Salivary hormonal values from high-speed resistive exercise workouts.

Our study purpose examined salivary hormonal responses to high-speed resistive exercise. Healthy subjects (n = 45) performed 2 elbow flexor workouts on a novel (inertial kinetic exercise; Oconomowoc, WI, USA) strength training device. Our methods included saliva sample collection at both preexercise and immediately postexercise; workouts entailed two 60-second sets separated by a 90-second rest period. The samples were analyzed in duplicate for their testosterone and cortisol concentrations ([T], [C]). Average and maximum elbow flexor torque were measured from each exercise bout; they were later analyzed with a 2(gender) × 2(workout) analysis of variance (ANOVA) with repeated measures for workout. The [T] and [C] each underwent a 2(gender) × 2(time) ANOVA with repeated measures for time. A within-subject design was used to limit error variance. Average and maximum torque each had gender (men > women; p < 0.05) effects. The [T] elicited a 2-way interaction (p < 0.05), as men incurred a significant 14% increase over time, but women's values were unchanged. Yet multivariate regression revealed that 3 predictor variables (body mass and average and maximum torques) did not account for a significant amount of variance associated with the rise in male [T]. Changes in [C] were not significant. In conclusion, changes in [T] concur with the results from other studies that showed significant elevations in male [T], despite the brevity of current workouts and the rather modest volume of muscle mass engaged. Practical applications imply that salivary assays may be a viable alternative to blood draws from athletes, yet coaches and others who may administer this treatment should know that our results may have produced greater pre-post hormonal changes if postexercise sample collection had occurred at a later time point.

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.

Blood lactate and hormonal responses to prototype flywheel ergometer workouts.

The purpose of the study was to compare blood lactate and hormonal responses with flywheel ergometer (FERG) leg presses for preliminary assessment of workouts best suited for future in-flight resistance exercise. Comprised of 10 repetition sets, the workouts entailed 3 sets of concentric and eccentric (CE3) actions, or concentric-only actions done for 3 (CO3) or 6 (CO6) sets. Methods employed included assessment of blood lactate concentrations ([BLa-]) before and 5 minutes postexercise. Venous blood was also collected before and at 1 and 30 minutes postexercise to assess growth hormone, testosterone, cortisol concentrations ([GH], [T], [C]) and [T/C] ratios. [BLa-] were compared with 2 (time) x 3 (workout) analysis of variance. Hormones were assessed with 2 (gender) x 3 (time) x 3 (workout) analysis of covariances. Results showed [BLa-] had a time effect. Growth hormone concentration showed gender x workout, gender x time, and workout x time interactions, whereas [T] had a 3-way interaction. [C] had gender, time, and workout effects. [T/C] yielded a gender x time interaction. It was concluded that, because CO6 and CE3 yielded similar anabolic hormonal data but the latter had a lower [C] 30 minutes postexercise, CE3 served as the best workout. Although the FERG was originally designed for microgravity, the effort put forth by current subjects was like that for workouts aimed at greater athletic performance and conditioning. Practical applications suggest that eccentric actions should be used for FERG workouts geared toward muscle mass and strength improvement.

Impact of acceleration on blood lactate values derived from high-speed resistance exercise.

Acceleration, or an increase in the rate of movement, is integral to success in many sports. Improvements in acceleration often entail workouts done at intensities that elicit higher blood lactate concentrations (BLa). The purpose of the study is to assess the impact of acceleration on BLa. Methods required subjects (n = 45) to perform 4 workouts that each involved two 1-minute sets of hip- and knee-extension repetitions on an inertial exercise trainer (Impulse Training Systems, Newnan, Georgia). Subjects performed 2 workouts comprised solely of phasic or tonic repetitions; their sequence was randomized to prevent an order effect. Before and 5 minutes after exercise, subjects' BLa were assessed with a calibrated analyzer (Sports Resource Group, Hawthorne, New York). Post and delta (post-pre) BLa both served as criterion measures for multivariate analysis. Average and peak acceleration values, derived from both phasic and tonic workouts, served as predictor variables. Results showed statistical significance (p < 0.05; R = 0.2534) and yielded the following prediction equation from phasic workouts: delta BLa = 1.40 + 1.116 (average acceleration set 1)--0.011 (peak acceleration set 1)--0.634 (average acceleration set 2) + 0.005 (peak acceleration set 2). Conclusions suggest delta BLa variance, which represents the increase of the metabolite incurred from workouts, is most easily explained by average acceleration values, which describes the mean increase in the rate of movement from phasic workouts. To improve an athlete's tolerance for acceleration-induced BLa increases, workouts should be tailored with respect to the muscles involved and the duration of exercise bouts of their chosen sport.

