Department of Orthopaedic Surgery, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
Division of Geriatrics, Department of Internal Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
PLoS One. 2019 Oct 1;14(10):e0222913. doi: 10.1371/journal.pone.0222913. eCollection 2019.
Inertial measurement unit (IMU)-based gait analysis can be used to quantitatively analyze the bilateral coordination and gait asymmetry (GA). The purpose of this study was to investigate changes in bilateral coordination and GA due to gait speed using an IMU based gait analysis and identify spatiotemporal factors affecting bilateral coordination and GA. Eighty healthy adults (40 men and 40 women) participated in the study. The mean age was 26.2 years, and the mean body mass index was 22.8 kg/m2. Three different walking speeds (80%, 100%, and 120% of preferred walking speed) on a treadmill were applied for 1 min of continuous level walking using a shoe-type IMU-based gait analysis system. The phase coordination index (PCI) and GA were calculated on three different walking speeds. Several variables (gait speed, height, body mass index, cadence, and step length) were analyzed as possible factors affecting the PCI and GA. Bilateral coordination and GA improved during fast walking (p = 0.005 and p = 0.019, respectively) and deteriorated during slow walking (p<0.001 and p = 0.008, respectively), compared with the participants' preferred walking speeds. The correlation analysis revealed that PCI was negatively correlated with step length at each walking condition and lower gait speed was negatively correlated with PCI and GA during slow walking. Both bilateral coordination and GA had a negative linear relationship with gait speed, showing an improvement in the fast walking condition and deterioration in the slow walking condition. Step length was the factor associated with the change in the bilateral coordination.
基于惯性测量单元（IMU）的步态分析可用于定量分析双侧协调和步态不对称性（GA）。本研究旨在通过基于 IMU 的步态分析研究由于步态速度变化引起的双侧协调和 GA 的变化，并确定影响双侧协调和 GA 的时空因素。80 名健康成年人（40 名男性和 40 名女性）参加了这项研究。平均年龄为 26.2 岁，平均体重指数为 22.8kg/m2。在跑步机上以三种不同的步行速度（80%、100%和 120%的最佳步行速度）进行 1 分钟的连续水平步行，使用鞋式基于 IMU 的步态分析系统。在三种不同的步行速度下计算相位协调指数（PCI）和 GA。分析了几个变量（步行速度、身高、体重指数、步频和步长），作为影响 PCI 和 GA 的可能因素。与参与者的最佳步行速度相比，快走时双侧协调和 GA 提高（p=0.005 和 p=0.019），慢走时则恶化（p<0.001 和 p=0.008）。相关分析显示，在每种步行条件下，PCI 与步长呈负相关，而较低的步行速度与慢走时的 PCI 和 GA 呈负相关。双侧协调和 GA 与步行速度呈负线性关系，在快速行走条件下改善，在缓慢行走条件下恶化。步长是与双侧协调变化相关的因素。
