Skyler T. Taylor

Data reliability from an instrumented vertical jump platform.

Caruso, JF, Daily, JS, Mclagan, JR, Shepherd, CM, Olson, NM, Marshall, MR, and Taylor, ST. Data reliability from an instrumented vertical jump platform. J Strength Cond Res 24(10): 2799-2808, 2010-A Vertec jump measurement and training system measures vertical jump heights but not additional variables that would reveal how the performance was achieved. Technology advances to equipment now include additional variables that elucidate how jump performance is achieved. However, acceptance of new jump-related equipment is predicated on the reliability of the vertical heights it measures in relation to those assessed by the Vertec. Thus, our study compared vertical jump height reliability data from a newly created instrumented platform to those concurrently derived from the Vertec. Methods required subjects (n = 105) to perform 2 jump trials separated by at least 2 days of rest. Trials began with a warm-up, followed by 3 to 5 maximal-effort jumps. The Vertec was placed directly over the platform so, as jumps occurred, subjects took off and landed on the instrumented device. At the jump apex subjects contacted the highest Vertec slapstick possible to assess maximum height attained. Four height measurements were derived from each jump: 3 platform-based calculations (from subjects take-off, hang time, and landing) and 1 Vertec. The platform-based calculations were compared to Vertec data to assess the reliability of the instrumented device. Intraclass correlation coefficient (0.90), coefficient of variation (17.3%), standard error of measurement (0.9 cm), and smallest real difference (3.7 cm) results showed heights calculated from platform take-offs were most reliable to Vertec values. It was concluded take-off from the platform yielded jump heights that are a viable alternative to those derived from the Vertec. Practical applications suggest coaches may use the platform to derive reliable vertical jump data in addition to other variables to better understand the performance of their athletes.

Front Squat Data Reproducibility Collected With a Triple-Axis Accelerometer

Caruso, JF, Olson, NM, Taylor, ST, McLagan, JR, Shepherd, CM, Borgsmiller, JA, Mason, ML, Riner, RR, Gilliland, L, and Griswold, S. Front squat data reproducibility collected with a triple-axis accelerometer. J Strength Cond Res 26(1): 40–46, 2012—The purpose of our study was to assess data reproducibility from 2 consecutive front squat workouts, spaced 1 week apart, performed by American college football players (n = 18) as they prepared for their competitive season. For each workout, our methods entailed the performance of 3–6 front squat repetitions per set at 55, 65, and 75% of subjects 1 repetition maximum (1RM) load. In addition, a fourth set was done at a heavier load, with a resistance equal to 80 and 83% of their 1RM values, for the first and second workouts, respectively. A triple-axis accelerometer was affixed to a barbell to quantify exercise performance. Per load, the accelerometer measures peak values for the following indices: force, velocity, and power. To assess data reproducibility, inter–workout comparisons were made for 12 performance indices with 4 statistical test-retest measures: intraclass correlation coefficients, coefficients of variation (CVs), and the SEM expressed in both absolute and relative terms. Current results show that the majority of performance indices exceeded intraclass correlation (0.75–0.80) and CV (10–15%) values previously deemed as acceptable levels of data reproducibility. The 2 indices with the greatest variability were power and velocity values obtained at 55% of the 1RM load; thus, it was concluded that higher movement rates at the lightest load were the most difficult aspect of front squat performance to repeat successfully over time. Our practical applications imply lighter loads, with inherently higher rates of barbell movement, yield lower data reproducibility values.

Anthropometry as a predictor of front squat performance in American college football players

To assess the extent anthropometry predicts front squat performance, American college football players (n = 18) performed 3-6 repetition sets at 55, 65, 75 and 80% of their 1RM (one repetition maximum) load across two workouts. At the conclusion of sets, an accelerometer (Myotest Inc., Royal Oak MI) measured peak power, force and velocity. Before the first workout, anthropometric data were collected from subjects that emphasized body segment length ratios in an attempt to predict front squat variance. Via multivariate regression, anthropometry attempted to predict the variance from each of 12 criterion variables (peak power, force and velocity at each load). With an α = 0.05, anthropometry predicted significant amounts of variance for six criterion variables, which also had high R (0.647-0.832) and R 2 (0.419-0.720) values. The same variables also yielded moderate standard error of estimates, thus anthropometry accounted for much front squat performance variance. Height/hip width ratio, body weight, body mass index and torso length were the best predictors of front squat performance. Based on current results, it was concluded anthropometry is an important predictor of front squat performance in American college football players.