Growth hormone levels after flywheel ergometer exercise: correlation with independent variables.

INTRODUCTION: In-flight muscle mass and strength losses are likely exacerbated by low growth hormone (GH) concentrations. Factors associated with exercise may foretell resultant GH levels and thereby help blunt future mass and strength losses. METHODS: To assess the ability of variables to predict GH variance from resistive exercise done on a flywheel ergometer (FE) designed for in-flight exercise, subjects (N=17) performed three types of workouts on the device. With a randomized design, subjects performed the workouts with the intent to determine if changes in post-exercise GH concentrations are impacted by contractile mode and workload. Body mass, blood lactate (BLa-) concentrations, and peak angular velocity (PAV), average power (AP), and total work (TW) from workouts attempted to predict GH variance. Pre-exercise blood draws, and at 1 and 30 min after workouts, were used to determine GH concentrations. BLa- levels were measured before workouts and at 5 min post-exercise. Delta (8, post-pre) and 30-min post-workout GH levels served as criterion variables. RESULTS: Multivariate regression with an alpha < or = 0.05 yielded the following significant prediction equation: deltaGH = 13.64 - 0.014 (body mass) - 0.607 (post-exercise BLa-) + 0.659 (deltaBLa-) - 0.624(PAV) + 0.653(TW) + 0.147(AP). DISCUSSION: Univariate correlations show body mass, deltaBLa-, and TW were the best predictors of deltaGH variance. Future research should also attempt to identify additional variables that account for the unexplained GH variance from FE workouts.

Performance evaluation of a high-speed inertial exercise trainer.

A high-speed, low-resistance inertial exercise trainer (IET, Impulse Training Systems, Newnan, Ga) is increasingly employed in rehabilitative and athletic performance settings. Repetitions on an IET are done through a large range of motion because multijoint movements occur over more than one plane of motion, with no limitation on velocities or accelerations attained. The current study purpose is to assess data reproducibility from an instrumented IET through multiple test-retest measures. Data collection methods required the IET left and right halves to be fitted with a TLL-2K force transducer (Transducer Techniques, Temecula, Calif) on one of its pulleys, and an infrared position sensor (Model CX3-AP-1A, automationdirect.com) located midway on the underside of each track. Signals passed through DI-158U signal conditioners (DATAQ Instruments, Akron, Ohio) and were measured with a four-channel analog data acquisition card at 4000 Hz. To assess data reproducibility, college-age subjects (n = 45) performed four IET workouts that were spaced 1 week apart. Workouts entailed two 60-second sets of repetitive knee- and hip-extensor muscle actions as subjects were instructed to exert maximal voluntary effort. Results from multiple test-retest measures show that the IET elicited reproducible intra- and interworkout data despite the unique challenge of multiplanar and multijoint exercise done over a large range of motion. We conclude that future studies in which IET performance measurement is required may choose to instrument the device with current methodology. Current practical applications include making IET data easier to comprehend for the coaches, athletes, and health care providers who use the device.

The combined acute effects of massage, rest periods, and body part elevation on resistance exercise performance.

Although massage administered between workouts has been suggested to improve recovery and subsequent performance, its application between bouts of repetitive supramaximal anaerobic efforts within a given workout has received little attention. The purpose of the study compared different forms of very short rest periods administered between resistance exercise sets of individual workouts on subsequent performance. With a within-subjects design methodology, subjects (n = 30) performed three workouts that were identical in terms of the exercises (45 degrees leg press, prone leg curl, seated shoulder press, standing barbell curl), number of sets, and the resistance employed. For each workout, subjects received one of the following treatments between sets: 1 minute of rest as they stood upright, 30 seconds of rest as they stood upright, or 30 seconds of concurrent massage and body part elevation (MBPE), which entailed petrassage of the exercised limbs in a raised and supported position in an attempt to abate fatigue and enhance recovery from the previous set. Subjects were instructed to perform as many repetitions as possible for each set. For each exercise, two dependent variables were calculated: a total work/elapsed time ratio and the cumulative number of repetitions performed. For each exercise, one-way repeated-measures analysis of variance and Tukey's post hoc test revealed the following total work/elapsed time results: 1 minute rest <30 seconds' rest, 30 seconds' MBPE. For each exercise, cumulative repetition results were as follows: 1 minute rest >30 seconds' rest, 30 seconds' MBPE. Results imply that rest period duration exerts more influence on resistance exercise performance than MBPE. Those who seek improved resistance exercise performance should pay particular attention to rest period durations.

