Department of Physical Therapy, University of Delaware, Newark, DE 19713, USA.
Department of Kinesiology & Health Education, University of Texas, Austin, TX 78712, USA.
Gait Posture. 2014 Jul;40(3):457-63. doi: 10.1016/j.gaitpost.2014.05.014. Epub 2014 Jun 4.
Falls and fall-related injuries cause extremely costly and potentially fatal health problems in people post-stroke. However, there is no global indicator of walking instability for detecting which individuals will have increased risk of falls. The purposes of this study were to directly quantify walking stability in stroke survivors and neurologically intact controls and to determine which stability measures would reveal the changes in walking stability following stroke. This study thus provided an initial step to establish objective measures for identifying potential fallers. Nine post-stroke individuals and nine controls walked on a treadmill at four different speeds. We computed short-term local divergence exponent (LDE) and maximum Floquet multiplier (maxFM) of the trunk motion, average and variability of dynamic margins of stability (MOS) and step spatiotemporal measures. Post-stroke individuals demonstrated larger short-term LDE (p = 0.002) and maxFM (p = 0.041) in the mediolateral (ML) direction compared to the controls but remained orbitally stable (maxFM < 1). In addition, post-stroke individuals walked with greater average step width (p = 0.003) but similar average ML MOS (p = 0.154) compared to the controls. Post-stroke individuals also exhibited greater variability in all MOS and step measures (all p < 0.005). Our findings indicate that post-stroke individuals walked with greater local and orbital instability and gait variability than neurologically intact controls. The results suggest that short-term LDE of ML trunk motion and the variability of MOS and step spatiotemporal measures detect the changes in walking stability associated with stroke. These stability measures may have the potential for identifying those post-stroke individuals at increased risk of falls.
中风后,跌倒及相关伤害会导致极其昂贵且潜在致命的健康问题。然而,目前尚无全球指标可以用于检测哪些个体的步行不稳定风险增加。本研究的目的是直接量化中风幸存者和神经正常对照者的步行稳定性,并确定哪些稳定性测量指标可揭示中风后步行稳定性的变化。因此,本研究为确定潜在跌倒者提供了初步的客观测量指标。9 名中风后患者和 9 名对照者在跑步机上以 4 种不同速度行走。我们计算了躯干运动的短期局部散度指数(LDE)和最大 Floquet 乘数(maxFM)、平均和动态稳定性边界(MOS)的变异性以及步幅时空测量指标。与对照组相比,中风后患者在横向(ML)方向上表现出更大的短期 LDE(p = 0.002)和 maxFM(p = 0.041),但仍保持轨道稳定(maxFM < 1)。此外,与对照组相比,中风后患者的平均步宽更大(p = 0.003),但平均 ML MOS 相似(p = 0.154)。中风后患者在所有 MOS 和步幅测量指标上的变异性也更大(所有 p < 0.005)。本研究结果表明,中风后患者的局部和轨道不稳定性以及步态变异性大于神经正常对照者。这些结果表明,ML 躯干运动的短期 LDE 和 MOS 以及步幅时空测量指标的变异性可检测与中风相关的步行稳定性变化。这些稳定性测量指标可能有潜力识别那些中风后跌倒风险增加的患者。