Rivière Jean Romain, Morin Jean-Benoît, Bowen Maximilien, Cross Matt R, Messonnier Laurent A, Samozino Pierre
Laboratoire Interuniversitaire de Biologie de La Motricité, Univ Savoie Mont Blanc, EA 7424, 73000, Chambéry, France.
Laboratoire Interuniversitaire de Biologie de La Motricité, Université Jean Monnet Saint-Etienne, Lyon 1, Université Savoie Mont Blanc, 42023, Saint-Etienne, France.
Sports Med Open. 2023 Jul 13;9(1):55. doi: 10.1186/s40798-023-00598-0.
To compare linear and curvilinear models describing the force-velocity relationship obtained in lower-limb acyclic extensions, considering experimental data on an unprecedented range of velocity conditions.
Nine athletes performed lower-limb extensions on a leg-press ergometer, designed to provide a very broad range of force and velocity conditions. Previously inaccessible low inertial and resistive conditions were achieved by performing extensions horizontally and with assistance. Force and velocity were continuously measured over the push-off in six resistive conditions to assess individual force-velocity relationships. Goodness of fit of linear and curvilinear models (second-order polynomial function, Fenn and Marsh's, and Hill's equations) on force and velocity data were compared via the Akaike Information Criterion.
Expressed relative to the theoretical maximal force and velocity obtained from the linear model, force and velocity data ranged from 26.6 ± 6.6 to 96.0 ± 3.6% (16-99%) and from 8.3 ± 1.9 to 76.6 ± 7.0% (5-86%), respectively. Curvilinear and linear models showed very high fit (adjusted r = 0.951-0.999; SEE = 17-159N). Despite curvilinear models better fitting the data, there was a ~ 99-100% chance the linear model best described the data.
A combination between goodness of fit, degrees of freedom and common sense (e.g., rational physiologically values) indicated linear modelling is preferable for describing the force-velocity relationship during acyclic lower-limb extensions, compared to curvilinear models. Notably, linearity appears maintained in conditions approaching theoretical maximal velocity. Using horizontal and assisted lower-limb extension to more broadly explore resistive/assistive conditions could improve reliability and accuracy of the force-velocity relationship and associated parameters.
考虑前所未有的速度条件下的实验数据,比较描述下肢非周期性伸展中力-速度关系的线性和曲线模型。
九名运动员在腿部推举测力计上进行下肢伸展,该测力计旨在提供非常广泛的力和速度条件。通过水平伸展并借助外力实现了以前无法达到的低惯性和阻力条件。在六种阻力条件下,在蹬离过程中连续测量力和速度,以评估个体的力-速度关系。通过赤池信息准则比较线性和曲线模型(二阶多项式函数、芬恩和马什方程以及希尔方程)对力和速度数据的拟合优度。
相对于从线性模型获得的理论最大力和速度,力和速度数据分别为26.6±6.6至96.0±3.6%(16 - 99%)和8.3±1.9至76.6±7.0%(5 - 86%)。曲线模型和线性模型显示出非常高的拟合度(调整后r = 0.951 - 0.999;标准误 = 17 - 159N)。尽管曲线模型对数据的拟合更好,但线性模型最能描述数据的可能性约为99 - 100%。
拟合优度、自由度和常识(例如合理的生理值)之间的结合表明,与曲线模型相比,线性建模更适合描述非周期性下肢伸展过程中的力-速度关系。值得注意的是,在接近理论最大速度的条件下,线性关系似乎得以维持。使用水平和辅助下肢伸展来更广泛地探索阻力/辅助条件可以提高力-速度关系及相关参数的可靠性和准确性。