Leg and calf press training modes and their impact on jump performance adaptations.

To examine the effects of resistance exercise (REX) mode on jump performance, subjects were assigned to one of three groups over a 6-week period with no cross-over. Subjects were assigned to leg and calf press REX on either a standard (n = 10) or ergometer (n = 9) device while a third group (n = 9) served as controls (CTRL). REX subjects worked out twice per week, which consisted of a three-set, 10-repetition paradigm for leg and calf press exercises. Immediately before and after the 6-week period, subjects performed tests that assessed jump (standing vertical jump, four-jump test protocol, depth jump) ability, while a fourth estimated knee extensor fast-twitch percentage (FT%) from fatigue incurred through a 50-repetition isokinetic protocol. Data analyses utilized 3 x 2 (group x time) repeated-measures ANCOVAs. Several dependent variables showed effects by group (standard REX, ergometer REX > CTRL) and time (post > pre). An interaction occurred for explosive leg power factor, a four-jump test variable, with standard REX post-test values as the interaction source. A trend for an interaction occurred for depth jump hang time, as ergometer REX values improved over time. Results suggest that mode-specific adaptations occur with REX training. Thus, athletes are best served with the selection of a REX device that is most specific to the demands of their jump performance task.

Body mass and exercise variable relationships to lactate derived from gravity-independent devices.

INTRODUCTION: Historically, exercise performance outcomes may be predicted with anthropometric variables such as body mass. To assess body mass and resistance exercise (REX) performance variable correlations to blood lactate values, subjects performed five different workouts on two devices that do not employ gravitational resistance. One device uses flywheels to impose a low-speed high-resistance exercise stimulus while the other, dubbed a Dual Performance Device (DPD), has a sled mounted on a very low friction track to enable high-speed low-resistance repetitions. METHODS: Subjects (n = 18) performed 3 leg press workouts on the flywheel ergometer (FE), which entailed: 1) a 3-set 10-repetition protocol with concentric and eccentric actions; or 2) the same set-repetition paradigm with concentric-only actions; or 3) a 6-set 10-repetition protocol of concentric-only actions. DPD workouts, done by a separate (n = 22) group, involved 2 workouts each composed exclusively of tonic or phasic seated knee and hip extensor repetitions. Multivariate regression was employed, with post-exercise and delta (post/ pre) blood lactate values as criterion measures. RESULTS: While body mass and performance values from FE workouts were weakly correlated to the criterion measures, body mass and average power (AP) variables from DPD tonic workouts explained 99% of the post-exercise and delta[BLa-] variance and yielded two prediction equations: post-REX blood lactate' = 0.06 + 11.21(AP) + -11.53(body mass), delta blood lactate' = 0.03 + 11.83(AP) + -12.00(body mass). CONCLUSIONS: Results were most likely due to differences in central command requirements for each exercise device.

Blood lactate responses to leg presses performed against inertial resistance.

INTRODUCTION: A flywheel ergometer has been devised which employs gravity-independent inertial resistance. Concentric and eccentric actions, which are integral to weight-bearing and ambulation activities, may be done on this ergometer. However, blood lactate responses to exercise on the ergometer by contractile mode and training volume are unknown. METHODS: Workout order was balanced so that subjects performed each type of ergometer leg press workout twice in a nonsequential manner. Per workout, 10 repetitions were performed per set. Workouts were as follows: three sets with concentric and eccentric (CE3) actions, three sets with concentric-only (CO3) actions, and six sets with concentric-only (CO6) actions. Pre- and 5-min post-exercise lactate was measured from a fingertip blood drop. Lactate means were compared with a 2 x 3 (time X workout) ANOVA with repeated measures applied to both independent variables and Scheffe's post hoc test. With body mass and performance measures as predictor variables, multivariate regression attempted to explain post-exercise and delta (post-pre) lactate variance. RESULTS: Post-exercise blood lactate values (mmol x L(-1), mean +/- SEM) were as follows: CE3, 8.08 +/- 0.44; CO3, 7.57 +/- 0.49; and CO6, 6.96 +/- 0.43. CE3 and CO6 workouts produced comparable volumes of work. Though several CE3 performance measures were significantly correlated to post-exercise and delta lactate values, power indices had the strongest relationship. DISCUSSION: Factors related to lactate production and clearance caused CE3 values to be highest. Power indices were most correlated to lactate as they denote a higher work rate and reliance on glycolysis.