) power in children for both sexes. METHODS: Fourty children healthy boys (n= 20) and girls (n= 20) aged 10 to 12 years old, randomly performed three VJ modalities: squat jump (SJ), counter movement jump without (CMJ) and with arm swings (CMJarms). Lower limbs muscle volume (MV) estimated using a standard anthropometric method. Peak power (PP) calculated by Sayers equation. RESULTS: significant correlations between MV and Peak vertical jump power showed for both sexes. Likewise, significant correlations were found between MV and body mass for boys (r= 0.66; p= 0.001) and for girls (r= 0.59; p= 0.006). CONCLUSIONS: The correlation observed between peak vertical jump power and MV in both sexes can be considered as estimation tool of the lower limbs muscle power. Lower limb’s muscle volume are determining factor in muscle power for both sexes.

Potential Energy as an Alternative for Assessing Lower Limb Peak Power in Children: A Bayesian Hierarchical Analysis

The aim of this study was to analyze the use of potential energy (PE) as an alternative method to assess peak power of the lower limbs (PP) in children. 815 Spanish children (416 girls; 6–11 years old; Body Mass Index groups (n): underweight = 40, normal weight = 431, overweight = 216, obese = 128) were involved in this study. All participants performed a Countermovement Jump (CMJ) test. PP was calculated using Duncan (PP_DUNCAN), Gomez-Bruton (PP_GOMEZ) and PE_CMJ formulas. A model with PE_CMJ as the predictor variable showed a higher predictive accuracy with PP_DUNCAN and PP_GOMEZ than CMJ height (R² = 0.99 and 0.97, respectively; ELPD_diff = 1037.0 and 646.7, respectively). Moreover, PE_CMJ showed a higher linear association with PP_DUNCAN and PP_GOMEZ across BMI groups than CMJ height (β_PECMJ range from 0.67 to 0.77 predicting PP_DUNCAN; and from 0.90 to 1.13 predicting PP_GOMEZ). Our results provide further support for proposing PE_CMJ as an index to measure PP of the lower limbs, taking into account the children’s weight and not only the height of the jump. Therefore, we suggest the use of PE_CMJ in physical education classes as a valid method for estimating PP among children when laboratory methods are not feasible.

The Effects of Tai Chi Chuan Exercise Training on the Lower Extremities of Middle-Aged and Elderly

Background: It is known that lower-limb muscle strength is easily maintained in elderly people who practice Tai Chi, although it is necessary to maintain lower-limb muscle strength even as age increases in order to prevent falls. However, the effect of long-term Tai Chi practice and age on lower-limb ability is unclear in middle-aged and elderly people. This research was designed to compare lower-extremity parameters during a countermovement jump between middle-aged and elderly individuals who frequently practice Tai Chi Chuan and individuals in the general population who constituted the healthy group. Methods: There were four groups, and each group included 12 participants. Ten Vicon motion system infrared cameras and two Kistler force plates were used. The data were standardized and analysed using independent-measure two-way ANOVA. Results: The statistical results showed that there was no interaction between the age factor and exercise type factor. The statistics of age factor also showed that age may decrease the jump height (36.36%), peak knee power (24.74%) and peak ankle power (21%) during the take-off phase. In the exercise type factor, long-term Tai Chi training significantly increased the jump height (60%), peak knee moment (19.80%), peak ankle moment (8.06%), peak hip power (29.80%), peak knee power (31.23%) and peak ankle power (16.88%) during the take-off phase. Conclusion: This study shows that long-term Tai Chi training can slow ageing-related functional decline. According to the results of this study, middle-aged and elderly people are encouraged to regularly perform Tai Chi exercises to increase the strength of various muscle groups in the lower limbs and slow the lower-limb muscle changes caused by ageing.

Determining jumping performance from a single body-worn accelerometer using machine learning

External peak power in the countermovement jump is frequently used to monitor athlete training. The gold standard method uses force platforms, but they are unsuitable for field-based testing. However, alternatives based on jump flight time or Newtonian methods applied to inertial sensor data have not been sufficiently accurate for athlete monitoring. Instead, we developed a machine learning model based on characteristic features (functional principal components) extracted from a single body-worn accelerometer. Data were collected from 69 male and female athletes at recreational, club or national levels, who performed 696 jumps in total. We considered vertical countermovement jumps (with and without arm swing), sensor anatomical locations, machine learning models and whether to use resultant or triaxial signals. Using a novel surrogate model optimisation procedure, we obtained the lowest errors with a support vector machine when using the resultant signal from a lower back sensor in jumps without arm swing. This model had a peak power RMSE of 2.3 W·kg^-1 (5.1% of the mean), estimated using nested cross validation and supported by an independent holdout test (2.0 W·kg^-1). This error is lower than in previous studies, although it is not yet sufficiently accurate for a field-based method. Our results demonstrate that functional data representations work well in machine learning by reducing model complexity in applications where signals are aligned in time. Our optimisation procedure also was shown to be robust can be used in wider applications with low-cost, noisy objective functions.

