Assessing single camera markerless motion capture with OpenSim inverse kinematics during upper limb activities of daily living

This study evaluates the accuracy of single camera markerless motion capture (SCMoCap) using Microsoft’s Azure Kinect, enhanced with inverse kinematics (IK) via OpenSim, for upper limb movement analysis. Twelve healthy adults performed ten upper-limb tasks, recorded simultaneously by OptiTrack (marker-based) and Azure Kinect (markerless) from frontal and sagittal views. Joint angles were calculated using two methods: (1) direct kinematics based on body coordinate frames and (2) inverse kinematics using OpenSim’s IK tool with anatomical keypoints. Accuracy was evaluated using root mean square error (RMSE) and Bland-Altman analysis. Results indicated that the IK method slightly improved joint angle agreement with OptiTrack for simpler movements, with an average RMSE of 8° for shoulder elevation in the sagittal plane compared to 9° with the coordinate frame method. However, both methods had higher RMSEs for rotational measurements, with IK and coordinate frame methods at 21° for shoulder rotation in the sagittal plane. Forearm pronation-supination measurements were unreliable due to tracking limitations. These findings suggest that Kinect with IK improves accuracy for simpler movements but struggles with rotational joint mechanics. Future research should focus on enhancing markerless tracking algorithms to fully realise the benefits of IK.

本研究评估了基于微软Azure Kinect的单相机无标记运动捕捉（single camera markerless motion capture，SCMoCap）的精度，该系统通过OpenSim实现逆运动学（inverse kinematics，IK）增强，用于上肢运动分析。招募12名健康成年受试者完成10项上肢任务，同时采用基于标记的OptiTrack系统与无标记的Azure Kinect系统分别从额状面与矢状面进行同步数据采集。本研究采用两种方法计算关节角度：其一为基于身体坐标系的直接运动学法，其二为结合解剖学关键点、通过OpenSim的IK工具实现的逆运动学法。采用均方根误差（root mean square error，RMSE）与布兰德-奥特曼分析对两种方法的测量精度进行评估。结果显示，针对较简单的运动，IK方法可小幅提升与OptiTrack系统的关节角度一致性；在矢状面肩抬升任务中，IK方法的平均RMSE为8°，而坐标系方法的平均RMSE为9°。但两种方法在旋转维度的测量中均表现出更高的RMSE：在矢状面肩旋转任务中，IK方法与坐标系方法的RMSE均为21°。前臂旋前-旋后测量因追踪硬件限制，可靠性较差。上述结果表明，搭载IK模块的Azure Kinect系统可提升简单运动的测量精度，但在旋转关节力学分析方面表现欠佳。未来研究应聚焦于优化无标记追踪算法，以充分发挥IK技术的应用价值。