Differences in gait patterns across age and knee OA status using IMU data

Common in-lab, marker-based gait analyses may not represent daily, real-world gait. Real-world gait analyses are feasible using inertial measurement units (IMUs), but estimating traditional gait kinematics (e.g., joint angles) from IMU data is challenging. Recent advancements in open-source methods (e.g., OpenSense) may enable reliable and repeatable estimation of joint angles. Before using OpenSense to study real-world gait, we must determine whether these methods: (1) estimate joint kinematics similarly to traditional marker-based motion capture (MoCap) and (2) differentiate groups with clinically different gait mechanics. In this project, we compared inverse kinematics calculated using IMU- and marker-based data across young adults, healthy older adults, and older adults with knee osteoarthritis. <br/><br/>This project includes the following software/data packages: <br/> <ul> <li> <a href="https://simtk.org/frs?group_id=2279#pack_2306">kneeOA_age_IMU </a> : Sample data, code, and documentation for comparison of IMU and marker-based data. </li> </ul>

在实验室中常见的基于标记的步态分析可能无法代表日常生活中的真实步态。使用惯性测量单元（IMU）进行真实世界的步态分析是可行的，但从IMU数据中估计传统的步态运动学参数（例如，关节角度）具有挑战性。近年来，开源方法（例如，OpenSense）的进展可能使得可靠且可重复的关节角度估计成为可能。在使用OpenSense研究真实世界步态之前，我们必须确定这些方法：（1）是否与传统基于标记的运动捕捉（MoCap）在估计关节运动学方面具有相似性；（2）是否能够区分具有临床不同步态机制的人群。在本项目中，我们比较了使用IMU和基于标记的数据计算出的逆运动学，涉及年轻成年人、健康老年人以及患有膝关节骨关节炎的老年人。 <br/><br/>本项目包括以下软件/数据包： <br/> <ul> <li> <a href="https://simtk.org/frs?group_id=2279#pack_2306">kneeOA_age_IMU </a> : 用于比较IMU和基于标记数据的样本数据、代码和文档。 </li> </ul>