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Martinez-Cava, A, Hernandez-Belmonte, A, Courel-Ibanez, J, Moran-Navarro, R, Gonzalez-Badillo, JJ, and Pallares, JG. Bench press at full range of motion produces greater neuromuscular adaptations than partial executions after prolonged resistance training. J Strength Cond Res XX(X): 000-000, 2019-Training at a particular range of motion (ROM) produces specific neuromuscular adaptations. However, the effects of full and partial ROM in one of the most common upper-limb exercises such as the bench press (BP) remain controversial. In this study, 50 recreationally to highly resistance trained men were randomly assigned to 1 of 4 training groups: full bench press (BPFULL), two-thirds bench press (BP2/3), and one-third bench press (BP1/3) and control (training cessation). Experimental groups completed a 10-week velocity-based resistance training program using the same relative load (linear periodization, 60-80% 1 repetition maximum [1RM]), only differing in the ROM trained. Individual ROM for each BP variation was determined in the familiarization and subsequently replicated in every lift during training and testing sessions. Neuromuscular adaptations were evaluated by 1RM strength and mean propulsive velocity (MPV). The BPFULL group obtained the best results for the 3 BP variations (effect size [ES] = 0.52-1.96); in turn, partial BP produced smaller improvements as the ROM decreased (BP2/3: ES = 0.29-0.78; BP1/3: ES = -0.01 to 0.66). After 10-week of training cessation, the control group declined in all neuromuscular parameters (ES = 0.86-0.92) except in MPV against low loads. Based on these findings, the BPFULL stands as the most effective exercise to maximize neuromuscular improvements in recreational and well-trained athletes compared with partial ROM variations.

The purpose of this study was threefold: i) to analyse the load-velocity relationship of the shoulder press (SP) exercise, ii) to investigate the stability (intra-individual variability) of this load-velocity relationship for athletes with different relative strength levels, and after a 10-week velocity-based resistance training (VBT), and iii) to describe the velocity-time pattern of the SP: first peak velocity [V max1 ], minimum velocity [V min ], and second peak velocity [V max2 ]. This study involves a cross-sectional (T1, n = 48 subjects with low, medium and high strength levels) and longitudinal (T2, n = 24 subjects randomly selected from T1 sample) design. In T1, subjects completed a progressive loading test up to the 1RM in the SP exercise. The barbell mean, peak and mean propulsive velocities (MV, PV and MPV) were monitored. In T2, subjects repeated the loading test after 10 weeks of VBT. There were very close relationships between the %1RM and velocity attained in the three velocity outcomes (T1, R2 : MV = 0.970; MPV = 0.969; PV = 0.954), being even stronger at the individual level (T1, R2 = 0.973–0.997). The MPV attained at the 1RM (~0.19 m·s-1) was consistent among different strength levels. Despite the fact that 1RM increased ~17.5% after the VBT programme, average MPV along the load-velocity relationship remained unaltered between T1 and T2 (0.69 ± 0.06 vs. 0.70 ± 0.06 m·s-1). Lastly, the three key parameters of the velocity-time curve were detected from loads > 74.9% 1RM at 14.3% (V max1 ), 46.1% (V min ), and 88.7% (V max2 ) of the concentric phase. These results may serve as a practical guideline to effectively implement the velocity-based method in the SP exercise.

La pandemia actual por la Covid-19 y su consecuente distanciamiento social ha acelerado la transformación de la educación tradicional hacia la educación en línea. Sin embargo, esta transformación se ha adaptado a nivel tecnológico, pero no pedagógico. El objetivo de este estudio ha sido analizar la adquisición de conocimientos anatómicos de los estudiantes de CAFD mediante el uso de vídeos e imágenes estáticas de surf gestionadas a través de un blog. Un total de 106 estudiantes del grado de CAFD participaron en el presente trabajo. Para el análisis del efecto en el aprendizaje se ha realizado un examen que contenía cinco preguntas sobre la anatomía aplicada al surf tras la visualización de los vídeos/imágenes. Tras el análisis estadístico, se observó un porcentaje de aciertos de 66.0%, 51.9%, 62.3% y 63.2%, para las preguntas 1, 2, 4 y 5 respectivamente. Esta metodología basada esencialmente en un análisis del movimiento permite una comprensión funcional de la anatomía del aparato locomotor en el deporte de aventura de surf. Estos resultados muestran una metodología útil y novedosa para el desarrollo de docencia online. Además, revelan el amplio margen con el que se cuenta para mejora de la enseñanza de la anatomía en CAFD mediante el uso combinado de las nuevas tecnologías.

Survival outcomes increase significantly when cardiopulmonary resuscitation (CPR) is provided correctly, but rescuers’ fatigue can compromise its delivery. We investigated the effect of two exercise modes on CPR effectiveness and physiological outputs. After 4 min baseline conditions, 30 lifeguards randomly performed a 100 m run and a combined water rescue before 4 min CPR (using an adult manikin and a 30:2 compression–ventilation ratio). Physiological variables were continuously measured during baseline and CPR using a portable gas analyzer (K4b2, Cosmed, Rome, Italy) and CPR effectiveness was analyzed using two HD video cameras. Higher oxygen uptake (23.0 ± 9.9 and 20.6 ± 9.1 vs. 13.5 ± 6.2 mL·kg·min−1) and heart rate (137 ± 19 and 133 ± 15 vs. 114 ± 15 bpm), and lower compression efficacy (63.3 ± 29.5 and 62.2 ± 28.3 vs. 69.2 ± 28.0%), were found for CPRrun and CPRswim compared to CPRbase. In addition, ventilation efficacy was higher in the rescues preceded by intense exercise than in CPRbase (49.5 ± 42.3 and 51.9 ± 41.0 vs. 33.5 ± 38.3%), but no differences were detected between CPRrun and CPRswim. In conclusion, CPRrun and CPRswim protocols induced a relevant physiological stress over each min and in the overall CPR compared with CPRbase. The CPRun protocol reduces the compression rate but has a higher effectiveness percentage than the CPRswim protocol, in which there is a considerably higher compression rate but with less efficacy.

