The purpose of this study was to assess validity and reliability of sprint performance outcomes measured with an iPhone application (named: MySprint) and existing field methods (i.e. timing photocells and radar gun). To do this, 12 highly trained male sprinters performed 6 maximal 40-m sprints during a single session which were simultaneously timed using 7 pairs of timing photocells, a radar gun and a newly developed iPhone app based on high-speed video recording. Several split times as well as mechanical outputs computed from the model proposed by Samozino et al. [(2015). A simple method for measuring power, force, velocity properties, and mechanical effectiveness in sprint running. Scandinavian Journal of Medicine & Science in Sports. https://doi.org/10.1111/sms.12490] were then measured by each system, and values were compared for validity and reliability purposes. First, there was an almost perfect correlation between the values of time for each split of the 40-m sprint measured with MySprint and the timing photocells (r = 0.989-0.999, standard error of estimate = 0.007-0.015 s, intraclass correlation coefficient (ICC) = 1.0). Second, almost perfect associations were observed for the maximal theoretical horizontal force (F), the maximal theoretical velocity (V), the maximal power (P) and the mechanical effectiveness (DRF - decrease in the ratio of force over acceleration) measured with the app and the radar gun (r = 0.974-0.999, ICC = 0.987-1.00). Finally, when analysing the performance outputs of the six different sprints of each athlete, almost identical levels of reliability were observed as revealed by the coefficient of variation (MySprint: CV = 0.027-0.14%; reference systems: CV = 0.028-0.11%). Results on the present study showed that sprint performance can be evaluated in a valid and reliable way using a novel iPhone app.
The absence of significant correlations between some of the FV relationship parameters suggests that for an individualized training prescription based on the FV profile both jumping and sprinting testing procedures should be performed with elite female soccer players.
García-Ramos, A, González-Hernández, JM, Baños-Pelegrín, E, Castaño-Zambudio, A, Capelo-Ramírez, F, Boullosa, D, Haff, GG, and Jiménez-Reyes, P. Mechanical and metabolic responses to traditional and cluster set configurations in the bench press exercise. J Strength Cond Res XX(X): 000-000, 2017-This study aimed to compare mechanical and metabolic responses between traditional (TR) and cluster (CL) set configurations in the bench press exercise. In a counterbalanced randomized order, 10 men were tested with the following protocols (sets × repetitions [inter-repetition rest]): TR1: 3 × 10 (0-second), TR2: 6 × 5 (0-second), CL5: 3 × 10 (5-second), CL10: 3 × 10 (10-second), and CL15: 3 × 10 (15-second). The number of repetitions (30), interset rest (5 minutes), and resistance applied (10 repetition maximum) were the same for all set configurations. Movement velocity and blood lactate concentration were used to assess the mechanical and metabolic responses, respectively. The comparison of the first and last set of the training session revealed a significant decrease in movement velocity for TR1 (Effect size [ES]: -0.92), CL10 (ES: -0.85), and CL15 (ES: -1.08) (but not for TR2 [ES: -0.38] and CL5 [ES: -0.37]); while blood lactate concentration was significantly increased for TR1 (ES: 1.11), TR2 (ES: 0.90), and CL5 (ES: 1.12) (but not for CL10 [ES: 0.03] and CL15 [ES: -0.43]). Based on velocity loss, set configurations were ranked as follows: TR1 (-39.3 ± 7.3%) > CL5 (-20.2 ± 14.7%) > CL10 (-12.9 ± 4.9%), TR2 (-10.3 ± 5.3%), and CL15 (-10.0 ± 2.3%). The set configurations were ranked as follows based on the lactate concentration: TR1 (7.9 ± 1.1 mmol·L) > CL5 (5.8 ± 0.9 mmol·L) > TR2 (4.2 ± 0.7 mmol·L) > CL10 (3.5 ± 0.4 mmol·L) and CL15 (3.4 ± 0.7 mmol·L). These results support the use of TR2, CL10, and CL15 for the maintenance of high mechanical outputs, while CL10 and CL15 produce less metabolic stress than TR2.
This study aimed to compare mechanical, metabolic, and perceptual responses between two traditional (TR) and four cluster (CL) set configurations. In a counterbalanced randomized order, 11 men were tested with the following protocols in separate sessions (sets × repetitions [inter-repetition rest]): TR1: 3×10 [0-s]; TR2: 6×5 [0-s]; CL1: 3×10 [10-s]; CL2: 3×10 [15-s]; CL3: 3×10 [30-s]); CL4: 1×30 [15-s]). The exercise (full-squat), number of repetitions (30), inter-set rest (5 min), and resistance applied (10RM) was the same for all set configurations. Mechanical fatigue was quantified by measuring the mean propulsive velocity during each repetition, and the change in countermovement jump height observed after each set and after the whole training session. Metabolic and perceptual fatigue were assessed via the blood lactate concentration and the OMNI perceived exertion scale measured after each training set, respectively. The mechanical, metabolic, and perceptual measures of fatigue were always significantly higher for the TR1 set configuration. The two set configurations that most minimized the mechanical measures of fatigue were CL2 and CL3. Perceived fatigue did not differ between the TR2, CL1, CL2 and CL3 set configurations. The lowest lactate concentration was observed in the CL3 set configuration. Therefore, both the CL2 and CL3 set configurations can be recommended because they maximize mechanical performance. However, the CL2 set configuration presents two main advantages with respect to CL3: (1) it reduces training session duration, and (2) it promotes higher metabolic stress, which to some extent may be beneficial for inducing muscle strength and hypertrophy gains.
