Relationship between vertical jump and maximal power output of legs and arms: Effects of ethnicity and sport

Using Machine Learning Algorithms to Pool Data from Meta-Analysis for the Prediction of Countermovement Jump Improvement

To solve the research-practice gap and take one step forward toward using big data with real-world evidence, the present study aims to adopt a novel method using machine learning to pool findings from meta-analyses and predict the change of countermovement jump. The data were collected through a total of 124 individual studies included in 16 recent meta-analyses. The performance of four selected machine learning algorithms including support vector machine, random forest (RF) ensemble, light gradient boosted machine, and the neural network using multi-layer perceptron was compared. The RF yielded the highest accuracy (mean absolute error: 0.071 cm; R²: 0.985). Based on the feature importance calculated by the RF regressor, the baseline CMJ ("Pre-CMJ") was the most impactful predictor, followed by age ("Age"), the total number of training sessions received ("Total number of training_session"), controlled or non-controlled conditions ("Control (no training)"), whether the training program included squat, lunge, deadlift, or hip thrust exercises ("Squat_Lunge_Deadlift_Hipthrust_True", "Squat_Lunge_Deadlift_Hipthrust_False"), or "Plyometric (mixed fast/slow SSC)", and whether the athlete was from an Asian pacific region including Australia ("Race_Asian or Australian"). By using multiple simulated virtual cases, the successful predictions of the CMJ improvement are shown, whereas the perceived benefits and limitations of using machine learning in a meta-analysis are discussed.

Kinematic Mobile Drop Jump Analysis at Different Heights Based on a Smartphone Inertial Sensor

The purpose of this study was to describe the acceleration variables in a plyometric jump test using the inertial sensor built into an iPhone 4S® smartphone, and the jumping variables from a contact mat. A cross-sectional study was conducted involving 16 healthy young adults. Linear acceleration, flight time, contact time and jump height were measured in a drop jump test from 60 cm and from 30 cm. Greater acceleration values were found in the drop jump test from 60 cm; the same was observed for the values from the contact mat. Multiple regression analysis was performed for each drop jump test: jump height was used as the dependent variable, and the most relevant variables were used as predictor variables (weight and maximum angular velocity in the Y axis for analysis of the drop jump from 60 cm, and weight and maximum acceleration in the Z axis for the drop jump from 30 cm). We found a significant regression model for the drop jump test from 60 cm (R2 = 0.515, p “ 0.001) and for the test from 30 cm (R2 = 0.460, p “ 0.01). According to the results obtained in this study, the built-in iPhone 4S® inertial sensor is able to measure acceleration for healthy young adults performing a vertical drop jump test. The acceleration kinematic variables are higher in the drop jump test from 60 cm than from 30 cm.

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.

Influence of ethnicity on vertical jump performances in male physical education students: a pilot study

BACKGROUND

The present study aimed to: 1) test the possibility of ethnic differences in squat jump (SJ), countermovement jump (CMJ) and countermovement jump with arms swing (CMJA); 2) test the possibility of ethnic differences in the effects of countermovement and arms swing; 3) verify whether the relationships between the different vertical jumps (VJ) (SJ, CMJ, CMJA) and maximal power (Pmax), determined from a force-velocity test (F-V), were dependent on the ethnicity as previously found for CMJA.

METHODS

VJ were performed by 84 active men (WAC): 40 WA and 44 C. VJ were measured on a force platform in three conditions: SJ, CMJ and CMJA. For technical reasons, only 39 of these participants (WA2C2) performed F-V test [V=V0(1-F/F0) and maximal power=0.25 V0F0]: 20 WA (WA2) and 19 C (C2).

RESULTS

There were significant ethnic differences (WA>C) in SJ, CMJ, CMJA, CMJA-CMJ, CMJA/CMJ. The effect sizes (Cohen d) of these ethnic differences were large for CMJA (0.93), CMJA-CMJ (1.11) CMJA/CMJ (0.82) and medium for CMJ (0.54) and SJ (0.56). Ethnic effect in the countermovement jump was small (Cohen d=0.04 for CMJ-SJ) and not significant.

CONCLUSIONS

For WA2C2, the slightly higher value of Pmax in WA2 (Cohen d =0.23) probably explained their slightly higher values of SJ, CMJ but not their higher values of CMJA and arms swing effect. In WA2C2, a difference in fast-fiber percentages was not the explanation of the ethnic differences because the optimal pedal rates corresponding to Pmax (0.5 V0) were similar in both groups.

Allometric scaling of power-force-velocity ergometry profiles in men

AIM

To examine the appropriate magnitude of allometric scaling of the force-velocity relationship according to body dimensions and to establish normative data for the power-force-velocity relationship for active men.

SUBJECTS AND METHODS

Ninety-seven participants completed a force-velocity test on a Monark cycle ergometer. Allometric exponents and percentile ranks were established for maximal power (Pmax), maximal force (F0) and maximal velocity (V0).

