Hsiao HaoYuan, Zabielski Thomas M, Palmer Jacqueline A, Higginson Jill S, Binder-Macleod Stuart A
Biomechanics and Movement Science Program, University of Delaware, DE 19716, United States.
Department of Kinesiology and Applied Physiology, University of Delaware, DE 19716, United States.
J Biomech. 2016 Dec 8;49(16):4107-4112. doi: 10.1016/j.jbiomech.2016.10.003. Epub 2016 Oct 8.
Recent rehabilitation approaches for individuals poststroke have focused on improving walking speed because it is a reliable measurement that is associated with quality of life. Previous studies have demonstrated that propulsion, the force used to propel the body forward, determines walking speed. However, there are several different ways of measuring propulsion and no studies have identified which measurement best reflects differences in walking speed. The primary purposes of this study were to determine for individuals poststroke, which measurement of propulsion (1) is most closely related to their self-selected walking speeds and (2) best reflects changes in walking speed within a session. Participants (N=43) with chronic poststroke hemiparesis walked at their self-selected and maximal walking speeds on a treadmill. Propulsive impulse, peak propulsive force, and mean propulsive value (propulsive impulse divided by duration) were analyzed. In addition, each participant׳s cadence was calculated. Pearson correlation coefficients were used to determine the relationships between different measurements of propulsion versus walking speed as well as changes in propulsion versus changes in walking speed. Stepwise linear regression was used to determine which measurement of propulsion best predicted walking speed and changes in walking speed. The results showed that all 3 measurements of propulsion were correlated to walking speed, with peak propulsive force showed the strongest correlation. Similarly, when participants increased their walking speeds, changes in peak propulsive forces showed the strongest correlation to changes in walking speed. In addition, multiplying each measurement by cadence improved the correlations. The present study suggests that measuring peak propulsive force and cadence may be most appropriate of the variables studied to characterize propulsion in individuals poststroke.
近期针对中风后个体的康复方法聚焦于提高步行速度，因为它是一项与生活质量相关的可靠指标。先前的研究表明，推进力，即用于推动身体向前的力量，决定步行速度。然而，测量推进力有几种不同的方法，且尚无研究确定哪种测量方法最能反映步行速度的差异。本研究的主要目的是为中风后个体确定，哪种推进力测量方法（1）与他们自我选择的步行速度最密切相关，以及（2）最能反映一次训练中步行速度的变化。患有慢性中风后偏瘫的参与者（N = 43）在跑步机上以自我选择的速度和最大步行速度行走。分析了推进冲量、峰值推进力和平均推进值（推进冲量除以持续时间）。此外，计算了每位参与者的步频。使用皮尔逊相关系数来确定推进力的不同测量值与步行速度之间的关系，以及推进力的变化与步行速度的变化之间的关系。采用逐步线性回归来确定哪种推进力测量方法最能预测步行速度和步行速度的变化。结果表明，推进力的所有三种测量值均与步行速度相关，其中峰值推进力的相关性最强。同样，当参与者提高步行速度时，峰值推进力的变化与步行速度的变化相关性最强。此外，将每个测量值乘以步频可提高相关性。本研究表明，测量峰值推进力和步频可能是在所研究的变量中最适合用于表征中风后个体推进力的方法。