This study aimed to analyze the influence of range of motion (ROM) on main biomechanical parameters of the bench press (BP) exercise: i) load-velocity relationship by mean (MV) and mean propulsive velocity (MPV), ii) one-repetition maximum strength (1RM); iii) contribution of the propulsive and braking phases, and iv) presence of the sticking region key parameters (first peak barbell velocity: Vmax1, minimum velocity: Vmin and second peak barbell velocity: Vmax2). Forty-two strength-trained males performed a progressive loading test, starting at 20 kg and gradually increasing the load in 10 kg until MPV ≤ 0.50 m·s-1 and 5 down to 2.5 kg until 1RM, in three different ROMs: full ROM (BPFULL), two-thirds (BP2/3) and one-third (BP1/3). While significant differences were detected in the velocity attained against loads between 30-95% 1RM (BPFULL, BP2/3 and BP1/3, p < 0.05), both MV and MPV showed a very close relationship to %1RM for the three BP variations (R2 = 0.935-0.966). The contribution of the braking phase decreased progressively until it completely disappeared at the 80%, 95% and 100% 1RM loads in BP1/3, BP2/3 and BPFULL, respectively. The 1RM increased as the ROM decreased (BPFULL < BP2/3 < BP1/3, p < 0.05). Despite the three biomechanical parameters that define the sticking region on the velocity-time curves were only observed in BPFULL variation, in 54.5% of the cases the subjects started their BP2/3 displacement before reaching the position at which the Vmin occurs in their BPFULL exercise. The complete or partial presence of the sticking region during the concentric action of the lift seems to underlie the differences in the 1RM strength, load-velocity profiles and the contribution of the propulsive phase in the BP exercise at different ROMs.

Lillo-Bevia, JR, Courel-Ibanez, J, Cerezuela-Espejo, V, Moran-Navarro, R, Martinez-Cava, A, and Pallares, JG. Is the functional threshold power a valid metric to estimate the maximal lactate steady state in cyclists? J Strength Cond Res XX(X): 000-000, 2019-The aims of this study were to determine (a) the repeatability of a 20-minute time-trial (TT20), (b) the location of the TT20 in relation to the main physiological events of the aerobic-anaerobic transition, and (c) the predictive power of a list of correction factors and linear/multiple regression analysis applied to the TT20 result to estimate the individual maximal lactate steady state (MLSS). Under laboratory conditions, 11 trained male cyclists and triathletes (V[Combining Dot Above]O2max 59.7 ± 3.0 ml·kg·min) completed a maximal graded exercise test to record the power output associated with the first and second ventilatory thresholds and V[Combining Dot Above]O2max measured by indirect calorimetry, several 30 minutes constant tests to determine the MLSS, and 2 TT20 tests with a short warm-up. Very high repeatability of TT20 tests was confirmed (standard error of measurement of ±3 W and smallest detectable change of ±9 W). Validity results revealed that MLSS differed substantially from TT20 (bias = 26 ± 7 W). The maximal lactate steady state was then estimated from the traditional 95% factor (bias = 12 ± 7 W) and a novel individual correction factor (ICF% = MLSS/TT20), resulting in 91% (bias = 1 ± 6 W). Complementary linear (MLSS = 0.7488 × TT20 + 43.24; bias = 0 ± 5 W) and multiple regression analysis (bias = 0 ± 4 W) substantially improved the individual MLSS workload estimation. These findings suggest reconsidering the TT20 procedures and calculations to increase the effectiveness of the MLSS prediction.

Morán-Navarro, R, Martínez-Cava, A, Sánchez-Medina, L, Mora-Rodríguez, R, González-Badillo, JJ, and Pallarés, JG. Movement velocity as a measure of level of effort during resistance exercise. J Strength Cond Res 33(6): 1496-1504, 2019-This study analyzed whether the loss of repetition velocity during a resistance exercise set was a reliable indicator of the number of repetitions left in reserve. After the assessment of one-repetition (1RM) strength and full load-velocity relationship, 30 men were divided into 3 groups according to their 1RM strength per body mass: novice, well trained, and highly trained. On 2 separate occasions and in random order, subjects performed tests of maximal number of repetitions to failure against loads of 65, 75, and 85% 1RM in 4 exercises: bench press, full squat, prone bench pull, and shoulder press. For each exercise, and regardless of the load being used, the absolute velocities associated with stopping a set before failure, leaving a certain number of repetitions (2, 4, 6, or 8) in reserve, were very similar and showed a high reliability (coefficient of variation [CV] 4.4-8.0%). No significant differences in these stopping velocities were observed for any resistance training exercise analyzed between the novice, well trained and highly trained groups. These results indicate that by monitoring repetition velocity one can estimate with high accuracy the proximity of muscle failure and, therefore, to more objectively quantify the level of effort and fatigue being incurred during resistance training. This method emerges as a substantial improvement over the use of perceived exertion to gauge the number of repetitions left in reserve.

