Bench Press at Full Range of Motion Produces Greater Neuromuscular Adaptations Than Partial Executions After Prolonged Resistance Training.

ABSTRACT: Martínez-Cava, A, Hernández-Belmonte, A, Courel-Ibáñez, J, Morán-Navarro, R, González-Badillo, JJ, and Pallarés, JG. Bench press at full range of motion produces greater neuromuscular adaptations than partial executions after prolonged resistance training. J Strength Cond Res 36(1): 10-15, 2022-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.

Is the Functional Threshold Power a Valid Metric to Estimate the Maximal Lactate Steady State in Cyclists?

ABSTRACT: Lillo-Beviá, JR, Courel-Ibáñez, J, Cerezuela-Espejo, V, Morán-Navarro, R, Martínez-Cava, A, and Pallarés, JG. Is the functional threshold power a valid metric to estimate the maximal lactate steady state in cyclists? J Strength Cond Res 36(1): 167-173, 2022-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 (V̇o2max 59.7 ± 3.0 ml·kg-1·min-1) completed a maximal graded exercise test to record the power output associated with the first and second ventilatory thresholds and V̇o2max 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.

Previous Intensive Running or Swimming Negatively Affects CPR Effectiveness.

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.

A comprehensive analysis of the velocity-based method in the shoulder press exercise: stability of the load-velocity relationship and sticking region parameters.

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 [Vmax1], minimum velocity [Vmin], and second peak velocity [Vmax2]. 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% (Vmax1), 46.1% (Vmin), and 88.7% (Vmax2) of the concentric phase. These results may serve as a practical guideline to effectively implement the velocity-based method in the SP exercise.

Effect of Pause Versus Rebound Techniques on Neuromuscular and Functional Performance After a Prolonged Velocity-Based Training.

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 < .05), the PAUSE (effect size [ES] = 0.76-1.12) presented greater enhancements than REBOUND (ES = 0.45-0.92). Although not significant, improvements in Wingate and sprint time at 0 to 10 and 0 to 20 m were higher for PAUSE (ES = 0.31-0.46) compared with REBOUND (ES = 0.10-0.29). Conversely, changes on countermovement jump and sprint time at 10 to 20 m were superior for REBOUND (ES = 0.17-0.88) than for PAUSE (ES = 0.09-0.75). 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.

Linear programming produces greater, earlier and uninterrupted neuromuscular and functional adaptations than daily-undulating programming after velocity-based resistance training.

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<0.001), except the fatigue test in the DUP group. Significant "time x group" interactions were observed in all strength variables and fatigue test in favour of the LP group. In addition, pre-post effect size (ES), percentages of change and weekly comparisons showed higher improvements in the LP group (ES=0.54-2.49, ∆=9.5-60.4%) compared to DUP (ES=0.40-1.65, ∆=5.5-27.2%). Based on these findings, the LP appears to stand as a more effective strategy than DUP to achieve greater, earlier and uninterrupted neuromuscular and functional adaptations in VBRT interventions.

Load-velocity relationship of the deadlift exercise.

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 (R2 = 0.971 and R2 = 0.963) with a low error of estimation (SEE = 0.08 and 0.09 m·s-1), which was maintained throughout the wide breadth of velocities. PV showed the poorest results (R2 = 0.958, SEE = 0.15 m·s-1). MV attained with the 1RM was 0.24 ± 0.03 m·s-1 and consistent between participants with different relative strengths. The load that maximized the power output was identified at ∼60% 1RM. In contrast to what was observed in velocity, power outcomes showed poor predictive capacity to estimate %1RM. Hence, the use of velocity-based equations is advisable to monitor athletes' performance and adjust the training load in the deadlift exercise. This finding provides an alternative to the demanding, time-consuming and interfering 1RM tests, and allows the use of the deadlift exercise following the VBT principles.

Measuring the physiological impact of extreme heat on lifeguards during cardiopulmonary resuscitation. Randomized simulation study.

