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通过功能数据分析,检测到在不同运动强度下进行的残奥会举重运动员的非对称速度曲线。

Asymmetric velocity profiles in Paralympic powerlifters performing at different exercise intensities are detected by functional data analysis.

机构信息

School of Physical Education, Physiotherapy and Occupational Therapy, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil; Brazilian Paralympic Reference Center, Sports Training Center, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.

Brazilian Paralympic Reference Center, Sports Training Center, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.

出版信息

J Biomech. 2021 Jun 23;123:110523. doi: 10.1016/j.jbiomech.2021.110523. Epub 2021 May 15.

Abstract

Asymmetries compromise performance in powerlifting and Paralympic powerlifting, but its quantification can be complex. Previous studies consider average or peak values to quantify asymmetries, however this approach does not consider the pattern of movement like velocity profiles. Here we demonstrate that conducting a functional analysis of variance (FANOVA) permits to quantify asymmetries in bench press performance by Paralympic powerlifting at different submaximal intensities. Kinematic data were collected from 10 Paralympic powerlifting athletes performing in bench press at submaximal intensities (50% and 90% of the one-repetition maximum). Linear velocity was quantified considering mean values and the entire waveform. Mean values were compared by analysis of variance (ANOVA) and the waveforms were compared by FANOVA. FANOVA identified asymmetry profiles that ANOVA did not recognize at the highest intensity, which is the closest to a competition. This way, FANOVA can bring advantages to the analysis of competitive performance. FANOVA data analysis identifies asymmetries at higher intensity of effort considering the whole pattern of movement. Therefore, we consider that the FANOVA's approach may benefit the biomechanical assessment of the Paralympic powerlifting.

摘要

不对称会影响力量举重和残奥会力量举重的表现,但对其进行量化可能比较复杂。以前的研究采用平均或峰值来量化不对称性,但这种方法没有考虑运动模式,如速度曲线。在这里,我们通过对不同次最大强度下的残奥会力量举重运动员进行功能方差分析 (FANOVA) 来证明,这种方法可以量化卧推表现中的不对称性。对 10 名残奥会力量举重运动员在次最大强度下(最大重复次数的 50%和 90%)进行卧推时的运动学数据进行了收集。考虑平均值和整个波形来量化线性速度。通过方差分析 (ANOVA) 比较平均值,通过 FANOVA 比较波形。FANOVA 确定了在最高强度下 ANOVA 无法识别的不对称性特征,而最高强度最接近比赛强度。因此,FANOVA 可以为竞技表现分析带来优势。FANOVA 数据分析考虑整个运动模式,在更高的运动强度下识别出不对称性。因此,我们认为 FANOVA 的方法可能有助于残奥会力量举重的生物力学评估。

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