What is the Best Method for Assessing Lower Limb Force-Velocity Relationship?

Giroux, Caroline; Rabita, Giuseppe; Chollet, Didier; Guilhem, Gaël

doi:10.1055/s-0034-1385886

Cited by 66 publications

(103 citation statements)

References 38 publications

(43 reference statements)

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“…Such results have been consistently observed from cycling [13–16], jumping [17–19], running [20, 21], leg push offs [4, 22–24], lifting [13, 25, 26] etc. Of utmost importance is that most of the cited studies revealed the correlation coefficients of the linear model applied to individual sets of data well above 0.9.…”

Section: Force-velocity Relationship Of Muscles Performing Functiosupporting

confidence: 55%

“…In addition, no significant differences in the strength of the relationships were found between the linear and polynomial regression models applied on the same sets of F and V data [18, 19, 25] suggesting that the assessed F-V relationships could be considered linear for further computation. Of importance could also be that the parameters depicting the maximum F, V and P of the tested muscles (i.e., the regression parameters F 0 , V 0 , and P 0 , respectively) proved to be highly reliable [17, 18, 24–26] and at least moderately valid [15, 17–19]. Finally, several studies have already showed that the same parameters could also be sensitive enough to detect the differences among various populations regarding the discussed muscle capacities [13, 16, 23, 27].…”

Section: Force-velocity Relationship Of Muscles Performing Functiomentioning

confidence: 99%

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Two-Load Method for Distinguishing Between Muscle Force, Velocity, and Power-Producing Capacities

Jarić

2016

Sports Med

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It has been generally accepted that muscles could have different mechanical capacities, such as those for producing high force (F), velocity (V), and power (P) outputs. Nevertheless, the standard procedures of the evaluation of muscle function both in research and routine testing are typically conducted under a single mechanical condition, such as under a single external load. Therefore, the observed outcomes do not allow for distinguishing among the different muscle capacities. As a result, the outcomes of most of the routine testing procedures have been of limited informational value, while a number of debated issues in research have originated from arbitrarily interpreted experimental findings regarding specific muscle capacities. A solution for the discussed problem could be based on the approximately linear and exceptionally strong F-V relationship typically observed from various functional tasks performed under different external loads. These findings allow for the 'two-loads method' proposed in this Current Opinion: the functional movement tasks (e.g., maximum jumping, cycling, running, pushing, lifting, or throwing) should be tested against just 2 distinctive external loads. Namely, the F-V relationship determined by 2 pairs of the F and V data could provide the parameters depicting the maximum F (i.e., the F-intercept), V (V-intercept), and P (calculated from the product of F and V) output of the tested muscles. Therefore, the proposed two-loads method applied in both research and routine testing could provide a deeper insight into the mechanical properties and function of the tested muscles and resolve a number of debated issues in the literature.

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Section: Force-velocity Relationship Of Muscles Performing Functiosupporting

confidence: 55%

Section: Force-velocity Relationship Of Muscles Performing Functiomentioning

confidence: 99%

Two-Load Method for Distinguishing Between Muscle Force, Velocity, and Power-Producing Capacities

Jarić

2016

Sports Med

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“…The relative difference between actual and optimal F-v profiles for a given individual represents the magnitude and the direction of the unfavorable balance between force and velocity qualities (i.e., force-velocity imbalance, FV imb in %), which makes possible the individual determination of force or velocity deficit. The actual individual F-v profile and P max can be easily determined from a series of loaded vertical jumps (Samozino et al, 2008, 2014; Jiménez-Reyes et al, 2014, 2016; Giroux et al, 2015, 2016), while the optimal F-v profile can be computed using previously proposed equations based on a biomechanical model (Samozino et al, 2012, 2014). For a given P max , vertical jump performance has been shown to be negatively correlated to FV imb , which supports the importance of considering this individual characteristic in addition to P max when designing training programs to improve ballistic performance (Samozino et al, 2012, 2014; Morin and Samozino, 2016).…”

