Arts et Métiers-Institut de Biomécanique Humaine Georges Charpak, 75013 Paris, France.
Université Côte d'Azur, CHU, France.
Sensors (Basel). 2024 Nov 5;24(22):7105. doi: 10.3390/s24227105.
Gait analysis is essential for evaluating walking patterns and identifying functional limitations. Traditional marker-based motion capture tools are costly, time-consuming, and require skilled operators. This study evaluated a 3D Marker-less Motion Capture (3D MMC) system using pose and depth estimations with the gold-standard Motion Capture (MOCAP) system for measuring hip and knee joint angles during gait at three speeds (0.7, 1.0, 1.3 m/s). Fifteen healthy participants performed gait tasks which were captured by both systems. The 3D MMC system demonstrated good accuracy (LCC > 0.96) and excellent inter-session reliability (RMSE < 3°). However, moderate-to-high accuracy with constant biases was observed during specific gait events, due to differences in sample rates and kinematic methods. Limitations include the use of only healthy participants and limited key points in the pose estimation model. The 3D MMC system shows potential as a reliable tool for gait analysis, offering enhanced usability for clinical and research applications.
步态分析对于评估行走模式和识别功能限制至关重要。传统的基于标记的运动捕捉工具成本高、耗时且需要熟练的操作人员。本研究评估了一种 3D 无标记运动捕捉（3D MMC）系统，该系统使用姿势和深度估计值与运动捕捉（MOCAP）金标准系统结合，以测量三种速度（0.7、1.0、1.3 m/s）下行走时髋关节和膝关节角度。15 名健康参与者完成了步态任务，这些任务由两个系统捕捉。3D MMC 系统表现出良好的准确性（LCC > 0.96）和出色的会话间可靠性（RMSE < 3°）。然而，在特定的步态事件中，由于采样率和运动学方法的差异，观察到中等至高的准确性和恒定偏差。限制包括仅使用健康参与者和姿势估计模型中的有限关键点。3D MMC 系统作为一种可靠的步态分析工具具有潜力，为临床和研究应用提供了增强的可用性。
