Faculty of Kinesiology, Human Performance Laboratory, University of Calgary, Calgary, Alberta, Canada.
PLoS One. 2018 Apr 18;13(4):e0195125. doi: 10.1371/journal.pone.0195125. eCollection 2018.
To wavelet transform the electromyograms of the vastii muscles and generate wavelet intensity patterns (WIP) of runners. Test the hypotheses: 1) The WIP of the vastus medialis (VM) and vastus lateralis (VL) of one step are more similar than the WIPs of these two muscles, offset by one step. 2) The WIPs within one muscle differ by having maximal intensities in specific frequency bands and these intensities are not always occurring at the same time after heel strike. 3) The WIPs that were recorded form one muscle for all steps while running can be grouped into clusters with similar WIPs. It is expected that clusters might have distinctly different, cluster specific mean WIPs.
The EMG of the vastii muscles from at least 1000 steps from twelve runners were recorded using a bipolar current amplifier and yielded WIPs. Based on the weights obtained after a principal component analysis the dissimilarities (1-correlation) between the WIPs were computed. The dissimilarities were submitted to a hierarchical cluster analysis to search for groups of steps with similar WIPs. The clusters formed by random surrogate WIPs were used to determine whether the groups were likely to be created in a non-random manner.
The steps were grouped in clusters showing similar WIPs. The grouping was based on the frequency bands and their timing showing that they represented defining parts of the WIPs. The correlations between the WIPs of the vastii muscles that were recorded during the same step were higher than the correlations of WPIs that were recorded during consecutive steps, indicating the non-randomness of the WIPs.
The spectral power of EMGs while running varies during the stance phase in time and frequency, therefore a time averaged power spectrum cannot reflect the timing of events that occur while running. It seems likely that there might be a set of predefined patterns that are used upon demand to stabilize the movement.
对股四头肌的肌电图进行小波变换,生成跑步者的小波强度模式(WIP)。检验以下假设:1)一步中股直肌(VM)和股外侧肌(VL)的 WIP 比这两块肌肉的 WIP 偏移一步更相似。2)一块肌肉内的 WIP 在特定频段具有最大强度,这些强度并不总是在脚跟触地后同时出现。3)在跑步时,从一个肌肉记录的 WIP 可以分为具有相似 WIP 的簇。预计集群可能具有明显不同的、集群特定的平均 WIP。
使用双极电流放大器从 12 名跑步者的至少 1000 步中记录股四头肌的 EMG,并产生 WIP。基于主成分分析后获得的权重,计算 WIP 之间的相似度(1-相关性)。将相似度提交给层次聚类分析,以搜索具有相似 WIP 的步骤组。使用随机替代 WIP 形成的聚类来确定这些组是否可能以非随机方式形成。
步骤被分为具有相似 WIP 的聚类。分组基于频率带及其时间,表明它们代表了 WIP 的定义部分。同一步记录的股四头肌 WIP 之间的相关性高于连续步记录的 WIP 之间的相关性,表明 WIP 的非随机性。
在站立阶段,跑步时的肌电图频谱功率在时间和频率上发生变化,因此时间平均功率谱不能反映跑步时发生的事件的时间。似乎有可能存在一组预定义的模式,可根据需要用于稳定运动。