Li Xiaotong, Santago Anthony C, Vidt Meghan E, Saul Katherine R
Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, USA.
Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, USA; Wake Forest School of Medicine, Winston-Salem, NC 27012, USA.
J Biomech. 2016 Sep 6;49(13):2806-2816. doi: 10.1016/j.jbiomech.2016.06.018. Epub 2016 Jun 23.
Continuous time-series data are frequently distilled into single values and analyzed using discrete statistical methods, underutilizing large datasets. Statistical parametric mapping (SPM) allows hypotheses over the entire spectrum, but consistency with discrete analyses of kinematic data is unclear. We applied SPM to evaluate effect of load and postural demands during reaching on thoracohumeral kinematics in older and young adults, and examined consistency between one-dimensional SPM and discrete analyses of the same dataset. We hypothesized that older adults would choose postures that bring the humerus anterior to the frontal plane (towards flexion) even for low demand tasks, and that SPM would reveal differences persisting over larger temporal portions of the reach. Ten healthy older (72.4±3.1yrs) and 16 young (22.9±2.5yrs) adults reached upward and forward with high and low loads. SPM and discrete t-tests were used to analyze group effects for elevation plane, elevation, and axial rotation joint angles and velocity. Older adults used more positive (anterior) elevation plane and less elevated postures to initiate and terminate reaching (p<0.008), with long duration differences during termination. When reaching upward, differences in elevation persisted over longer temporal periods at midreach for high loads (32-58% of reach) compared to low load (41-45%). SPM and discrete analyses were consistent, but SPM permitted clear identification of temporal periods over which differences persisted, while discrete methods allowed analysis of extracted values, like ROM. This work highlights the utility of SPM to analyze kinematics time series data, and emphasizes importance of task selection when assessing age-related changes in movement.
连续时间序列数据经常被提炼为单一值，并使用离散统计方法进行分析，从而未充分利用大型数据集。统计参数映射（SPM）允许对整个频谱进行假设，但与运动学数据的离散分析的一致性尚不清楚。我们应用SPM来评估老年人和年轻人在伸手够物过程中负荷和姿势需求对胸肱运动学的影响，并检验一维SPM与同一数据集离散分析之间的一致性。我们假设，即使对于低需求任务，老年人也会选择使肱骨位于额平面之前（趋于屈曲）的姿势，并且SPM将揭示在伸手够物的较大时间部分中持续存在的差异。10名健康老年人（72.4±3.1岁）和16名年轻人（22.9±2.5岁）在高负荷和低负荷情况下向上和向前伸手够物。使用SPM和离散t检验来分析在仰角平面、仰角和轴向旋转关节角度及速度方面的组间效应。老年人在开始和结束伸手够物时使用更正向（向前）的仰角平面和更低的姿势（p<0.008），在结束时有较长的持续时间差异。当向上伸手够物时，与低负荷（41-45%的伸手够物过程）相比，高负荷（32-58%的伸手够物过程）在伸手够物中间阶段仰角的差异在更长的时间内持续存在。SPM和离散分析结果一致，但SPM能清晰识别差异持续存在的时间段，而离散方法则允许对提取的值（如ROM）进行分析。这项工作突出了SPM在分析运动学时间序列数据方面的实用性，并强调了在评估与年龄相关的运动变化时任务选择的重要性。