The choice of the optimal squatting depth for resistance training (RT) has been a matter of debate for decades and is still controversial. In this study, fifty-three resistance-trained men were randomly assigned to one of four training groups: full squat (F-SQ), parallel squat (P-SQ), half squat (H-SQ), and Control (training cessation). Experimental groups completed a 10-week velocity-based RT programme using the same relative load (linear periodization from 60% to 80% 1RM), only differing in the depth of the squat trained. The individual range of motion and spinal curvatures for each squat variation were determined in the familiarization and subsequently replicated in every lift during the training and testing sessions. Neuromuscular adaptations were evaluated by one-repetition maximum strength (1RM) and mean propulsive velocity (MPV) at each squatting depth. Functional performance was assessed by countermovement jump, 20-m sprint and Wingate tests. Physical functional disability included pain and stiffness records. F-SQ was the only group that increased 1RM and MPV in the three squat variations (ES = 0.77-2.36), and achieved the highest functional performance (ES = 0.35-0.85). P-SQ group obtained the second best results (ES = 0.15-0.56). H-SQ produced no increments in neuromuscular and functional performance (ES = -0.11-0.28) and was the only group reporting significant increases in pain, stiffness and physical functional disability (ES = 1.21-0.87). Controls declined on all tests (ES = 0.02-1.32). We recommend using F-SQ or P-SQ exercises to improve strength and functional performance in well-trained athletes. In turn, the use of H-SQ is inadvisable due to the limited performance improvements and the increments in pain and discomfort after continued training.

Pallares, JG, Cerezuela-Espejo, V, Moran-Navarro, R, Martinez-Cava, A, Conesa, E, and Courel-Ibanez, J. A new short track test to estimate the V[Combining Dot Above]O2max and maximal aerobic speed in well-trained runners. J Strength Cond Res 33(5): 1216-1221, 2019-This study was designed to validate a new short track test (Track(1:1)) to estimate running performance parameters maximal oxygen uptake (V[Combining Dot Above]O2max) and maximal aerobic speed (MAS), based on a laboratory treadmill protocol and gas exchange data analysis (Lab(1:1)). In addition, we compared the results with the University of Montreal Track Test (UMTT). Twenty-two well-trained male athletes (V[Combining Dot Above]O2max 60.3 ± 5.9 ml·kg·min; MAS ranged from 17.0 to 20.3 km·h) performed 4 testing protocols: 2 in laboratory (Lab(1:1)-pre and Lab(1:1)) and 2 in the field (UMTT and Track(1:1)). The Lab(1:1)-pre was designed to determine individuals' Vpeak and set initial speeds for the subsequent Lab(1:1) short ramp graded exercise testing protocol, starting at 13 km·h less than each athlete's Vpeak, with 1 km·h increments per minute until exhaustion. The Track(1:1) was a reproduction of the Lab(1:1) protocol in the field. A novel equation was yielded to estimate the V[Combining Dot Above]O2max from the Vpeak achieved in the Track(1:1). Results revealed that the UMTT significantly underestimated the Vpeak (-4.2%; bias = -0.8 km·h; p 0.05). Thus, the current Track(1:1) test emerges as a better alternative than the UMTT to estimate maximal running performance parameters in well-trained and highly trained athletes on the field.

This study aimed to analyze the agreement between five bar velocity monitoring devices, currently used in resistance training, to determine the most reliable device based on reproducibility (between-device agreement for a given trial) and repeatability (between-trial variation for each device). Seventeen resistance-trained men performed duplicate trials against seven increasing loads (20-30-40-50-60-70-80 kg) while obtaining mean, mean propulsive and peak velocity outcomes in the bench press, full squat and prone bench pull exercises. Measurements were simultaneously registered by two linear velocity transducers (LVT), two linear position transducers (LPT), two optoelectronic camera-based systems (OEC), two smartphone video-based systems (VBS) and one accelerometer (ACC). A comprehensive set of statistics for assessing reliability was used. Magnitude of errors was reported both in absolute (m s−1) and relative terms (%1RM), and included the smallest detectable change (SDC) and maximum errors (MaxError). LVT was the most reliable and sensitive device (SDC 0.02–0.06 m s−1, MaxError 3.4–7.1% 1RM) and the preferred reference to compare with other technologies. OEC and LPT were the second-best alternatives (SDC 0.06–0.11 m s−1), always considering the particular margins of error for each exercise and velocity outcome. ACC and VBS are not recommended given their substantial errors and uncertainty of the measurements (SDC > 0.13 m s−1).

This study aims to identify the measurement error associated with the mean movement velocity when using high-speed camera-based methods and video analysis during resistance training. Eleven resistance-trained men (26.0 ± 3.4 years) completed a progressive loading test in bench press exercise. Measurements from concentric mean velocity (MV), distance and time were obtained from a linear velocity transducer (T-Force) and videos recorded with high speed cameras on readily available smartphones (Samsung S6, Xiaomi A1, and iPhone X) and digital photo cameras (Casio FH20). Videos were examined using video analysis software (Kinovea). Despite the high correlations detected, the Bland-Altman analyses revealed that all high speed cameras produced substantial overestimation of barbell MV against high loads >60% 1RM (MV error = 0.06 ± 0.03 m·s−1 to 0.08 ± 0.04 m·s−1), but mainly against low loads

This study aimed to compare the effect of linear (LP) and daily-undulating (DUP) programming models on neuromuscular and functional performance using the velocity-based resistance training (VBRT) approach. Thirty-two resistance trained men were randomly assigned into 2 groups: LP (n = 16) or DUP (n = 16). Both training groups completed an 8-week VBRT intervention using the full squat exercise, only differing in the relative intensity (% 1RM) distribution during the training program. Changes produced by each periodization model were evaluated using the following variables: estimated 1RM; average mean propulsive velocity (MPV) attained for all absolute loads common to Pre-test and Post-test; average MPV attained against absolute loads lifted faster than 1 m•s−1; average MPV attained against absolute loads lifted slower than 1 m•s − 1; countermovement jump (CMJ) and fatigue test. Moreover, CMJ and 1RM parameters were evaluated weekly to analyze their evolution along the training program. LP and DUP strategies significantly improved all performance variables analyzed (p