Developing a new muscle power prediction equation through vertical jump power output in adolescent women

Explosive power is a performance determinant in many sports activities. Vertical jump tests for assessing power output are widely employed. Accurate and reliable methods are needed to predict human power output using the widely employed vertical jump height.To determine vertical jump capacity by using force platform in high school-level girls and to develop an equation that predict vertical jump muscle power (MP) (watts) through body composition and vertical jump height.An experimental group consisting of 87 high school-level young sedentary girls (mean; age; 16.49 ± 1.93, height;161.25 ± 6.21, weight; 55.59 ± 10.27) and a validation (control) group consisting of a similar population of 30 people (mean; age; 16.14 ± 1.31, height; 163.30 ± 6.28, weight; 56.65 ± 9.59), participated in this study. A stepwise linear regression model, including fat free body mass, vertical jump height and fat percentage as independent parameters was applied to develop a new muscle power (MP) estimation equation. Pearson product-moment correlation coefficients were calculated between actual and predicted MP.The new prediction equation obtained from regression analysis for muscle power (MP) could explain 74.5% (R) of the variation. A strong and high correlation was observed between the Pearson product-moment correlation coefficients of the actual and predicted MP (experimental; r = 0.863; P < .000) and (control; r = 0.898; P < .000).The direct measurements of muscle power (MP) require researchers to access costly and complex instruments. This need will be met by the MP estimation equations obtained from a simple vertical jump height and body composition measurement.

When Jump Height is not a Good Indicator of Lower Limb Maximal Power Output: Theoretical Demonstration, Experimental Evidence and Practical Solutions

Lower limb external maximal power output capacity is a key physical component of performance in many sports. During squat jump and countermovement jump tests, athletes produce high amounts of mechanical work over a short duration to displace their body mass (i.e. the dimension of mechanical power). Thus, jump height has been frequently used by the sports science and medicine communities as an indicator of the power output produced during the jump and by extension, of maximal power output capacity. However, in this article, we contend that squat jump and countermovement jump height are not systematically good indicators of power output produced during the jump and maximal power output capacity. To support our opinion, we first detail why, theoretically, jump height and maximal power output capacity are not fully related. Specifically, we demonstrate that individual body mass, push-off distance, optimal loading and the force-velocity profile confound the jump height-power relationship. We also discuss the relationship between squat jump or countermovement jump height and maximal power output capacity measured with a force plate based on data reported in the literature, which added to our own experimental evidence. Finally, we discuss the limitations of existing practical solutions (regression-based estimation equations and allometric scaling), and advocate using a valid, reliable and simple field-based procedure to compute individual power output produced during the jump and maximal power output capacity directly from jump height, body mass and push-off distance. The latter may allow researchers and practitioners to reduce bias in their assessment of lower limb mechanical power output by using jump height as an input with a simple yet accurate computation method, and not as the first/only variable of interest.

The effects of tai chi chuan exercise training on countermovement jump performance in the elderly

This study sought to compare the biomechanical parameters of the lower extremities during a countermovement jump in elderly people who are engaged in frequent practice of tai chi chuan (TCG) and in the general population of healthy elderly people (HG). Each group included 12 participants. Ten Vicon Motion System infrared cameras and two Kistler force plates were employed for measurement. The jump height, duration, centre of mass (COM) displacement, joint ROM, and upward velocity were analysed in this study. Motion analysis and force platform data were combined to calculate joint moments and powers during the takeoff phase. The data were analysed using independent sample t-tests. The results showed that the tai chi chuan practitioner group (0.13 m) achieved 44% higher jump heights (p < 0.05). The COM displacement during squatting was lower in the TCG (0.25 m) than in the HG (0.19 m) (p < 0.05). The knee and ankle ROMs of the TCG were higher than those of the HG (p < 0.05). Peak knee moment 23% and peak knee power 32% higher in TCG compared to the HG (p < 0.05), suggesting that frequent practice of tai chi chuan may slow the rate of knee degeneration.