RESULTS

The mean (± SD) of Pmax, F0 and V0 were 1114.90 ± 160.60 W, 191.97 ± 26.51 N, and 227.87 ± 8.82 rpm, respectively. V0 was not related to any body size descriptors. Allometric exponents for Pmax, and F0 scaled for body mass were b = 0.77 (0.64-0.90) and 0.74 (0.61-0.86), respectively. Correlations between allometrically scaled Pmax and F0 with body mass were r = 0.002 (p = 0.984) and r = 0.008 (p = 0.940), respectively, suggesting that the allometric exponents derived were effective in partialling out the effect of body mass on Pmax and F0 results.

CONCLUSIONS

The allometric exponents and normative values of the current study provide a useful tool for comparing the scores of force-velocity tests between individuals without the confounding effect of body size.

The Relationship between Pedal Force and Crank Angular Velocity in Sprint Cycling

PURPOSE

Relationships between tangential pedal force and crank angular velocity in sprint cycling tend to be linear. We set out to understand why they are not hyperbolic, like the intrinsic force-velocity relationship of muscles.

METHODS

We simulated isokinetic sprint cycling at crank angular velocities ranging from 30 to 150 rpm with a forward dynamic model of the human musculoskeletal system actuated by eight lower extremity muscle groups. The input of the model was muscle stimulation over time, which we optimized to maximize average power output over a cycle.

RESULTS

Peak tangential pedal force was found to drop more with crank angular velocity than expected based on intrinsic muscle properties. This linearizing effect was not due to segmental dynamics but rather due to active state dynamics. Maximizing average power in cycling requires muscles to bring their active state from as high as possible during shortening to as low as possible during lengthening. Reducing the active state is a relatively slow process, and hence must be initiated a certain amount of time before lengthening starts. As crank angular velocity goes up, this amount of time corresponds to a greater angular displacement, so the instant of switching off extensor muscle stimulation must occur earlier relative to the angle at which pedal force was extracted for the force-velocity relationship.

CONCLUSION

Relationships between pedal force and crank angular velocity in sprint cycling do not reflect solely the intrinsic force-velocity relationship of muscles but also the consequences of activation dynamics.

Effects of ethnicity on the relationship between vertical jump and maximal power on a cycle ergometer

The aim of this study was to verify the impact of ethnicity on the maximal power-vertical jump relationship. Thirty-one healthy males, sixteen Caucasian (age: 26.3 ± 3.5 years; body height: 179.1 ± 5.5 cm; body mass: 78.1 ± 9.8 kg) and fifteen Afro-Caribbean (age: 24.4 ±2.6 years; body height: 178.9 ± 5.5 cm; body mass: 77.1 ± 10.3 kg) completed three sessions during which vertical jump height and maximal power of lower limbs were measured. The results showed that the values of vertical jump height and maximal power were higher for Afro-Caribbean participants (62.92 ± 6.7 cm and 14.70 ± 1.75 W∙kg-1) than for Caucasian ones (52.92 ± 4.4 cm and 12.75 ± 1.36 W∙kg-1). Moreover, very high reliability indices were obtained on vertical jump (e.g. 0.95 < ICC < 0.98) and maximal power performance (e.g. 0.75 < ICC < 0.97). However, multiple linear regression analysis showed that, for a given value of maximal power, the Afro-Caribbean participants jumped 8 cm higher than the Caucasians. Together, these results confirmed that ethnicity impacted the maximal power-vertical jump relationship over three sessions. In the current context of cultural diversity, the use of vertical jump performance as a predictor of muscular power should be considered with caution when dealing with populations of different ethnic origins.

Vertical Jumping Tests versus Wingate Anaerobic Test in Female Volleyball Players: The Role of Age

Single and continuous vertical jumping tests, as well as the Wingate anaerobic test (WAnT), are commonly used to assess the short-term muscle power of female volleyball players; however, the relationship among these tests has not been studied adequately. Thus, the aim of the present study was to examine the relationship of single and continuous vertical jumps with the WAnT in female volleyball players. Seventy adolescent (age 16.0 ± 1.0 years, body mass 62.5 ± 7.1 kg, height 170.4 ± 6.1 cm, body fat 24.2% ± 4.3%) and 108 adult female volleyball players (age 24.8 ± 5.2 years, body mass 66.5 ± 8.7 kg, height 173.2 ± 7.4 cm, body fat 22.0% ± 5.1%) performed the squat jump (SJ), countermovement jump (CMJ), Abalakov jump (AJ), 30 s Bosco test and WAnT (peak power, P_peak; mean power, P_mean). Mean power in the Bosco test was correlated (low to large magnitude) with P_mean of the WAnT (r = 0.27, p = 0.030 in adolescents versusr = 0.56, p < 0.001 in adults). SJ, CMJ and AJ also correlated with P_peak (0.28 ≤ r ≤ 0.46 in adolescents versus 0.58 ≤ r ≤ 0.61 in adults) and with P_mean (0.43 ≤ r ≤ 0.51 versus 0.67 ≤ r ≤ 0.71, respectively) of the WAnT (p < 0.05). In summary, the impact of the Bosco test and WAnT on muscle power varied, especially in the younger age group. Single jumping tests had larger correlations with WAnT in adults than in adolescent volleyball players. These findings should be taken into account by volleyball coaches and fitness trainers during the assessment of short-term muscle power of their athletes.

