Yang Hyung Suk, Atkins Lee T, James C Roger
Center for Rehabilitation Research, Texas Tech University Health Sciences Center, TX, USA.
Center for Rehabilitation Research, Texas Tech University Health Sciences Center, TX, USA.
Gait Posture. 2016 Oct;50:212-216. doi: 10.1016/j.gaitpost.2016.09.010. Epub 2016 Sep 11.
The purpose of this study was to examine the nature of the intra-subject independence among strides during treadmill walking. We investigated the strength of the relationships among strides sampled in different ways from a population of observed strides. Eighteen asymptomatic subjects walked on a treadmill at 1.4±0.1m/s. Maximum angles and ranges of motion from the ankle, knee and hip joints, as well as stride duration were obtained and autocorrelation coefficients (AC) for 3 lags were calculated among 12 strides sampled consecutively (CS), in order but non-adjacently (NA), and randomly (RA). Ninety-nine percent of AC values were within Bartlett's 95% confidence interval limits and thus the strides were not considered significantly autocorrelated. The results support the hypothesis that strides obtained from an individual walking on a treadmill can be statistically independent. This supports the theoretical assumption that in some circumstances humans can be modeled as random sample generators due to inherent movement variability. The ability to assess statistically clinical intervention provides objective rigor for evaluating rehabilitation outcomes.
本研究的目的是探讨在跑步机上行走时步幅之间个体内部独立性的本质。我们研究了从观察到的步幅总体中以不同方式采样的步幅之间关系的强度。18名无症状受试者在跑步机上以1.4±0.1米/秒的速度行走。获取了踝关节、膝关节和髋关节的最大角度和运动范围以及步幅持续时间,并计算了连续采样(CS)、按顺序但不相邻(NA)和随机(RA)采样的12步之间3个滞后的自相关系数(AC)。99%的AC值在巴特利特95%置信区间范围内,因此步幅不被认为具有显著自相关性。结果支持了这样的假设,即从在跑步机上行走的个体获得的步幅在统计学上可以是独立的。这支持了理论假设,即在某些情况下,由于固有的运动变异性,人类可以被建模为随机样本生成器。评估临床干预的统计学能力为评估康复结果提供了客观的严谨性。