da Silva Soares Jéssica, Carpes Felipe P, de Fátima Geraldo Gislaine, Bertú Medeiros Fabíola, Roberto Kunzler Marcos, Sosa Machado Álvaro, Augusto Paolucci Leopoldo, Gustavo Pereira de Andrade André
Biomechanics Laboratory, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil.
Applied Neuromechanics Research Group, Universidade Federal do Pampa, Uruguaiana, RS, Brazil.
J Biomech. 2021 Jun 9;122:110478. doi: 10.1016/j.jbiomech.2021.110478. Epub 2021 Apr 24.
Pedaling asymmetry is claimed as a factor of influence on injury and performance. However, the evidence is still controversial. Most previous studies determined peak torque asymmetries, which in our understanding does not consider the pattern of movement like torque profiles. Here we demonstrate that asymmetries in pedaling torque at different exercise intensities can be better described when the torque profiles are considered using functional analysis of variance than when only the peak values are analyzed. We compared peak torques and torque curves recorded while cyclists pedaled at submaximal intensities of 60%, 80%, and 95% of the maximal power output and compared data between the preferred and non-preferred legs. ANOVA showed symmetry or rather no difference in the amount of peak torque between legs, regardless of pedaling intensity. FANOVA, on the other hand, revealed significant asymmetries between legs, regardless of cycling intensity, apparently for different sections of the cycle, however, not for peak torque, either. We conclude that pedaling asymmetry cannot be quantified solely by peak torques and considering the analysis of the entire movement cycle can more accurately reflect the biomechanical movement pattern. Therefore, FANOVA data analysis could be an alternative to identify asymmetries. A novel approach as described here might be useful when combining kinetics assessment with other approaches like EMG and kinematics and help to better understand the role of pedaling asymmetries for performance and injury risks.
蹬踏不对称被认为是影响损伤和运动表现的一个因素。然而,证据仍存在争议。以前的大多数研究确定了峰值扭矩不对称性,而在我们看来,这并未考虑诸如扭矩曲线等运动模式。在此我们证明,与仅分析峰值相比,当使用方差功能分析来考虑扭矩曲线时,不同运动强度下的蹬踏扭矩不对称性能够得到更好的描述。我们比较了自行车运动员在最大功率输出的60%、80%和95%的次最大强度下蹬踏时记录的峰值扭矩和扭矩曲线,并比较了优势腿和非优势腿之间的数据。方差分析表明,无论蹬踏强度如何,双腿之间的峰值扭矩量呈对称或无差异。另一方面,功能方差分析显示,无论骑行强度如何,双腿之间在不同的骑行阶段存在显著不对称性,然而,峰值扭矩方面并非如此。我们得出结论,蹬踏不对称不能仅通过峰值扭矩来量化,考虑整个运动周期的分析能够更准确地反映生物力学运动模式。因此,功能方差分析数据分析可作为识别不对称性的一种替代方法。当将动力学评估与肌电图和运动学等其他方法相结合时,此处描述的新方法可能会很有用,并有助于更好地理解蹬踏不对称对运动表现和损伤风险的作用。