Influence of Movement Velocity on Accuracy of Estimated Repetitions to Failure in Resistance-Trained Men

2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Daniel A. Hackett
2017 ◽  
Vol 12 (10) ◽  
pp. 1378-1384 ◽  
Author(s):  
Miguel Sánchez-Moreno ◽  
David Rodríguez-Rosell ◽  
Fernando Pareja-Blanco ◽  
Ricardo Mora-Custodio ◽  
Juan José González-Badillo

Purpose: To analyze the relationship between movement velocity and relative load (%1RM) in the pull-up exercise (PU) and to determine the pattern of repetition-velocity loss during a single set to failure in pulling one’s own body mass. Methods: Fifty-two men (age = 26.5 ± 3.9 y, body mass = 74.3 ± 7.2 kg) performed a first evaluation (T1) consisting of an 1-repetition-maximum test (1RM) and a test of maximum number of repetitions to failure pulling one’s own body mass (MNR) in the PU exercise. Thirty-nine subjects performed both tests on a second occasion (T2) following 12 wk of training. Results: The authors observed a strong relationship between mean propulsive velocity (MPV) and %1RM (r = −.96). Mean velocity attained with 1RM load (V1RM) was 0.20 ± 0.05 m·s−1, and it influenced the MPV attained with each %1RM. Although 1RM increased by 3.4% from T1 to T2, the relationship between MPV and %1RM, and V1RM, remained stable. The authors also confirmed stability in the V1RM regardless of individual relative strength. The authors found a strong relationship between percentage of velocity loss and percentage of performed repetitions (R2 = .88), which remained stable despite a 15% increase in MNR. Conclusions: Monitoring repetition velocity allows estimation of the %1RM used as soon as the first repetition with a given load is performed, and the number of repetitions remaining in reserve when a given percentage of velocity loss is achieved during a PU exercise set.


Motricidade ◽  
2017 ◽  
Vol 13 (1) ◽  
pp. 1 ◽  
Author(s):  
Mário C. Marques

Intensity during strength training has been commonly identified with relative load (percentage of one-repetition maximum, 1RM) or with performing a given maximal number of repetitions in each set (XRM: 5RM, 10RM, 15 RM, etc.). Yet, none of these methods can be appropriate for precisely monitoring the real training effort in each training session.The first approach requires coaches to individually assess the 1RM value for each athlete. We may agree that expressing intensity as a percentage of the maximum repetition has the advantage that it can be used to program strength training for multiple athletes simultaneously, the loads being later transformed in absolute values (kg) for each individual. Further, another advantage is that this expression of the intensity can clearly reflect the dynamics of the evolution of the training load if we understand the percentage of 1RM as an effort, and not as a simple arithmetic calculus. Nevertheless, direct assessment of 1RM has some possible disadvantages worth noting. It may be associated with risk of injury when performed incorrectly or by novice athlete’s and it is time-consuming and impractical for large groups. Moreover, the actual RM can change quite rapidly after only a few training sessions and often the obtained value is not the subject’s true maximum.The classic way to prescribe loading intensity is to determine, through trial and error, the maximum number of repetitions that one can be performed with a given submaximal weight. For example, 5RM refers to a weight that can only be lifted five times. Some studies identified the relationship between selected percentages of 1RM and the number of repetitions to failure, establishing a repetition maximum continuum. It is believed that certain performance characteristics are best trained using specific RM load ranges. This method eliminates the need for a direct 1RM test, but it is not without drawbacks either. Using exhaustive efforts is common practice in strength training, but increasing evidence (Sanborn et al., 2000; Folland et al., 2002; Izquierdo et al., 2006; Drinkwater et al., 2007) shows that training to repetition failure does not necessarily produce better strength gains and that may even be counterproductive by inducing excessive fatigue, mechanical and metabolic strain (Fry, 2004). In fact, fatigue associated with training to failure not only significantly reduces the force that a muscle can generate, but also the nervous system’s ability to voluntarily activate the muscles (Häkkinen, 1993). Consequently, this approach, besides being very tiring and having shown no advantage over other lower effort types of training, it is unrealistic because it is practically impossible to know exactly how many repetitions can be done with a given absolute load without any initial reference. In addition, if in the first set the subject has completed the maximum number of repetitions, it will be very difficult or even impossible to perform properly the same number of reps in the following sets.Movement velocity is another variable which could be of great interest for monitoring exercise intensity, but surprisingly it has been vaguely mentioned in most studies to date. The importance that monitoring movement velocity for strength training programming have already been noticed in 1991 (González-Badillo, 1991). More recently, González-Badillo and Sánchez-Medina (2010, 2011) studied this hypothesis and confirmed that movement velocity provides as a determinant of the level of effort during resistance training as well as an indicator of the degree of fatigue. Unfortunately, the lack of use of this variable is likely because until recently it was not possible to accurately measure velocity in isoinertial strength training exercises/movements.  Indeed, most research that has addressed movement velocity in strength training was basically conducted using isokinetic apparatus which, unfortunately, is not an ideal or common training practice. The actual velocity performed in each repetition could be the best reference to determine accurately the real metabolic effort for each athlete. The higher the velocity achieved against a given (absolute) load, the greater the intensity with positive consequences for training effect (González Badillo and Ribas, 2002). Therefore, movement velocity should be the main “ingredient” of training intensity. With this approach, instead of a certain amount of weight to be lifted, coaches must be encouraging to prescribe strength training according to two important variables: 1) first repetition’s mean velocity, which is intrinsically related to loading intensity; and 2) a maximum percent velocity loss to be allowed in each set. When this percent loss limit is exceeding the set must be terminated. The limit of repetition velocity loss should be set beforehand depending on the primary training goal being pursued, the particular exercise to be performed as well as the training experience and performance level of each athlete.


