This paper illustrates how multilevel functional models can detect and characterize biomechanical changes along different sport training sessions. Our analysis focuses on the relevant cases to identify differences in knee biomechanics in recreational runners during low and high-intensity exercise sessions with the same energy expenditure by recording $20$ steps. To do so, we review the existing literature of multilevel models, and then, we propose a new hypothesis test to look at the changes between different levels of the multilevel model as low and high-intensity training sessions. We also evaluate the reliability of measures recorded in three-dimension knee angles from the functional intra-class correlation coefficient (ICC) obtained from the decomposition performed with the multilevel funcional model taking into account $20$ measures recorded in each test. The results show that there are no statistically significant differences between the two modes of exercise. However, we have to be careful with the conclusions since, as we have shown, human gait-patterns are very individual and heterogeneous between groups of athletes, and other alternatives to the p-value may be more appropriate to detect statistical differences in biomechanical changes in this context.
翻译:本文说明了多层次功能模型如何在不同的体育培训班中发现和描述生物机能变化。我们的分析侧重于相关案例,通过记录20美元的步骤,找出低强度和高强度运动课期间娱乐跑步者膝部生物机能的差异,同时以同样的能源支出来记录20美元。为此,我们审查了多层次模式的现有文献,然后提出了一个新的假设测试,将多层次模式不同层次之间的变化看成低强度和高强度培训课。我们还评估了从与多层次滑动模型的分解中获得的三层膝部内相关系数(ICC)所记录的措施的可靠性。结果显示,这两种模式之间在统计上没有重大差异。然而,我们必须谨慎对待这些结论,因为正如我们所显示的那样,人类运动模式在运动员群体之间非常个别,而且差异很大,因此其他替代方法可能更适合于检测生物机能变化中的统计差异。