Anthropometry as a Predictor of Bench Press Performance Done at Different Loads

Abstract Caruso, JF, Taylor, ST, Lutz, BM, Olson, NM, Mason, ML, Borgsmiller, JA, and Riner, RD. Anthropometry as a predictor of bench press performance done at different loads. J Strength Cond Res 26(9): 2460–2467, 2012—The purpose of our study was to examine the ability of anthropometric variables (body mass, total arm length, biacromial width) to predict bench press performance at both maximal and submaximal loads. Our methods required 36 men to visit our laboratory and submit to anthropometric measurements, followed by lifting as much weight as possible in good form one time (1 repetition maximum, 1RM) in the exercise. They made 3 more visits in which they performed 4 sets of bench presses to volitional failure at 1 of 3 (40, 55, or 75% 1RM) submaximal loads. An accelerometer (Myotest Inc., Royal Oak MI) measured peak force, velocity, and power after each submaximal load set. With stepwise multivariate regression, our 3 anthropometric variables attempted to explain significant amounts of variance for 13 bench press performance indices. For criterion measures that reached significance, separate Pearson product moment correlation coefficients further assessed if the strength of association each anthropometric variable had with the criterion was also significant. Our analyses showed that anthropometry explained significant amounts (p < 0.05) of variance for 8 criterion measures. It was concluded that body mass had strong univariate correlations with 1RM and force-related measures, total arm length was moderately associated with 1RM and criterion variables at the lightest load, whereas biacromial width had an inverse relationship with the peak number of repetitions performed per set at the 2 lighter loads. Practical applications suggest results may help coaches and practitioners identify anthropometric features that may best predict various measures of bench press prowess in athletes.

β2-Adrenergic Agonist Administration and Strength Training

Abstract β2-Adrenergic agonists (β2AA) produce myriad effects throughout the human body. Prescribed concurrently with theophylline for the bronchodilatory effects they offer in the treatment of asthma and chronic obstructive pulmonary disease, β2AA actions include many beneficial and adverse changes when administered to animals at supraphysiological doses. Beneficial changes include improved musculoskeletal health and function, which can be maintained because adverse changes are reduced if oral β2AA are given at therapeutic dosages in humans with concurrent resistive exercise administration. Combined oral β2AA-resistive exercise treatments have been shown to produce gains in musculoskeletal health and function in numerous healthy and disuse atrophy human models. The mechanism(s) by which β2AA exert their effects are a function of multiple factors, not the least of which includes the type of model receiving the drug treatment. Combined oral β2AA-resistive exercise treatments in humans showed that adverse effects were greatly reduced when prudent and safer drug administration practices were employed (eg, screening subjects for tolerance before drug treatment). Results from human research trials suggest that administration of the combined treatment improves musculoskeletal function and performance with minimal health risk if proper precautions are followed. A related issue is administration of the combined treatment as an ergogenic aid to athletic performance. Given the results presented in this article, physicians should be wary of potential drug abuse and administer β2AA only under appropriate circumstances when such a treatment is warranted.

The effect of flywheel-based resistive exercise workouts on testosterone/cortisol ratios

Toassessthesubsequent testosterone/cortisol ratio(TCr)fromflywheel-basedresistiveexercise, usingawithin-subjects design volunteers (7men, 10 women) performed three seated legpress workouts on an ergometer (YoYoTechnologies, Stockholm Sweden). Comprised of ten-repetition sets, the workouts entailed: a three-set protocol composed of concentric and eccentric actions (CE3), as well as concentric-only paradigms of three (CO3) and six (CO6) sets. Venous blood, collected before bouts and at one and 30 minutes post-exercise, was used to quantify the TCr. Data were examined with ANOVA and multivariate regression. ANOVA yielded a gender x time TCr interaction, as male values declined significantly yet womens data were unchanged. With the TCr at one and 30 minutes post-exercise as separate criterion measures, and data pooled across genders and workouts, multivariate regression revealed significance per dependent variable. Univariate correlations showed the best predictors of the post-exercise TCr in descending order were: body mass, average power and delta lactate. Gender and quadriceps muscle volume may have acted as confounding variables to allow body mass to the best current study predictor. Continued research should examine additional predictor variables, as current results only accounted for roughly 30% of the total criterion measure variance.

Prediction of Resultant Testosterone Concentrations from Flywheel-Based Resistive Exercise

INTRODUCTION Numerous variables impact resultant testosterone concentrations (TC) that foretell the efficacy of workouts. Identifying variables may aid the development of in-flight exercise prescription. METHODS To identify variables that predict the variance in TC from flywheel ergometer exercise, 17 subjects did 3 workouts in a randomized order. Comprised of 10-repetition leg press sets, workouts entailed either: 1) 3 sets of both concentric and eccentric muscle actions (CE3), and concentric-only actions done for 2) three (CO3), or 3) six (CO6) sets. Venous plasma TC were collected before and at 1 and 30 min postexercise. The last two collection points served as criterion measures. Body mass, delta blood lactate levels, peak angular velocity, average power, and total work from workouts were used to predict the variance in TC. RESULTS Predictor variables accounted for significant levels of variance at both 1 and 30 min post-exercise for both the CE3 and the concentric-only (CO3 and CO6 bouts combined) workouts using multivariate regression. Inclusion of eccentric variables (only collected from the CE3 bout; r2 = 0.90) predicted nearly twice the variance than the concentric-only (r2 = 0.54) workouts. CONCLUSIONS Body mass and average power indices were the best predictors of the variance in post-workout TC. Since a flywheel-based device is used to abate in-flight muscle atrophy and strength losses, exercise prescriptions may wish to monitor these indices as they impacted post-workout TC to the greatest extent. Future research should assess why eccentric variables increased the amount of explained variance from flywheel ergometer workouts.