Estimation of Peak Muscle Power From a Countermovement Vertical Jump in Children and Adolescents

Gomez-Bruton, A, Gabel, L, Nettlefold, L, Macdonald, H, Race, D, and McKay, H. Estimation of peak muscle power from a countermovement vertical jump in children and adolescents. J Strength Cond Res 33(2): 390-398, 2019-Several equations to predict muscle power (MP) from vertical jump height (VJH) have been developed in adults. However, few have been derived in children. We therefore aimed to: (a) evaluate the validity of existing MP estimation equations from a vertical countermovement jump (CMJ) in children and adolescents and (b) develop and validate a new MP estimation equation for use in children and adolescents. We measured peak MP (in watts) and VJH (in centimeters) during a CMJ using a force platform in 249 children and adolescents (9-17 years; 119 boys and 130 girls). We compared actual (force platform) with predicted (12 existing prediction equations) MP using repeated-measures analysis of variance and estimated bias using modified Bland-Altman plots. We developed a new prediction equation using stepwise linear regression, assessed predictive error using leave-one-out and 10-fold cross-validation, and externally validated the equation in an independent sample (n = 100). All existing prediction equations demonstrated some degree of bias, either systematic bias (mean differences ranging 178-1,377 W; 8-64%) or bias at the extremes or interactions with sex. Our new prediction equation estimates MP from VJH and body mass: Power (W) = 54.2 × VJH (cm) + 34.4 × body mass (kg) - 1,520.4. With this new equation, there was no difference between actual and predicted MP (0%) and negligible differences (0.2-0.9%) in R and root mean square error between our observed and cross-validated sets. Actual and predicted MP were not different in our external validation (p = 0.12). The new equation demonstrates excellent validity and can be used to predict MP from a CMJ in children and adolescents.

Jump higher, run faster: effects of diversified sport participation on talent identification and selection in youth basketball

The aims of this study were to examine the medium-term effects of previous experiences during early stages of sport development on physical capacities of under-13 (U-13) talented basketball players and, to identify variables that discriminated under-14 (U-14) national team training camp selection. Anthropometrical and physical measurements were collected during a basketball training camp. Previous sport experiences (6-10 years), maturity offset, power outputs for jumping and sprinting were determined. A cluster analysis was used to allocate the subjects according to their different levels of sport experiences (more specialized vs. less specialized) to allow creating a dummy variable for the subsequent analysis of the physical variables. A stepwise discriminant analysis was computed to identify the construct that best classifies selected and non-selected players for U-14 national team training camp. The less specialized group outscored more specialized in all physical parameters, irrespectively of gender. The Abalakov Jump Peak Power and Predicted Adult Height (PAH) could successfully discriminate selected from non-selected players for U-14 national team training camp in boys and PAHin girls. The diversified and non-specific sport stimulus during early ages seem to be determinant to the acquisition and development of fundamental movement skills of talented basketball players.

Methodological Considerations on the Relationship Between the 1,500-m Rowing Ergometer Performance and Vertical Jump in National-Level Adolescent Rowers

Maciejewski, H, Rahmani, A, Chorin, F, Lardy, J, Samozino, P, and Ratel, S. Methodological considerations on the relationship between the 1,500-m rowing ergometer performance and vertical jump in national-level adolescent rowers. J Strength Cond Res 33(11): 3000-3007, 2019-The purpose of this study was to investigate whether 3 different approaches for evaluating squat jump performance were correlated with rowing ergometer performance in elite adolescent rowers. Fourteen young male competitive rowers (15.3 ± 0.6 years), who took part in the French rowing national championships, performed a 1,500-m all-out rowing ergometer performance (P1500) and a squat jump (SJ) test. The performance in SJ was determined by calculating the jump height (HSJ in cm), a jump index (ISJ = HSJ·body mass·gravity, in J), and the mean power output (PSJ in W) from the Samozino et al.'s method. Furthermore, allometric modeling procedures were used to consider the importance of body mass (BM) in the relationships between P1500 and jump scores. P1500 was significantly correlated with HSJ (r = 0.29, p ≤ 0.05), ISJ (r = 0.72, p < 0.0001), and PSJ (r = 0.86, p < 0.0001). Furthermore, BM explained at least 96% of the relationships between SJ and rowing performances. However, the similarity between both allometric exponents for PSJ and P1500 (1.15 and 1.04, respectively) indicates that BM could influence jump and rowing ergometer performances at the same rate, and that PSJ could be the best correlate of P1500. Therefore, the calculation of power seems to be more relevant than HSJ and ISJ to (a) evaluate jump performance and (b) infer the capacity of adolescent rowers to perform 1,500-m all-out rowing ergometer performance, irrespective of their body mass. This could help coaches to improve their training program and potentially identify talented young rowers.

