Yang Feng, Pai Yi-Chung
Department of Kinesiology, University of Texas at El Paso, El Paso, TX 79968, USA.
Department of Physical Therapy, University of Illinois at Chicago, 1919 West Taylor St., Room 426 (M/C 898) Chicago, IL 60612, USA.
J Biomech. 2014 Dec 18;47(16):3876-81. doi: 10.1016/j.jbiomech.2014.10.006. Epub 2014 Oct 14.
The primary purpose of this study was to systematically evaluate and compare the predictive power of falls for a battery of stability indices, obtained during normal walking among community-dwelling older adults. One hundred and eighty seven community-dwelling older adults participated in the study. After walking regularly for 20 strides on a walkway, participants were subjected to an unannounced slip during gait under the protection of a safety harness. Full body kinematics and kinetics were monitored during walking using a motion capture system synchronized with force plates. Stability variables, including feasible-stability-region measurement, margin of stability, the maximum Floquet multiplier, the Lyapunov exponents (short- and long-term), and the variability of gait parameters (including the step length, step width, and step time), were calculated for each subject. Sensitivity of predicting slip outcome (fall vs. recovery) was examined for each stability variable using logistic regression. Results showed that the feasible-stability-region measurement predicted fall incidence among these subjects with the highest sensitivity (68.4%). Except for the step width (with an sensitivity of 60.2%), no other stability variables could differentiate fallers from those who did not fall for the sample included in this study. The findings from the present study could provide guidance to identify individuals at increased risk of falling using the feasible-stability-region measurement or variability of the step width.
本研究的主要目的是系统评估和比较在社区居住的老年人正常行走过程中获得的一系列稳定性指标对跌倒的预测能力。187名社区居住的老年人参与了该研究。在人行道上正常行走20步后,参与者在安全带保护下的步态中遭遇一次突然滑倒。使用与测力板同步的运动捕捉系统监测行走过程中的全身运动学和动力学。为每个受试者计算稳定性变量,包括可行稳定区域测量、稳定裕度、最大弗洛凯乘数、李雅普诺夫指数(短期和长期)以及步态参数的变异性(包括步长、步宽和步时)。使用逻辑回归分析每个稳定性变量对滑倒结果(跌倒与恢复)的预测敏感性。结果表明,可行稳定区域测量对这些受试者跌倒发生率的预测敏感性最高(68.4%)。除步宽(敏感性为60.2%)外,本研究纳入的样本中,没有其他稳定性变量能够区分跌倒者和未跌倒者。本研究结果可为使用可行稳定区域测量或步宽变异性来识别跌倒风险增加的个体提供指导。