Reliability of Force-Velocity Tests in Cycling and Cranking Exercises in Men and Women

The present study examined the reliability of the force-velocity relationship during cycling and arm cranking exercises in active males and females. Twenty male and seventeen female physical education students performed three-session tests with legs and three-session tests with arms on a friction-loaded ergometer on six different sessions in a randomized order. The reliability of maximal power (Pmax), maximal pedal rate (V 0), and maximal force (F0) were studied using the coefficient of variation (CV), the intraclass correlation coefficient (ICC) and the test-retest correlation coefficient (r). Reliability indices were better for men (1.74 ≤ CV ≤ 4.36, 0.82 ≤ ICC ≤ 0.97, and 0.81 ≤ r ≤ 0.97) compared with women (2.34 ≤ CV ≤ 7.04, 0.44 ≤ ICC ≤ 0.98, and 0.44 ≤ r ≤ 0.98) and in cycling exercise (1.74 ≤ CV ≤ 3.85, 0.88 ≤ ICC ≤ 0.98, and 0.90 ≤ r ≤ 0.98) compared with arm exercise (2.37 ≤ CV ≤ 7.04, 0.44 ≤ ICC ≤ 0.95, and 0.44 ≤ r ≤ 0.95). Furthermore, the reliability indices were high for Pmax and F0 whatever the expression of the results (raw data or data related to body dimensions). Pmax and F0 could be used in longitudinal physical fitness investigations. However, further studies are needed to judge V 0 reliability.

Mobile Jump Assessment (mJump): A Descriptive and Inferential Study

BACKGROUND

Vertical jump tests are used in athletics and rehabilitation to measure physical performance in people of different age ranges and fitness. Jumping ability can be analyzed through different variables, and the most commonly used are fly time and jump height. They can be obtained by a variety of measuring devices, but most are limited to laboratory use only. The current generation of smartphones contains inertial sensors that are able to record kinematic variables for human motion analysis, since they are tools for easy access and portability for clinical use.

OBJECTIVE

The aim of this study was to describe and analyze the kinematics characteristics using the inertial sensor incorporated in the iPhone 4S, the lower limbs strength through a manual dynamometer, and the jump variables obtained with a contact mat in the squat jump and countermovement jump tests (fly time and jump height) from a cohort of healthy people.

METHODS

A cross sectional study was conducted on a population of healthy young adults. Twenty-seven participants performed three trials (n=81 jumps) of squat jump and countermovement jump tests. Acceleration variables were measured through a smartphone's inertial sensor. Additionally, jump variables from a contact mat and lower limbs dynamometry were collected.

RESULTS

In the present study, the kinematic variables derived from acceleration through the inertial sensor of a smartphone iPhone 4S, dynamometry of lower limbs with a handheld dynamometer, and the height and flight time with a contact mat have been described in vertical jump tests from a cohort of young healthy subjects. The development of the execution has been described, examined and identified in a squat jump test and countermovement jump test under acceleration variables that were obtained with the smartphone.

CONCLUSIONS

The built-in iPhone 4S inertial sensor is able to measure acceleration variables while performing vertical jump tests for the squat jump and countermovement jump in healthy young adults. The acceleration kinematics variables derived from the smartphone's inertial sensor are higher in the countermovement jump test than the squat jump test.

Musculotendinous Stiffness of Triceps Surae, Maximal Rate of Force Development, and Vertical Jump Performance

The relationships between ankle plantar flexor musculotendinous stiffness (MTS) and performance in a countermovement vertical jump (CMJ) and maximal rate of torque development (MRTD) were studied in 27 active men. MTS was studied by means of quick releases at 20 (S0.2), 40 (S0.4), 60 (S0.6), and 80% (S0.8) of maximal voluntary torque (TMVC). CMJ was not correlated with strength indices but was positively correlated with MRTD/BM,S0.4/BM. The slopeα2and interceptβ2of the torque-stiffness relationships from 40 to 80%TMVCwere correlated negatively (α2) and positively (β2) with CMJ. The different stiffness indices were not correlated with MRTD. The prediction of CMJ was improved by the introduction of MRTD in multiple regressions between CMJ and stiffness. CMJ was also negatively correlated with indices of curvature of the torque-stiffness relationship. The subjects were subdivided in 3 groups in function of CMJ (groups H, M, and L for high, medium, and low performers, resp.). There was a downward curvature of the torque-stiffness relationship at high torques in group H or M and the torque-stiffness regression was linear in group L only. These results suggested that torque-stiffness relationships with a plateau at high torques are more frequent in the best jumpers.