2018 ◽  
pp. 36-39
Author(s):  
N Ikramov ◽  
T Majidov

The article brings up data on sediment diversity at watercourse bed and on their movement in the form of ridges. The ridge form movement of sediment leads to the reduction of reservoir volume and canal cross section area, which has an effect on their carrying capacity, filling of pump station forechambers and hydroelectric station pressure basins with sediment. The presence of sediment in flow leads to abrasive deterioration of pumps, water motors and pressure pipes and to other negative consequences. Research work tasks on the study of these effects have been examined with the purpose of preventing such negative consequences. On the basis of laboratory data diagrams and relationships were obtained for ridge length, height and movement velocity vs. sediment hydraulic and geometric sizes.


2020 ◽  
Vol 11 ◽  
Author(s):  
Bruno Fernández-Valdés ◽  
Jaime Sampaio ◽  
Juliana Exel ◽  
Jacob González ◽  
Julio Tous-Fajardo ◽  
...  

Author(s):  
Michael Rheese ◽  
Eric J. Drinkwater ◽  
Hans Leung ◽  
Justin W. Andrushko ◽  
Jacob Tober ◽  
...  

2014 ◽  
Vol 40 (2) ◽  
pp. 58-67
Author(s):  
Ruta Puziene ◽  
Asta Anikeniene ◽  
Gitana Karsokiene

In the research of vertical movements of the earth’s crust, examination of statistical correlations between the measured vertical movements of the earth’s crust and territorial geo-indexes is accomplished with the help of mathematical statistical analysis. Availability of the precise repeated levelling measuring data coupled with the preferred research methodology offer a chance to determine and predict recent vertical movements of the earth’s crust. For the inquiry into recent vertical movements of the earth’s crust, a Lithuanian class I vertical network levelling polygon was used. Drawing on measurements made in the polygon, vertical velocities of earth’s crust movements were calculated along the following levelling lines. For determining the relations shared by vertical movements of the earth’s crust and territorial geo-parameters, the following territory-defining parameters are accepted. Examination of the special qualities of relations shared by vertical movements of the earth’s crust and geo-parameters in the territory under research contributed to the computation of correlation matrices. Regression models are worked out taking into consideration only particular territory-defining geo-parameters, i.e. only those parameters which exhibit the following correlation coefficient value of the vertical earth’s crust movement velocity: r ≥ 0.50. A forecast of the velocities pertaining to vertical movements of the earth’s crust in the territory under examination was made with the application of regression models. Further in the process of this research, a map was compiled specifying the velocities of vertical movements of the earth’s crust in the territory. In the eastern part of this territory, the earth’s crust rises at a rate of up to 3 mm/year; while in the western part of it, the earth crust lowers at a rate of up to –1.5 mm/year. In order to pinpoint territories characterised by temperate and regular rising/lowering or intensive rising/lowering, a map of horizontal gradients of recent vertical earth crust movements in the territory enclosed by levelling polygon was compiled.


1998 ◽  
Vol 35 (4) ◽  
pp. 431-437 ◽  
Author(s):  
Michael P. Caligiuri ◽  
James B. Lohr ◽  
Robert K. Ruck
Keyword(s):  

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