Section: Introductionmentioning

confidence: 99%

Effectiveness of an Individualized Training Based on Force-Velocity Profiling during Jumping

et al. 2017

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Ballistic performances are determined by both the maximal lower limb power output (Pmax) and their individual force-velocity (F-v) mechanical profile, especially the F-v imbalance (FVimb): difference between the athlete's actual and optimal profile. An optimized training should aim to increase Pmax and/or reduce FVimb. The aim of this study was to test whether an individualized training program based on the individual F-v profile would decrease subjects' individual FVimb and in turn improve vertical jump performance. FVimb was used as the reference to assign participants to different training intervention groups. Eighty four subjects were assigned to three groups: an “optimized” group divided into velocity-deficit, force-deficit, and well-balanced sub-groups based on subjects' FVimb, a “non-optimized” group for which the training program was not specifically based on FVimb and a control group. All subjects underwent a 9-week specific resistance training program. The programs were designed to reduce FVimb for the optimized groups (with specific programs for sub-groups based on individual FVimb values), while the non-optimized group followed a classical program exactly similar for all subjects. All subjects in the three optimized training sub-groups (velocity-deficit, force-deficit, and well-balanced) increased their jumping performance (12.7 ± 5.7% ES = 0.93 ± 0.09, 14.2 ± 7.3% ES = 1.00 ± 0.17, and 7.2 ± 4.5% ES = 0.70 ± 0.36, respectively) with jump height improvement for all subjects, whereas the results were much more variable and unclear in the non-optimized group. This greater change in jump height was associated with a markedly reduced FVimb for both force-deficit (57.9 ± 34.7% decrease in FVimb) and velocity-deficit (20.1 ± 4.3%) subjects, and unclear or small changes in Pmax (−0.40 ± 8.4% and +10.5 ± 5.2%, respectively). An individualized training program specifically based on FVimb (gap between the actual and optimal F-v profiles of each individual) was more efficient at improving jumping performance (i.e., unloaded squat jump height) than a traditional resistance training common to all subjects regardless of their FVimb. Although improving both FVimb and Pmax has to be considered to improve ballistic performance, the present results showed that reducing FVimb without even increasing Pmax lead to clearly beneficial jump performance changes. Thus, FVimb could be considered as a potentially useful variable for prescribing optimal resistance training to improve ballistic performance.

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“…This method, based on macroscopic modelling of body mass displacement and the associated mechanical external work, requires only body mass, hPO and jump height. The initial reliability and concurrent validity was tested against reference force plate measurements [8], and was confirmed in subsequent studies from other authors, including additional load conditions and application to CMJ [7,46,47]. In this method, the mean power produced during a jump was computed as:…”

Section: 3mentioning

confidence: 84%

Jump height is a poor indicator of lower limb maximal power output: theoretical demonstration, experimental evidence and practical solutions

Morin¹,

Jiménez-Reyes²,

Brughelli³

et al. 2018

Preprint

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KEY POINTS1. Despite a widespread use, we contended that jump height as measured during vertical jump tests is not a good indicator of lower limb power or maximal power output capability.2. We showed this based on several confounding factors: body mass, push-off distance, individual force-velocity profile and optimal force-velocity profile. Some experimental data were also shown and discussed to further illustrate the not very-good correlation between jump height and power output.3. Finally, in order to address this issue, we discussed the possible practical solutions, and advocate for the use of a simple, accurate computation method based on jump height as an input. ABSTRACTLower limb maximal power output (Pmax) is a key physical component of performance in many sports. During squat jump (SJ) and countermovement jump (CMJ) tests, athletes produce high amounts of mechanical work over a short duration to displace their body mass (i.e. the dimension of mechanical power). Thus, jump height has been frequently used by the sports science and medicine communities as an indicator of Pmax. However, in this article, we contended that SJ and CMJ height are in fact poor indicators of Pmax in trained populations.To support our opinion, we first detailed why, theoretically, jump height and Pmax are not fully related. Specifically, we demonstrated that individual body mass, distance of push-off, optimal loading and force-velocity characteristics confound the jump height-Pmax relationship. We also discussed the poor relationship between SJ or CMJ height and Pmax measured with a force plate based on data reported in the literature, which added to our own experimental evidence. Finally, we discussed the limitations of existing practical solutions (regression-based estimation equations and allometric scaling), and advocated using a valid, reliable and simple field-based procedure to compute individual Pmax directly from jump height, body mass and push-off distance. The latter may allow researchers and practitioners to reduce bias in their assessment of Pmax by using jump height as an input with a simple yet accurate computation method, and not as the first/only variable of interest. Morin et al. Pre-Print -2018 -Jump height is a poor indicator of lower limb maximal power output3

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What is the Best Method for Assessing Lower Limb Force-Velocity Relationship?

Cited by 66 publications

References 38 publications

Two-Load Method for Distinguishing Between Muscle Force, Velocity, and Power-Producing Capacities

Two-Load Method for Distinguishing Between Muscle Force, Velocity, and Power-Producing Capacities

Effectiveness of an Individualized Training Based on Force-Velocity Profiling during Jumping

Jump height is a poor indicator of lower limb maximal power output: theoretical demonstration, experimental evidence and practical solutions

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