Velocity-based training (VBT) is gaining popularity in strength and conditioning due to multiple practical advantages for auto-regulating and individualizing training volume and load on a day-to-day basis. Because the load-velocity relationship varies among exercises, the knowledge of particular equations is indispensable to effectively implement the VBT. The aim of this study was to determine the complete load- and power-velocity profile of the deadlift exercise to provide practical equations and normative values for resistance training coaches and practitioners. Twenty strength-trained men performed a progressive loading test at maximal intended velocity to determine their one-repetition maximum (1RM). Mean (MV), mean propulsive (MPV) and peak velocity (PV) were measured during the concentric phase. Both MV and MPV showed a very close relationship to %1RM (R

Purpose: A variation of the traditional squat (SQ) rebound technique (REBOUND) including a momentary pause ∼2 seconds (PAUSE) between eccentric and concentric phases has been proposed. Although there is a consensus about the lower acute effects on performance of this PAUSE variant compared with traditional REBOUND technique, no information exists about the differences in longitudinal adaptations of these SQ executions. Methods: A total of 26 men were randomly assigned into the PAUSE (n = 13) or REBOUND (n = 13) groups and completed a 10-week velocity-based training using the SQ exercise, only differing in the technique. Neuromuscular adaptations were assessed by the changes in the 1-repetition maximum strength and mean propulsive velocity achieved against the absolute loads (in kilograms) common to pretest and posttest. Functional performance was evaluated by the following tests: countermovement jump, Wingate, and sprint time at 0 to 10, 10 to 20, and 0 to 20 m. Results: Whereas both groups showed significant increases in most of the neuromuscular tests (P Conclusion: Imposing a pause between eccentric and concentric phases in the SQ exercise could be an interesting strategy to increase neuromuscular and functional adaptations in sport actions that mainly depend on concentric contractions. Moreover, sport abilities highly dependent on the stretch-shortening cycle could benefit from the REBOUND or a combination of the 2 techniques.

Three to 5 cycling tests to exhaustion allow prediction of time to exhaustion (TTE) at power output based on calculation of critical power (CP). We aimed to determine the accuracy of CP predictions of TTE at power outputs habitually endured by cyclists. Fourteen endurance-trained male cyclists underwent 4 randomized cycle-ergometer TTE tests at power outputs eliciting (i) mean Wingate anaerobic test (WAnTmean), (ii) maximal oxygen consumption, (iii) respiratory compensation threshold (VT2), and (iv) maximal lactate steady state (MLSS). Tests were conducted in duplicate with coefficient of variation of 5%–9%. Power outputs were 710 ± 63 W for WAnTmean, 366 ± 26 W for maximal oxygen consumption, 302 ± 31 W for VT2 and 247 ± 20 W for MLSS. Corresponding TTE were 00:29 ± 00:06, 03:23 ± 00:45, 11:29 ± 05:07, and 76:05 ± 13:53 min:s, respectively. Power output associated with CP was only 2% lower than MLSS (242 ± 19 vs. 247 ± 20 W; P < 0.001). The CP predictions overestimated TTE at WAnTmean (00:24 ± 00:10 mm:ss) and MLSS (04:41 ± 11:47 min:s), underestimated TTE at VT2 (–04:18 ± 03:20 mm:ss; P < 0.05), and correctly predicted TTE at maximal oxygen consumption. In summary, CP accurately predicts MLSS power output and TTE at maximal oxygen consumption. However, it should not be used to estimate time to exhaustion in trained cyclists at higher or lower power outputs (e.g., sprints and 40-km time trials). Novelty CP calculation enables to predict TTE at any cycling power output. We tested those predictions against measured TTE in a wide range of cycling power outputs. CP appropriately predicted TTE at maximal oxygen consumption intensity but err at higher and lower cycling power outputs.

This study investigated the inter- and intra-device agreement of four new devices marketed for barbell velocity measurement. Mean, mean propulsive and peak velocity outcomes were obtained for bench press and full squat exercises along the whole load-velocity spectrum (from light to heavy loads). Measurements were simultaneously registered by two linear velocity transducers T-Force, two linear position transducers Speed4Lifts, two smartphone video-based systems My Lift, and one 3D motion analysis system STT. Calculations included infraclass correlation coefficient (ICC), Bland-Altman Limits of Agreement (LoA), standard error of measurement (SEM), smallest detectable change (SDC) and maximum errors (MaxError). Results were reported in absolute (m/s) and relative terms (%1RM). Three velocity segments were differentiated according to the velocity-load relationships for each exercise: heavy (≥ 80% 1RM), medium (50% < 1RM < 80%) and light loads (≤ 50% 1RM). Criteria for acceptable reliability were ICC > 0.990 and SDC < 0.07 m/s (~5% 1RM). The T-Force device shown the best intra-device agreement (SDC = 0.01–0.02 m/s, LoA

This study aimed to compare the load-velocity and load-power relationships of three common variations of the squat exercise. 52 strength-trained males performed a progressive loading test up to the one-repetition maximum (1RM) in the full (F-SQ), parallel (P-SQ) and half (H-SQ) squat, conducted in random order on separate days. Bar velocity and vertical force were measured by means of a linear velocity transducer time-synchronized with a force platform. The relative load that maximized power output (Pmax) was analyzed using three outcome measures: mean concentric (MP), mean propulsive (MPP) and peak power (PP), while also including or excluding body mass in force calculations. 1RM was significantly different between exercises. Load-velocity and load-power relationships were significantly different between the F-SQ, P-SQ and H-SQ variations. Close relationships (R

