The force platform is recognized as the ‘gold standard’ for testing vertical jumps. 1 – 3 The force platform estimates the velocity and power of the system center of mass from the directly recorded vertical ground reaction force data using the direct dynamic approach. Due to potential
Alejandro Pérez-Castilla, Belén Feriche, Slobodan Jaric, Paulino Padial and Amador García-Ramos
Pedro Jiménez-Reyes, Fernando Pareja-Blanco, David Rodríguez-Rosell, Mario C. Marques and Juan José González-Badillo
To determine what variables determine the differences in performance on 2 tests of squat jump (SJ) performed under light load in highly trained athletes using maximal velocity (Vmax) or flight time (FT) as the discriminating factor of SJ performance.
Thirty-two participants performed 2 maximal weighted SJs using a force platform synchronized with a linear transducer. Mean force (Fmean), mean and maximal power (Pmean, Pmax), peak force (PF), maximal rate of force development (RFDmax), and time required to attain PF (TPF) and RFDmax (TRFDmax) were analyzed. SJs were divided into 2 segments: from the initiation of force application to PF1 and from the moment after PF1 to Vmax.
Traditional significance statistics revealed significant differences in the same variables between best and worst SJs using both FT and Vmax. However, to use an approach based on the magnitude of the effect, the best SJ showed greater Pmax (83/17/0%), Pmean (85/15/0%), Fmean (71/29/0%), RFDmax1 (73/27/0%), and PF1 (53/47/0%) and lower TPF2 (0/61/39%) than the worst SJ when Vmax was used to discriminate SJ performance. However, using FT to differentiate SJ performance, no difference was observed between best and worst.
Although jump height assessed through FT is a valid measure, these results suggest that Vmax is a more sensitive variable than FT to detect differences in loaded-SJ performance.
Veena Iyengar, Marcio J. Santos and Alexander S. Aruin
We investigated whether slower velocity of arm movement affects grip-force generation in conditions with the finger touch provided to the wrist of the target arm. Nine subjects performed the task of lifting and transporting an object at slow, intermediate, and fast velocities with a light finger touch from the contralateral arm and without it. There was an effect of velocity of arm movement on grip-force generation in both conditions. However, when the no touch and touch trials performed with similar velocity were matched, the effect of touch on grip-force reduction was statistically significant (p < .001). The observed decrease in grip force could not be explained by slower movement execution in the touch conditions and underlines the importance of using a contralateral touch in the performance of activities of daily living. It also points to a possibility of the development of therapeutic advances for the enhancement of grip-force control in patients with neurological impairments.
James J. Tufano, Jenny A. Conlon, Sophia Nimphius, Lee E. Brown, Harry G. Banyard, Bryce D. Williamson, Leslie G. Bishop, Amanda J. Hopper and G. Gregory Haff
To determine the effects of intraset rest frequency and training load on muscle time under tension, external work, and external mechanical power output during back-squat protocols with similar changes in velocity.
Twelve strength-trained men (26.0 ± 4.2 y, 83.1 ± 8.8 kg, 1.75 ± 0.06 m, 1.88:0.19 one-repetition-maximum [1RM] body mass) performed 3 sets of 12 back squats using 3 different set structures: traditional sets with 60% 1RM (TS), cluster sets of 4 with 75% 1RM (CS4), and cluster sets of 2 with 80% 1RM (CS2). Repeated-measures ANOVAs were used to determine differences in peak force (PF), mean force (MF), peak velocity (PV), mean velocity (MV), peak power (PP), mean power (MP), total work (TW), total time under tension (TUT), percentage mean velocity loss (%MVL), and percentage peak velocity loss (%PVL) between protocols.
Compared with TS and CS4, CS2 resulted in greater MF, TW, and TUT in addition to less MV, PV, and MP. Similarly, CS4 resulted in greater MF, TW, and TUT in addition to less MV, PV, and MP than TS did. There were no differences between protocols for %MVL, %PVL, PF, or PP.
These data show that the intraset rest provided in CS4 and CS2 allowed for greater external loads than with TS, increasing TW and TUT while resulting in similar PP and %VL. Therefore, cluster-set structures may function as an alternative method to traditional strength- or hypertrophy-oriented training by increasing training load without increasing %VL or decreasing PP.
David Hawkins and Mark Smeulders
The purpose of this study was to determine if the characteristic Hill model, used to describe me force–velocity relationship for isolated tetanically stimulated muscle, could be modified and used to describe me torque–velocity behavior of me hip for maximally and submaximally stimulated hip extensor muscles. Fourteen subjects performed hip extension movements at effort levels of 100%, 70%, and 40% of a maximum isometric effort. A solenoid provided isometric resistance to hip extension. Once the desired effort level was achieved, as indicated by me isometric force, the solenoid released and me hip moved against an opposing elastic resistance equal to 75%, 50%, 25%, and 0% of the specified effort level. An electrogoniometer quantified hip angle. Hip velocity was determined by numerically differentiating the angle data. Torque-velocity-activation (or effort level) data were determined for each trial. Model parameters were determined to give me best fit to the data for each subject. Average parameter values were determined for each gender and for the entire group. The modified Hill-type model, T m = (T max · A − K 1 · ω)/(K2 · ω + 1), accurately describes me relationship between joint torque (T m), maximum isometric joint torque (T max), joint velocity (ω), and muscle activation level (A) for subject-specific parameters (K 1 and K 2), but not for parameters averaged across genders or the entire group. Values for T max, K 1, and K 2 ranged from 90 to 385 Nm, 6.1 to 47.9 Nms, and 0.030 to 0.716 s, respectively.
Anson B. Rosenfeldt, Amanda L. Penko, Andrew S. Bazyk, Matthew C. Streicher, Tanujit Dey and Jay L. Alberts
Gait impairment is a hallmark of Parkinson’s disease (PD) with up to 87% of individuals exhibiting gait dysfunction in the early stages of diagnosis ( Kang et al., 2005 ). Primary gait impairments in PD include decreased cadence, velocity, step length, and arm swing ( Morris, Huxham, McGinley, Dodd
Harry G. Banyard, Kazunori Nosaka, Alex D. Vernon and G. Gregory Haff
demonstrated an inverse linear relationship exists between load and velocity (load–velocity profile [LVP]), meaning that if maximal effort is given for the concentric phase of a lift, heavier loads cannot be lifted with the same velocity as lighter loads. 4 – 8 Furthermore, if maximal concentric effort is
Ian N. Bezodis, David G. Kerwin, Stephen-Mark Cooper and Aki I.T. Salo
There has been continued interest into the effect of step length and step frequency on sprint performance (velocity), specifically recently looking at the acceleration phase of the sprint. 1 – 3 Furthermore, research into the maximum velocity phase has been inconclusive in identifying the most
Irineu Loturco, Lucas A. Pereira, Ciro Winckler, Weverton L. Santos, Ronaldo Kobal and Michael McGuigan
The load–velocity relationship is widely recognized for its ability to accurately predict the 1-repetition maximum (1RM) in both lower-body and upper-body exercises. 1 – 3 With the data generated by linear-regression models, practitioners can frequently monitor and adjust the resistance
Scott R. Brown, Erin R. Feldman, Matt R. Cross, Eric R. Helms, Bruno Marrier, Pierre Samozino and Jean-Benoît Morin
portion of ground reaction force production and is central to sprint acceleration. 5 Moreover, the measurement of F H forms the basis on which force-velocity profiling can be performed as an assessment tool to determine asymmetry and guide training periodization. 5 , 6 In sprinting, targeted