OBJECTIVE: Lifeguard teams carry out their work in extremely hot conditions in many parts of the world. The aim of this study was to analyze the impact of high temperatures on physiological parameters during cardiopulmonary resuscitation (CPR). METHOD: A randomized quasi-experimental cross-over design was used to test physiological lifesaving demands (50 min acclimatization +10 min CPR) in two different thermal environments: Thermo-neutral environment (25 °C) vs Hyperthermic environment (37 °C). RESULTS: The data obtained from 21 lifeguards were included, this covers a total of 420 min of resuscitation. The CPR performance was constantly maintained during the 10 min. The Oxygen uptake (VO 2) ranged from 17 to 18 ml/min/kg for chest compressions (CC) and between 13 and 14 ml/min/kg for ventilations (V) at both 25 °C and 37 °C, with no significant difference between environments (p > 0.05). The percentage of maximum heart rate (%HR max) increased between 7% and 8% at 37 °C (p < 0.001), ranging between 75% and 82% of HR max. The loss of body fluids (LBF) was higher in the hyperthermic environment; LBF: (37 °C: 400 ± 187 g vs 25 °C: 148 ± 81 g, p < 0.001). Body temperature was 1 °C higher at the end of the test (p < 0.001). The perceived fatigue (RPE) increased by 37° an average of 2 points on a scale of 10 (p = 0.001). CONCLUSIONS: Extreme heat is not a limiting factor in CPR performance with two lifeguards. Metabolic consumption is sustained, with an increase in CC, so V can serve as active rest. Nevertheless, resuscitation at 37 °C results in a higher HR, is more exhausting and causes significant loss of fluids due to sweating.

Correction: Reliability of technologies to measure the barbell velocity: Implications for monitoring resistance training.

[This corrects the article DOI: 10.1371/journal.pone.0232465.].

Reliability of technologies to measure the barbell velocity: Implications for monitoring resistance training.

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 <0.01m/s, MaxError = 1.3-2.2%1RM). The Speed4Lifts and STT were found as highly reliable, especially against lifting velocities ≤1.0 m/s (Speed4Lifts, SDC = 0.01-0.05 m/s; STT, SDC = 0.02-0.04 m/s), whereas the My Lift app showed the worst results with errors well above the acceptable levels (SDC = 0.26-0.34 m/s, MaxError = 18.9-24.8%1RM). T-Force stands as the preferable option to assess barbell velocity and to identify technical errors of measurement for emerging monitoring technologies. Both the Speed4Lifts and STT are fine alternatives to T-Force for measuring velocity against high-medium loads (velocities ≤ 1.0 m/s), while the excessive errors of the newly updated My Lift app advise against the use of this tool for velocity-based resistance training.

Time to exhaustion during cycling is not well predicted by critical power calculations.

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.

Full squat produces greater neuromuscular and functional adaptations and lower pain than partial squats after prolonged resistance training.

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.

Range of Motion and Sticking Region Effects on the Bench Press Load-Velocity Relationship.

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.

Reproducibility and Repeatability of Five Different Technologies for Bar Velocity Measurement in Resistance Training.

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).

A New Short Track Test to Estimate the V[Combining Dot Above]O2max and Maximal Aerobic Speed in Well-Trained Runners.

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; p < 0.05), 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, 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.

Validity of Skin, Oral and Tympanic Temperatures During Exercise in the Heat: Effects of Wind and Sweat.

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.

Velocity- and power-load relationships in the half, parallel and full back squat.

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 (R2 = 0.92-0.96) between load (%1RM) and bar velocity were found and they were specific for each squat variation, with faster velocities the greater the squat depth. Unlike the F-SQ and P-SQ, no sticking region was observed for the H-SQ when lifting high loads. The Pmax corresponded to a broad load range and was greatly influenced by how force output is calculated (including or excluding body mass) as well as the exact outcome variable used (MP, MPP, PP).

Movement Velocity as a Measure of Level of Effort During Resistance Exercise.

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 Relationship Between Lactate and Ventilatory Thresholds in Runners: Validity and Reliability of Exercise Test Performance Parameters.

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 (<3.1%), low bias (<0.5 km·h-1), and high correlation (ICC > 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 (<0.1 km·h-1; bias = 1.3; ICC = 0.82; p = 0.9l9), respectively. MLSS was identified as a different physiological event and a midpoint between VT1 (bias = -2.0 km·h-1) and VT2 (bias = 2.3 km·h-1). MAS was accurately estimated (SEM ± 0.3 km·h-1) from peak velocity (Vpeak) attained during GXT with the equation: MASEST (km·h-1) = Vpeak (km·h-1) * 0.8348 + 2.308. Current individualized GXT protocol based on individuals' MAS was solid to determine both maximal and submaximal physiological parameters. Lactate threshold tests can be a valid and reliable alternative to VT and MLSS to identify the workloads at the transition from aerobic to anaerobic metabolism in well-trained runners. In contrast with traditional assumption, the MLSS constituted a midpoint physiological event between VT1 and VT2 in runners. The Vpeak stands out as a powerful predictor of MAS.