The aim of this study was to quantify peak age and improvements over the preceding years to peak age in elite athletic contestants according to athlete performance level, sex, and discipline. Individual season bests for world-ranked top 100 athletes from 2002 to 2016 (14,937 athletes and 57,049 individual results) were downloaded from the International Association of Athletics Federations’ website. Individual performance trends were generated by fitting a quadratic curve separately to each athlete’s performance and age data using a linear modeling procedure. Mean peak age was typically 25–27 y, but somewhat higher for marathon and male throwers (∼28–29 y). Women reached greater peak age than men in the hurdles and middle- and long-distance running events (mean difference, ±90% CL: 0.6, ±0.3 to 1.9, ±0.3 y: small to moderate). Male throwers had greater peak age than corresponding women (1.3, ±0.3 y: small). Throwers displayed the greatest performance improvements over the 5 y prior to peak age (mean [SD]: 7.0% [2.9%]), clearly ahead of jumpers, long-distance runners, hurdlers, middle-distance runners, and sprinters (3.4, ±0.2% to 5.2, ±0.2%; moderate to large). Similarly, top 10 athletes showed greater improvements than top 11–100 athletes in all events (1.0, ±0.9% to 1.8, ±1.1%; small) except throws. Women improved more than men in all events (0.4, ±0.2% to 2.9, ±0.4%) except sprints. This study provides novel insight on performance development in athletic contestants that are useful for practitioners when setting goals and evaluating strategies for achieving success.

To describe the acute and delayed time course of recovery following resistance training (RT) protocols differing in the number of repetitions (R) performed in each set (S) out of the maximum possible number (P). Ten resistance-trained men undertook three RT protocols [S × R(P)]: (1) 3 × 5(10), (2) 6 × 5(10), and (3) 3 × 10(10) in the bench press (BP) and full squat (SQ) exercises. Selected mechanical and biochemical variables were assessed at seven time points (from − 12 h to + 72 h post-exercise). Countermovement jump height (CMJ) and movement velocity against the load that elicited a 1 m s−1 mean propulsive velocity (V1) and 75% 1RM in the BP and SQ were used as mechanical indicators of neuromuscular performance. Training to muscle failure in each set [3 × 10(10)], even when compared to completing the same total exercise volume [6 × 5(10)], resulted in a significantly higher acute decline of CMJ and velocity against the V1 and 75% 1RM loads in both BP and SQ. In contrast, recovery from the 3 × 5(10) and 6 × 5(10) protocols was significantly faster between 24 and 48 h post-exercise compared to 3 × 10(10). Markers of acute (ammonia, growth hormone) and delayed (creatine kinase) fatigue showed a markedly different course of recovery between protocols, suggesting that training to failure slows down recovery up to 24–48 h post-exercise. RT leading to failure considerably increases the time needed for the recovery of neuromuscular function and metabolic and hormonal homeostasis. Avoiding failure would allow athletes to be in a better neuromuscular condition to undertake a new training session or competition in a shorter period of time.

The use of bar velocity to estimate relative load in the back squat exercise was examined. 80 strength-trained men performed a progressive loading test to determine their one-repetition maximum (1RM) and load-velocity relationship. Mean (MV), mean propulsive (MPV) and peak (PV) velocity measures of the concentric phase were analyzed. Both MV and MPV showed a very close relationship to %1RM (R2=0.96), whereas a weaker association (R2=0.79) and larger SEE (0.14 vs. 0.06 m·s−1) were found for PV. Prediction equations to estimate load from velocity were obtained. When dividing the sample into 3 groups of different relative strength (1RM/body mass), no differences were found between groups for the MPV attained against each %1RM. MV attained with the 1RM was 0.32±0.03 m·s−1. The propulsive phase accounted for ~82% of concentric duration at 40% 1RM, and progressively increased until reaching 100% at 1RM. Provided that repetitions are performed at maximal intended velocity, a good estimation of load (%1RM) can be obtained from mean velocity as soon as the first repetition is completed. This finding provides an alternative to the often demanding, time-consuming and interfering 1RM or nRM tests and allows implementing a velocity-based resistance training approach.

This study aimed to analyze the influence of range of motion (ROM) on main biomechanical parameters of the bench press (BP) exercise: i) load-velocity relationship by mean (MV) and mean propulsive velocity (MPV), ii) one-repetition maximum strength (1RM); iii) contribution of the propulsive and braking phases, and iv) presence of the sticking region key parameters (first peak barbell velocity: V(max1), minimum velocity: V(min) and second peak barbell velocity: V(max2)). Forty-two strength-trained males performed a progressive loading test, starting at 20 kg and gradually increasing the load in 10 kg until MPV ≤ 0.50 m·s(-1) and 5 down to 2.5 kg until 1RM, in three different ROMs: full ROM (BP(FULL)), two-thirds (BP(2/3)) and one-third (BP(1/3)). While significant differences were detected in the velocity attained against loads between 30-95% 1RM (BP(FULL), BP(2/3) and BP(1/3), p < 0.05), both MV and MPV showed a very close relationship to %1RM for the three BP variations (R(2) = 0.935-0.966). The contribution of the braking phase decreased progressively until it completely disappeared at the 80%, 95% and 100% 1RM loads in BP(1/3), BP(2/3) and BP(FULL), respectively. The 1RM increased as the ROM decreased (BP(FULL) < BP(2/3) < BP(1/3), p < 0.05). Despite the three biomechanical parameters that define the sticking region on the velocity-time curves were only observed in BP(FULL) variation, in 54.5% of the cases the subjects started their BP(2/3) displacement before reaching the position at which the V(min) occurs in their BP(FULL) exercise. The complete or partial presence of the sticking region during the concentric action of the lift seems to underlie the differences in the 1RM strength, load-velocity profiles and the contribution of the propulsive phase in the BP exercise at different ROMs.

