Watari Ricky, Osis Sean T, Phinyomark Angkoon, Ferber Reed
Faculty of Kinesiology, University of Calgary, Calgary, Alberta, Canada.
Coordination for the Improvement of Higher Education Personnel (CAPES), Brasilia, Brazil.
BMC Musculoskelet Disord. 2018 Apr 19;19(1):120. doi: 10.1186/s12891-018-2045-3.
Previous studies have suggested that distinct and homogenous sub-groups of gait patterns exist among runners with patellofemoral pain (PFP), based on gait analysis. However, acquisition of 3D kinematic data using optical systems is time consuming and prone to marker placement errors. In contrast, axial segment acceleration data can represent an overall running pattern, being easy to acquire and not influenced by marker placement error. Therefore, the purpose of this study was to determine if pelvic acceleration patterns during running could be used to classify PFP patients into homogeneous sub-groups. A secondary purpose was to analyze lower limb kinematic data to investigate the practical implications of clustering these subjects based on 3D pelvic acceleration data.
A hierarchical cluster analysis was used to determine sub-groups of similar running profiles among 110 PFP subjects, separately for males (n = 44) and females (n = 66), using pelvic acceleration data (reduced with principal component analysis) during treadmill running acquired with optical motion capture system. In a secondary analysis, peak joint angles were compared between clusters (α = 0.05) to provide clinical context and deeper understanding of variables that separated clusters.
The results reveal two distinct running gait sub-groups (C1 and C2) for female subjects and no sub-groups were identified for males. Two pelvic acceleration components were different between clusters (PC1 and PC5; p < 0.001). While females in C1 presented similar acceleration patterns to males, C2 presented greater vertical and anterior peak accelerations. All females presented higher and delayed mediolateral acceleration peaks than males. Males presented greater ankle eversion (p < 0.001), lower knee abduction (p = 0.007) and hip adduction (p = 0.002) than all females, and lower hip internal rotation than C1 (p = 0.007).
Two distinct and homogeneous kinematic PFP sub-groups were identified for female subjects, but not for males. The results suggest that differences in running gait patterns between clusters occur mainly due to sex-related factors, but there are subtle differences among female subjects. This study shows the potential use of pelvic acceleration patterns, which can be acquired with accessible wearable technology (i.e. accelerometers).
先前的研究表明，基于步态分析，髌股疼痛（PFP）跑步者中存在不同且同质的步态模式亚组。然而，使用光学系统获取三维运动学数据既耗时又容易出现标记放置错误。相比之下，轴向节段加速度数据可以代表整体跑步模式，易于获取且不受标记放置错误的影响。因此，本研究的目的是确定跑步过程中的骨盆加速度模式是否可用于将PFP患者分类为同质亚组。第二个目的是分析下肢运动学数据，以研究基于三维骨盆加速度数据对这些受试者进行聚类的实际意义。
使用层次聚类分析，分别对110名PFP受试者中的男性（n = 44）和女性（n = 66），利用光学运动捕捉系统在跑步机跑步过程中获取的骨盆加速度数据（经主成分分析降维），确定相似跑步轮廓的亚组。在二次分析中，比较各聚类之间的峰值关节角度（α = 0.05），以提供临床背景并更深入地理解区分聚类的变量。
结果显示女性受试者有两种不同的跑步步态亚组（C1和C2），男性未识别出亚组。各聚类之间有两个骨盆加速度成分不同（PC1和PC5；p < 0.001）。虽然C1中的女性表现出与男性相似的加速度模式，但C2表现出更大的垂直和前向峰值加速度。所有女性的内外侧加速度峰值均高于男性且延迟出现。男性的踝外翻角度大于所有女性（p < 0.001），膝关节外展角度小于所有女性（p = 0.007），髋关节内收角度小于所有女性（p = 0.002），髋关节内旋角度小于C1组（p = 0.007）。
确定了女性受试者有两种不同且同质的运动学PFP亚组，男性则没有。结果表明，聚类之间跑步步态模式的差异主要源于性别相关因素，但女性受试者之间存在细微差异。本研究显示了骨盆加速度模式的潜在用途，其可通过可获取的可穿戴技术（即加速度计）获得。
