Department of Kinesiology and Applied Physiology, University of Delaware, Newark, DE,USA.
School of Kinesiology, University of Michigan, Ann Arbor, MI,USA.
J Appl Biomech. 2023 Apr 6;39(3):133-142. doi: 10.1123/jab.2022-0194. Print 2023 Jun 1.
In-lab, marker-based gait analyses may not represent real-world gait. Real-world gait analyses may be feasible using inertial measurement units (IMUs) in combination with open-source data processing pipelines (OpenSense). Before using OpenSense to study real-world gait, we must determine whether these methods estimate joint kinematics similarly to traditional marker-based motion capture (MoCap) and differentiate groups with clinically different gait mechanics. Healthy young and older adults and older adults with knee osteoarthritis completed this study. We captured MoCap and IMU data during overground walking at 2 speeds. MoCap and IMU kinematics were computed with OpenSim workflows. We tested whether sagittal kinematics differed between MoCap and IMU, whether tools detected between-group differences similarly, and whether kinematics differed between tools by speed. MoCap showed more anterior pelvic tilt (0%-100% stride) and joint flexion than IMU (hip: 0%-38% and 61%-100% stride; knee: 0%-38%, 58%-89%, and 95%-99% stride; and ankle: 6%-99% stride). There were no significant tool-by-group interactions. We found significant tool-by-speed interactions for all angles. While MoCap- and IMU-derived kinematics differed, the lack of tool-by-group interactions suggests consistent tracking across clinical cohorts. Results of the current study suggest that IMU-derived kinematics with OpenSense may enable reliable evaluation of gait in real-world settings.
在实验室中,基于标记的步态分析可能无法代表真实世界中的步态。使用惯性测量单元 (IMU) 结合开源数据处理管道 (OpenSense) 可能可以进行真实世界中的步态分析。在使用 OpenSense 研究真实世界中的步态之前,我们必须确定这些方法是否可以像传统基于标记的运动捕捉 (MoCap) 一样估计关节运动学,并区分具有临床不同步态力学的组。健康的年轻和老年成年人以及患有膝骨关节炎的老年人完成了这项研究。我们在两种速度下进行地面行走时捕获了 MoCap 和 IMU 数据。使用 OpenSim 工作流程计算了 MoCap 和 IMU 运动学。我们测试了 MoCap 和 IMU 之间的矢状面运动学是否存在差异,工具是否相似地检测到组间差异,以及运动学是否因速度而不同。MoCap 显示出比 IMU 更大的骨盆前倾(0%-100%步幅)和关节屈曲(髋关节:0%-38%和 61%-100%步幅;膝关节:0%-38%、58%-89%和 95%-99%步幅;踝关节:6%-99%步幅)。工具与组之间没有显著的相互作用。我们发现所有角度的工具与速度之间都存在显著的相互作用。虽然 MoCap 和 IMU 得出的运动学存在差异,但工具与组之间缺乏相互作用表明在临床队列中具有一致的跟踪效果。当前研究的结果表明,使用 OpenSense 进行 IMU 衍生的运动学分析可能能够在真实环境中可靠地评估步态。