Pallarés, JG, Cerezuela-Espejo, V, Morán-Navarro, R, Martínez-Cava, A, Conesa, E, and Courel-Ibáñez, J. A new short track test to estimate the V[Combining Dot Above]O2max and maximal aerobic speed in well-trained runners. J Strength Cond Res 33(5): 1216-1221, 2019-This study was designed to validate a new short track test (Track(1:1)) to estimate running performance parameters maximal oxygen uptake (V[Combining Dot Above]O2max) and maximal aerobic speed (MAS), based on a laboratory treadmill protocol and gas exchange data analysis (Lab(1:1)). In addition, we compared the results with the University of Montreal Track Test (UMTT). Twenty-two well-trained male athletes (V[Combining Dot Above]O2max 60.3 ± 5.9 ml·kg·min; MAS ranged from 17.0 to 20.3 km·h) performed 4 testing protocols: 2 in laboratory (Lab(1:1)-pre and Lab(1:1)) and 2 in the field (UMTT and Track(1:1)). The Lab(1:1)-pre was designed to determine individuals' Vpeak and set initial speeds for the subsequent Lab(1:1) short ramp graded exercise testing protocol, starting at 13 km·h less than each athlete's Vpeak, with 1 km·h increments per minute until exhaustion. The Track(1:1) was a reproduction of the Lab(1:1) protocol in the field. A novel equation was yielded to estimate the V[Combining Dot Above]O2max from the Vpeak achieved in the Track(1:1). Results revealed that the UMTT significantly underestimated the Vpeak (-4.2%; bias = -0.8 km·h; p0.05), which notably altered the estimations (MAS: -2.6%, bias = -0.5 km·h; V[Combining Dot Above]O2max: 4.7%, bias = 2.9 ml·kg·min). In turn, data from Track(1:1) were very similar to the laboratory test and gas exchange methods (Vpeak: -0.6%, bias =0.1 km·h; MAS: 0.3%, bias =0.1 km·h; V[Combining Dot Above]O2max: 0.4%, bias = 0.2 ml·kg·min, p0.05). Thus, the current Track(1:1) test emerges as a better alternative than the UMTT to estimate maximal running performance parameters in well-trained and highly trained athletes on the field.

The use of bar velocity to estimate relative load in the back squat exercise was examined. 80 strength-trained men performed a progressive loading test to determine their one-repetition maximum (1RM) and load-velocity relationship. Mean (MV), mean propulsive (MPV) and peak (PV) velocity measures of the concentric phase were analyzed. Both MV and MPV showed a very close relationship to %1RM (R 2 =0.96), whereas a weaker association (R 2 =0.79) and larger SEE (0.14 vs. 0.06 m·s −1 ) were found for PV. Prediction equations to estimate load from velocity were obtained. When dividing the sample into 3 groups of different relative strength (1RM/body mass), no differences were found between groups for the MPV attained against each %1RM. MV attained with the 1RM was 0.32±0.03 m·s −1 . The propulsive phase accounted for ~82% of concentric duration at 40% 1RM, and progressively increased until reaching 100% at 1RM. Provided that repetitions are performed at maximal intended velocity, a good estimation of load (%1RM) can be obtained from mean velocity as soon as the first repetition is completed. This finding provides an alternative to the often demanding, time-consuming and interfering 1RM or nRM tests and allows implementing a velocity-based resistance training approach.

The aims of this study were (1) to establish the best fit between ventilatory and lactate exercise performance parameters in running and (2) to explore novel alternatives to estimate the maximal aerobic speed (MAS) in well-trained runners. Twenty-two trained male athletes (V˙O2max 60.2 ± 4.3 ml·kg·min−1) completed three maximal graded exercise tests (GXT): (1) a preliminary GXT to determine individuals' MAS; (2) two experimental GXT individually adjusted by MAS to record the speed associated to the main aerobic–anaerobic transition events measured by indirect calorimetry and capillary blood lactate (CBL). Athletes also performed several 30 min constant running tests to determine the maximal lactate steady state (MLSS). Reliability analysis revealed low CV ( 0.91) for all determinations except V-Slope (ICC = 0.84). Validity analysis showed that LT, LT+1.0, and LT+3.0 mMol·L−1 were solid predictors of VT1 (−0.3 km·h−1; bias = 1.2; ICC = 0.90; p = 0.57), MLSS (−0.2 km·h−1; bias = 1.2; ICC = 0.84; p = 0.74), and VT2 (

This experiment investigates the validity of six thermometers with different measuring sensors, operation and site of application, to estimate core temperature (Tc) in comparison to an ingestible thermometric sensor based on quartz crystal technology. Measurements were obtained before, during and after exercise in the heat, controlling the presence of air-cooling and skin sweating. Twelve well-trained men swallowed the ingestible thermometer 6 h before the trial. After pre-exercise resting measurements at 20 °C, subjects entered a heat chamber held at 40 °C. Exercise in the heat consisted of 60 min of pedalling on cycle ergometer at 90% of the individually determined first ventilatory threshold. Results reveal that wind and skin sweat invalidate the use of skin infrared thermometry to estimate Tc during exercise in the heat. However, better Tc estimations were obtained in wind-restricted situations. We detected important differences between same-technology devices but different models and brands. In conclusion, there are important limitations to assess Tc accurately using non-invasive thermometers during and after exercise in the heat. Because some devices showed better validity than others did, we recommended using tympanic Braun®, and non-contact skin infrared Medisana® or Visiofocus® in wind-restricted and no sweat conditions to estimate Tc during exercise in the heat.