BackgroundMovement velocity has been proposed as an effective tool to prescribe the load during resistance training in young healthy adults. This study aimed to elucidate whether movement velocity could also be used to estimate the relative load (i.e., % of the one-repetition maximum (1RM)) in older women.MethodsA total of 22 older women (age = 68.2 ± 3.6 years, bench press 1RM = 22.3 ± 4.7 kg, leg press 1RM = 114.6 ± 15.9 kg) performed an incremental loading test during the free-weight bench press and the leg press exercises on two separate sessions. The mean velocity (MV) was collected with a linear position transducer.ResultsA strong linear relationship between MV and the relative load was observed for the bench press (%1RM = −130.4 MV + 119.3;r2= 0.827, standard error of the estimate (SEE) = 6.10%1RM,p< 0.001) and leg press exercises (%1RM = −158.3 MV + 131.4;r2= 0.913, SEE = 5.63%1RM,p< 0.001). No significant differences were observed between the bench press and leg press exercises for the MV attained against light-medium relative loads (≤70%1RM), while the MV associated with heavy loads (≥80%1RM) was significantly higher for the leg press.ConclusionsThese results suggest that the monitoring of MV could be useful to prescribe the loads during resistance training in older women. However, it should be noted that the MV associated with a given %1RM is significantly lower in older women compared to young healthy individuals.
Uric acid (UA) is the most abundant antioxidant compound in saliva and one of the most sensitive biomarkers for detecting changes in the oxidative status of the organism. The aim of this study was to evaluate the effect of: (i) different methods of saliva sampling and (ii) the correction by salivary flow or total protein on UA concentrations in saliva. Paired saliva (collected by two different methods, passive drooling and using Salivette cotton rolls) and serum samples were obtained from 12 healthy men after the performance of two resistance training exercises of different level of effort that can produce different concentrations in UA in saliva. There were no significant differences between values of uric acid in saliva using Salivette and passive drool. Correlations between UA in serum and saliva and increases in UA in saliva after exercise were detected when saliva samples were obtained by passive drool and Salivette and were not corrected by salivary flow or total protein concentration. Therefore for UA measurements in saliva it would not be recommended to normalize the results by salivary flow or protein concentration. This study highlights the importance of choosing an adequate sampling method selection as well as the expression of results when analytes are measured in saliva.
Cuevas-Aburto, J, Jukic, I, Chirosa-Ríos, LJ, González-Hernández, JM, Janicijevic, D, Barboza-González, P, Guede-Rojas, F, and García-Ramos, A. Effect of traditional, cluster, and rest redistribution set configurations on neuromuscular and perceptual responses during strength-oriented resistance training. J Strength Cond Res 36(6): 1490–1497, 2022—This study aimed to compare the acute effect of traditional (TR), cluster (CL), and rest redistribution (RR) set configurations on neuromuscular and perceptual measures of fatigue. Thirty-one resistance-trained men randomly performed a Control session and 3 experimental sessions consisting of the squat (SQ) and bench press (BP) exercises performed against the 10 repetition maximum load using TR (3 sets of 6 repetitions; 3 minutes of interset rest), CL (3 sets of 6 repetitions; 30 seconds of intraset rest every 2 repetitions; 3 minutes of interset rest), and RR (9 sets of 2 repetitions; 45 seconds of interset rest) set configurations. A significant effect of “set configuration” (p = 0.002) was observed for barbell velocity. The average velocity of the training session was lower for TR compared with CL (% difference = 5.09% in SQ and 5.68% in BP) and RR (% difference = 5.92% in SQ and 2.71% in BP). The 3 set configurations induced comparable decrements in countermovement jump height (% difference from −6.0% to −8.1%) and throwing velocity (% difference from −0.6% to −1.2%). Ratings of perceived exertion (RPE-10) values collected after the sets were higher for TR (SQ: 6.9 ± 0.7 a.u.; BP: 6.8 ± 0.8 a.u.) compared with CL (SQ: 6.2 ± 0.8 a.u.; BP: 6.4 ± 0.7 a.u.) and RR (SQ: 6.2 ± 0.8 a.u.; BP: 6.6 ± 0.9 a.u.), while the session RPE did not differ between the set configurations (p = 0.595). CL and RR set configurations allow for higher velocities and lower RPE values during resistance training sessions not performed to failure in comparison with a TR set configuration.
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