Department of Biomechanics, Kinesiology and Computer Science in Sport, Centre for Sport Science and University Sports, University of Vienna, Auf der Schmelz 6a (USZ II), 1150, Vienna, Austria.
Neuromechanics Research Group, Centre for Sport Science and University Sports, University of Vienna, Vienna, Austria.
Sci Rep. 2024 Jun 4;14(1):12860. doi: 10.1038/s41598-024-63640-5.
A common theory of motor control posits that movement is controlled by muscle synergies. However, the behavior of these synergies during highly complex movements remains largely unexplored. Skateboarding is a hardly researched sport that requires rapid motor control to perform tricks. The objectives of this study were to investigate three key areas: (i) whether motor complexity differs between skateboard tricks, (ii) the inter-participant variability in synergies, and (iii) whether synergies are shared between different tricks. Electromyography data from eight muscles per leg were collected from seven experienced skateboarders performing three different tricks (Ollie, Kickflip, 360°-flip). Synergies were extracted using non-negative matrix factorization. The number of synergies (NoS) was determined using two criteria based on the total variance accounted for (tVAF > 90% and adding an additional synergy does not increase tVAF > 1%). In summary: (i) NoS and tVAF did not significantly differ between tricks, indicating similar motor complexity. (ii) High inter-participant variability exists across participants, potentially caused by the low number of constraints given to perform the tricks. (iii) Shared synergies were observed in every comparison of two tricks. Furthermore, each participant exhibited at least one synergy vector, which corresponds to the fundamental 'jumping' task, that was shared through all three tricks.
一种常见的运动控制理论认为,运动是由肌肉协同作用控制的。然而,这些协同作用在高度复杂的运动中的行为仍然很大程度上未被探索。滑板是一项研究甚少的运动,需要快速的运动控制才能完成技巧。本研究的目的是调查三个关键领域:(i)滑板技巧之间的运动复杂性是否不同,(ii)协同作用的参与者间变异性,以及(iii)不同技巧之间是否存在协同作用。从七名经验丰富的滑板者的每条腿的八块肌肉中采集肌电图数据,他们执行了三种不同的技巧(Ollie、Kickflip、360°-flip)。使用非负矩阵分解提取协同作用。协同作用的数量(NoS)使用基于总方差解释(tVAF>90%和添加额外的协同作用不会增加 tVAF>1%)的两个标准来确定。总之:(i)技巧之间的 NoS 和 tVAF 没有显著差异,表明运动复杂性相似。(ii)参与者之间存在高度的参与者间变异性,这可能是由于执行技巧时给予的约束数量较少造成的。(iii)在每两个技巧的比较中都观察到共享的协同作用。此外,每个参与者都表现出至少一个协同作用向量,这对应于基本的“跳跃”任务,通过所有三个技巧都可以共享。