El propósito de este estudio ha sido describir los cambios que sufre el estado de ánimo que presentan los deportistas de combate durante las fases de bajada de peso y su posterior recuperación antes del comienzo de los eventos competitivos prioritarios de la temporada. Un total de 105 hombres y mujeres especialistas en las modalidades de combate de lucha olímpica, taekwondo y boxeo fueron pesados y contestaron la versión abreviada del Perfil de Estados de Ánimo (POMS) entre 30 y 60 minutos antes del pesaje oficial (PRE) y entre 30 y 60 minutos antes del comienzo del primer combate (POST) de sus respectivos campeonatos nacionales. Los resultados demostraron que las hubo mejoras significativas (p < .05) en las dimensiones de Cólera, Fatiga y Depresión, aunque estos cambios no parecen estar relacionados con la variación porcentual de la masa corporal que experimentan los deportistas durante este mismo periodo (r < .261). Estos hallazgos nos indican que las 12-18 horas que separan el pesaje oficial y el comienzo del torneo en deportes de combate propician mejoras sustanciales en sus estados de ánimo, aunque estos cambios parecen ser independientes de sus fluctuación de la masa corporal. ABSTRACT: The purpose of this study was to describe changes in the mood state of combat sport athletes during the weight cutting phases and subsequent recovery before the start of the main competitive events of the season. One hundred and five men and women combat sport specialist of Olympic wrestling, taekwondo and boxing were weighted and answered the abbreviated version of the Profile of Mood States (POMS) 30 to 60 minutes before the official weigh-in (PRE) and 30 to 60 minutes before the start of the first bout (POST) of their respective national championships. The results showed significant improvements (p < .05) in the Anger, Fatigue and Depression dimensions, although these changes do not appear to be related to the percentage change in the body mass experienced by these athletes during the same period (r < .261). These findings indicate that the 12-18 hours that separate the official weigh-in and the start of the tournament produce substantial improvements on the athletes´ mood state, although these changes seems to be independent on their body mass oscillations RESUMO: O objetivo deste estudo foi descrever as alterações sofridas pelo clima que os atletas lutaram durante as fases de redução de peso e subsequente recuperação antes do início dos eventos prioritários da temporada competitivos. Um total de 105 homens e mulheres especialistas nas categorias de combate de wrestling, taekwondo e boxe foram pesados e responderam a versão curta do Profile of Mood States (POMS) entre 30 e 60 minutos antes da pesagem oficial (PRE) e entre 30 e 60 minutos antes do início do primeiro ataque (POST) nos seus respectivos campeonatos nacionais. Os resultados mostraram que houve melhora significativa (p

Purpose The purpose of this study was to determine, i) the reliability of blood lactate and ventilatory-based thresholds, ii) the lactate threshold that corresponds with each ventilatory threshold (VT1 and VT2) and with maximal lactate steady state test (MLSS) as a proxy of cycling performance. Methods Fourteen aerobically-trained male cyclists ([Formula: see text] 62.1±4.6 ml·kg-1·min-1) performed two graded exercise tests (50 W warm-up followed by 25 W·min-1) to exhaustion. Blood lactate, [Formula: see text] and [Formula: see text] data were collected at every stage. Workloads at VT1 (rise in [Formula: see text];) and VT2 (rise in [Formula: see text]) were compared with workloads at lactate thresholds. Several continuous tests were needed to detect the MLSS workload. Agreement and differences among tests were assessed with ANOVA, ICC and Bland-Altman. Reliability of each test was evaluated using ICC, CV and Bland-Altman plots. Results Workloads at lactate threshold (LT) and LT+2.0 mMol·L-1 matched the ones for VT1 and VT2, respectively (p = 0.147 and 0.539; r = 0.72 and 0.80; Bias = -13.6 and 2.8, respectively). Furthermore, workload at LT+0.5 mMol·L-1 coincided with MLSS workload (p = 0.449; r = 0.78; Bias = -4.5). Lactate threshold tests had high reliability (CV = 3.4-3.7%; r = 0.85-0.89; Bias = -2.1-3.0) except for DMAX method (CV = 10.3%; r = 0.57; Bias = 15.4). Ventilatory thresholds show high reliability (CV = 1.6%-3.5%; r = 0.90-0.96; Bias = -1.8-2.9) except for RER = 1 and V-Slope (CV = 5.0-6.4%; r = 0.79; Bias = -5.6-12.4). Conclusions Lactate threshold tests can be a valid and reliable alternative to ventilatory thresholds to identify the workloads at the transition from aerobic to anaerobic metabolism.

Background It is habitual for combat sports athletes to lose weight rapidly to get into a lower weight class. Fluid restriction, dehydration by sweating (sauna or exercise) and the use of diuretics are among the most recurrent means of weight cutting. Although it is difficult to dissuade athletes from this practice due to the possible negative effect of severe dehydration on their health, athletes may be receptive to avoid weight cutting if there is evidence that it could affect their muscle performance. Therefore, the purpose of the present study was to investigate if hypohydration, to reach a weight category, affects neuromuscular performance and combat sports competition results. Methods We tested 163 (124 men and 39 woman) combat sports athletes during the 2013 senior Spanish National Championships. Body mass and urine osmolality (UOSM) were measured at the official weigh-in (PRE) and 13–18 h later, right before competing (POST). Athletes were divided according to their USOM at PRE in euhydrated (EUH; UOSM 250–700 mOsm · kgH2O−1), hypohydrated (HYP; UOSM 701–1080 mOsm · kgH2O−1) and severely hypohydrated (S-HYP; UOSM 1081–1500 mOsm · kgH2O−1). Athletes’ muscle strength, power output and contraction velocity were measured in upper (bench press and grip) and lower body (countermovement jump - CMJ) muscle actions at PRE and POST time-points. Results At weigh-in 84 % of the participants were hypohydrated. Before competition (POST) UOSM in S-HYP and HYP decreased but did not reach euhydration levels. However, this partial rehydration increased bench press contraction velocity (2.8-7.3 %; p < 0.05) and CMJ power (2.8 %; p < 0.05) in S-HYP. Sixty-three percent of the participants competed with a body mass above their previous day’s weight category and 70 of them (69 % of that sample) obtained a medal. Conclusions Hypohydration is highly prevalent among combat sports athletes at weigh-in and not fully reversed in the 13–18 h from weigh-in to competition. Nonetheless, partial rehydration recovers upper and lower body neuromuscular performance in the severely hypohydrated participants. Our data suggest that the advantage of competing in a lower weight category could compensate the declines in neuromuscular performance at the onset of competition, since 69 % of medal winners underwent marked hypohydration.

