Dynamic compression enhances pressure-to-pain threshold in elite athlete recovery: exploratory study. J Strength Cond Res 29(5): 1263–1272, 2015—Athlete recovery-adaptation is crucial to the progress and performance of highly trained athletes. The purpose of this study was to assess peristaltic pulse dynamic compression (PPDC) in reducing short-term pressure-to-pain threshold (PPT) among Olympic Training Center athletes after morning training. Muscular tenderness and stiffness are common symptoms of fatigue and exercise-induced muscle microtrauma and edema. Twenty-four highly trained athletes (men = 12 and women = 12) volunteered to participate in this study. The athletes were randomly assigned to experimental (n = 12) and control (n = 12) groups. Pressure-to-pain threshold measurements were conducted with a manual algometer on 3 lower extremity muscles. Experimental group athletes underwent PPDC on both legs through computer-controlled circumferential inflated leggings that used a peristaltic-like pressure pattern from feet to groin. Pressures in each cell were set to factory defaults. Treatment time was 15 minutes. The control group performed the same procedures except that the inflation pump to the leggings was off. The experimental timeline included a morning training session, followed by a PPT pretest, treatment application (PPDC or control), an immediate post-test (PPT), and a delayed post-test (PPT) after the afternoon practice session. Difference score results showed that the experimental group's PPT threshold improved after PPDC treatment immediately and persisted the remainder of the day after afternoon practice. The control group showed no statistical change. We conclude that PPDC is a promising means of accelerating and enhancing recovery after the normal aggressive training that occurs in Olympic and aspiring Olympic athletes.

While strength is indeed a skill, most discussions have primarily considered structural adaptations rather than ultrastructural augmentation to improve performance. Altering the structural component of the muscle is often the aim of hypertrophic training, yet not all hypertrophy is equal; such alterations are dependent upon how the muscle adapts to the training stimuli and overall training stress. When comparing bodybuilders to strength and power athletes such as powerlifters, weightlifters, and throwers, while muscle size may be similar, the ability to produce force and power is often inequivalent. Thus, performance differences go beyond structural changes and may be due to the muscle's ultrastructural constituents and training induced adaptations. Relative to potentiating strength and power performances, eliciting specific ultrastructural changes should be a variable of interest during hypertrophic training phases. By focusing on task-specific hypertrophy, it may be possible to achieve an optimal amount of hypertrophy while deemphasizing metabolic and aerobic components that are often associated with high-volume training. Therefore, the purpose of this article is to briefly address different types of hypertrophy and provide directions for practitioners who are aiming to achieve optimal rather than maximal hypertrophy, as it relates to altering ultrastructural muscular components, to potentiate strength and power performance.

One of the most meaningful technical innovations in cycling over the past two decades was the development of mobile power meters. With the ability to measure the physical strain under “real world” outdoor conditions, the knowledge of the demand during cycling has improved enormously. Power output has been described as the most direct measure of intensity during cycling and consequently power meters becomes a popular tool to monitor the training and racing of cyclists. However, only limited research data are available on the utilisation of power meters for performance assessment in the field or the analysis of training data. Therefore, the aims of the thesis were to evaluate the ecological validity of a field test, to provide an extensive insight into the longitudinal training strategies of world-class cyclists and to investigate the effects of interval training in the field at difference cadences. The first study aimed to assess the reproducibility of power output during a 4-min (TT4) and a 20-min (TT20) time-trial and the relationship with performance markers obtained during a laboratory graded exercise test (GXT). Ventilatory and lactate thresholds during a GXT were measured in competitive male cyclists (n = 15; VO2max 67 ± 5 mL . min−1 . kg−1; Pmax 440 ± 38 W ). Two 4- min and 20-min time-trials were performed on flat roads. Strong intraclass-correlations for TT4 (r = 0.98; 95 % CL: 0.92-0.99) and TT20 (r = 0.98; 95 % CL: 0.95-0.99) were observed. TT4 showed a bias ± random error of −0.8 ± 23W or −0.2 ± 5.5%. During TT20 the bias ± random error was −1.8 ± 14 W or 0.6 ± 4.4 %. Both time-trials were strongly correlated with performance measures from the GXT (p < 0.001). Significant differences were observed between power output during TT4 and GXT measures (p < 0.001). No significant differences were found between TT20 and power output at the second lactate-turn-point (LTP 2) (p = 0.98) and respiratory compensation point (RCP) (p = 0.97). In conclusion, TT4 and TT20 mean power outputs are reliable predictors of endurance performance. TT20 was in agreement with power output at RCP and LTP 2. Study two aimed to quantify power output (PO) and heart rate (HR) distributions across a whole season in elite cyclists. Power output and heart rate were monitored for 11 months in ten male (age: 29.1 ± 6.7 y; VO2max: 66.5 ± 7.1 mL . min−1 . kg−1) and one female (age: 23.1y; VO2max: 71.5 mL . min−1 . kg−1) cyclist. In total, 1802 data sets were sampled and divided into workout categories according to training goals. The PO at the RCP was used to determine seven intensity zones (Z1-Z7). PO and HR distributions into Z1-Z7 were calculated for all data and workout categories. The ratio of mean PO to RCP (intensity factor, IF) was assessed for each training session and for each interval during the training sessions (IFINT). Variability of PO was calculated as coefficient of variation (CV ). There was no significant difference in the distribution of PO and HR for the total season (p = 0.15), although significant differences between workout categories were observed (p < 0.001). Compared with PO, HR distributions showed a shift from low to high intensities. IF was significantly different between categories (p < 0.001). The IFINT was related to performance (p < 0.01), although the overall IF for the session was not. Also, total training time was related to performance (p < 0.05). The variability in PO was inversely associated with performance (p < 0.01). In conclusion, HR accurately reflects exercise intensity over a total season or low intensity workouts but is limited when applied to high intensity workouts. Better performance by cyclists was characterised by lower variability in PO, greater training volume and the production of higher exercise intensities during intervals. The third study tested the effects of low-cadence (60 rev . min−1) uphill (Int60) or high-cadence (100 rev . min−1) flat (Int100) interval training on PO during 20 min uphill (TTup) and flat (TTflat) time-trials. Eighteen male cyclists (VO2max: 58.6 ± 5.4 mL . min−1 . kg−1) were randomly assigned to Int60, Int100 or a control group (Con). The interval training comprised of two training sessions per week over four weeks, which consisted of 6 bouts of 5 min at the PO at RCP. For the control group, no interval training was conducted. A two-factor ANOVA revealed significant increases on performance measures obtained from GXT (Pmax: 2.8 ± 3.0 %; p < 0.01; PO and VO2 at RCP: 3.6 ± 6.3 % and 4.7 ± 8.2 %, respectively; p < 0.05; and VO2 at ventilatory threshold: 4.9 ± 5.6 %; p < 0.01), with no significant group effects. Significant interactions between group and the uphill and flat time-trials, pre vs. post-training on time-trial PO were observed (p < 0.05). Int60 increased PO during both, TTup (4.4 ± 5.3 %) and TTflat (1.5 ± 4.5 %), whereas the changes were − 1.3 ± 3.6 %; 2.6 ± 6.0 % for Int100 and 4.0 ± 4.6 %; − 3.5 ± 5.4 % for Con, during TTup and TTflat, respectively. PO was significantly higher during TTup than TTflat (4.4 ± 6.0 %; 6.3 ± 5.6 %; pre and post-training, respectively; p < 0.001). These findings suggest that higher forces during the low-cadence intervals are potentially beneficial to improve performance. In contrast to the GXT, the time-trials are ecologically valid to detect specific performance adaptations.