Power Output Prediction From Jump Height and Body Mass Does Not Appropriately Categorize or Rank Athletes

The purposes of this study were (a) to verify the agreement of categorization and ranks based on the actual power output measured by a force plate (PPact) and the estimated power output (PPest) from jump height and body mass (BM), and (b) to verify whether the ratio standard is adequate to scale the PPact for BM. The countermovement jumps of 309 male athletes were analyzed. The athletes were first categorized into tertiles (superior, intermediate, and inferior) according to PPact and PPest. After that the athletes were ranked (highest to lowest power output) according to PPact and PPest. The PPest equation explained 81% of PPact variance (standard error of estimate = 277.4 W). The PPest (3,757.1 ± 579.8 W) displayed similar mean values compared with PPact (3,757.1 ± 642.3 W). However, the agreement between the categories generated by PPact and PPest was only moderate (k = 0.6; p < 0.01), and in the intermediate tertile, the categorization differs 38.8%. The agreement between the ranks analyzed from a Bland-Altman plot shows bias zero, but a wide limits of agreement (81 ranks; 26.2%). For the PPact scaling, the ratio standard may be considered as an adequate method for removing the BM effect, considering the lack of correlation between the scaled PPact (PPact/BM) and BM, and also the confirmation of Tanner's special circumstance. In conclusion, our findings indicate that the athlete's power output was not appropriately categorized or ranked when using PPest. Furthermore, the use of the scaled PPact is recommended to fairly compare athletes with different BMs.

Lower-Limb Power cannot be Estimated Accurately from Vertical Jump Tests

The countermovement jump test is often adopted to monitor lower-limb power of an individual. Despite several studies on the validity of this test, there is still a need to determine the minimal difference needed to be confident that a difference in power between two individuals is present or that a true change in the performance of an individual has occurred. In this study, power was measured from ground reaction forces and compared to that obtained from predictive equations for two groups of subjects (67 trained and 20 highly trained individuals). The height of each jump was determined with kinematic techniques. The main outcome is a large discrepancy between power calculated from ground reaction forces and that calculated from predictive equations. For the trained group, the R-square value between power and predicted power was 0.53 and the minimal difference to consider that two individuals were different was 821.7 W. For the highly trained individuals, a much larger R-square value was obtained (0.94). Despite this, the minimal difference to consider that two individuals were different was still large (689.3 W). The large minimal differences obtained raise serious concerns about using countermovement jumps for appraisal and monitoring of lower-limb power of an individual.

Reliability of vertical jump performance evaluated with contact mat in elderly women

The aim of this study was to evaluate the reliability of the vertical jump (VJ) using a contact mat in elderly women. Thirty-one physically active women aged 69·5 ± 5·6 years participated in this study. Jump performance was evaluated with a contact mat. The first testing session (s1) consisted of four countermovement jumps interspersed with 40 s rest intervals. After a period of 5-7 days, volunteers performed the second session (s2) utilizing the same procedures. The intersession statistical analysis was calculated considering the two highest jumps, one obtained in each section. The intra-session analysis utilized all eight jumps, all four from each section, and the differences between means were calculated by repeated measures ANOVA. Reliability was tested using the intra-class correlation coefficient (ICC) and agreement by the Bland-Altman method. The intra- and inter-subject variation percentage was calculated by the coefficient of variation (CV).

RESULTS

The intersession results displayed a high ICC (0·91; P<0·001) and a good agreement verified by the Bland-Altman method. There was a significant difference in the intra-session analysis only in s2 between the jumps 2 and 4. Both in s1 and s2, the ICC was high (0·96; P<0·001; 0·95; P<0·001), and the within session reliability CV was low (10·14% and 9·07%).

CONCLUSION

In physically active elderly women, VJ evaluation using a contact mat is a reliable method and could be used to estimate jump height. Additionally, the results of this study could serve as reference values in similar samples evaluated with the same procedures.