El objetivo de esta investigación es validar nuevas ecuaciones de regresión para estimar el valor de fuerza dinámica máxima absoluta (1RM) mediante test de máximo número de repeticiones hasta el fallo muscular (nRM) ejecutados con técnica de parada o stop. Igualmente, se estudian los niveles de validez que presentan las ecuaciones que ya se encuentran actualmente definidas en la literatura internacional para estimar la mag- nitud de la carga (%1RM) y el valor de 1RM a partir de un test nRM en ejecuciones con técnica de parada. Los resultados indican que las nuevas ecuaciones propuestas en esta investigación [1RM en Press Banca = masa desplazada en kg (-0,01841*nRM)+0,981; 1RM en Sentadilla Completa = masa desplazada en kg (-0,01176*nRM)+0,975]muestran indicadores sus- tancialmente mejores de validez(ET = 1,8-2,2 kg; R2 = 0,956-0,988), y por lo tanto de mayor capacidad predictiva, que el resto de ecuaciones definidas en la literatura internacional hasta la fecha. ABSTRACT: This study validates new regression equations to estimate the value of the absolute maximum dynamic strength (1RM) by means of a maximum number of repetitions test to muscular failure (nRM) executed with stop technique. Also, this study assesses the validity of the equations that are already stablished in the international publications to estimate the load (% 1RM) and the 1RM value from a nRM test in executions with stop technique. The results indicate that the new equations proposed in this research [Bench Press 1RM = weight lifted in kg (-0,01841*nRM)+0,981; Full Squat 1RM = weight lifted in kg (-0,01176*nRM)+0,975] show sub- stantially better validity levels (SEM = 1,8-2,2 kg; R2 = 0,956-0,988), and therefore of greater predictive ability, than the rest of equations described in the international literature to date

La natación tiene unas circunstancias especiales a la hora de entrenar y monitorizar la actividad física que se lleva a cabo. Esto ha hecho que a lo largo del tiempo hayan surgido investigaciones y recursos que nos permitan controlar el proceso de entrenamiento de manera efectiva con alternativas a las variables clásicas. Además, el comportamiento fisiológico en el medio acuático varía respecto al ejercicio físico fuera de él, lo que también hace que sean necesarias algunas adaptaciones metodológicas. Actualmente la natación es un deporte creciente por su gran importancia dentro del triatlón, y las nuevas tecnologías también han logrado ofrecernos nuevas vías para el entendimiento y control del proceso formativo y de entrenamiento. El correcto manejo de las variables que determinan la carga de entrenamiento es la clave para conseguir las adaptaciones que nos aporten una mejora o nos ayude a contrarrestar los factores limitantes del rendimiento. Este trabajo muestra las principales modificaciones que requiere la programación del volumen, intensidad y densidad del entrenamiento en el medio acuático ABSTRACT: The swimming has special circumstances when it comes to train and monitor physical activity. This has meant that over time have arisen research and resources that enable us to control the training process effectively with alternatives to the classic variables. In addition, the physiological behaviour in the acuatic environment varies from the exercise out of it, which also makes some methodological adaptations are necessary. Currently swimming is a growing sport for its great importance in the triathlon, and new technologies have also managed to offer new avenues for understanding and control of the training process and training. The correct handling of the variables that determine the training load is the key to the adaptations that bring us a better or help us counter the limiting factors of performance. This paper shows the main changes required volume programming, training intensity and density in the aquatic environment

Background In Olympic combat sports, weight cutting is a common practice aimed to take advantage of competing in weight divisions below the athlete's normal weight. Fluid and food restriction in combination with dehydration (sauna and/or exercise induced profuse sweating) are common weight cut methods. However, the resultant hypohydration could adversely affect health and performance outcomes. Purpose The aim of this study is to determine which of the routinely used non-invasive measures of dehydration best track urine osmolality, the gold standard non-invasive test. Method Immediately prior to the official weigh-in of three National Championships, the hydration status of 345 athletes of Olympic combat sports (i.e., taekwondo, boxing and wrestling) was determined using five separate techniques: i) urine osmolality (UOSM), ii) urine specific gravity (USG), iii) urine color (UCOL), iv) bioelectrical impedance analysis (BIA), and v) thirst perception scale (TPS). All techniques were correlated with UOSM divided into three groups: euhydrated (G1; UOSM 250–700 mOsm·kg H2O−1), dehydrated (G2; UOSM 701–1080 mOsm·kg H2O−1), and severely dehydrated (G3; UOSM 1081–1500 mOsm·kg H2O−1). Results We found a positive high correlation between the UOSM and USG (r = 0.89: p = 0.000), although this relationship lost strength as dehydration increased (G1 r = 0.92; G2 r = 0.73; and G3 r = 0.65; p = 0.000). UCOL showed a moderate although significant correlation when considering the whole sample (r = 0.743: p = 0.000) and G1 (r = 0.702: p = 0.000) but low correlation for the two dehydrated groups (r = 0.498–0.398). TPS and BIA showed very low correlation sizes for all groups assessed. Conclusion In a wide range of pre-competitive hydration status (UOSM 250–1500 mOsm·kg H2O−1), USG is highly associated with UOSM while being a more affordable and easy to use technique. UCOL is a suitable tool when USG is not available. However, BIA or TPS are not sensitive enough to detect hypohydration at official weight-in before an Olympic combat championship.