Biomechanical biofeedback may enhance rehabilitation and provide clinicians with more objective task evaluation. These feedbacks often rely on expensive motion capture systems, which restricts their widespread use, leading to the development of computer vision-based methods. These methods are subject to large joint angle errors, considering the upper limb, and exclude the scapula and clavicle motion in the analysis. Our open-source approach offers a user-friendly solution for high-fidelity upper-limb kinematics using a single low-cost RGBD camera and includes semi-automatic skin marker labeling. Real-time biomechanical analysis, ranging from kinematics to muscle force estimation, was conducted on eight participants performing a hand-cycling motion to demonstrate the applicability of our approach on the upper limb. Markers were recorded by the RGBD camera and an optoelectronic camera system, considered as a reference. Muscle activity and external load were recorded using eight EMG and instrumented hand pedals, respectively. Bland-Altman analysis revealed significant agreements in the 3D markers' positions between the two motion capture methods, with errors averaging 3.3$\pm$3.9 mm. For the biomechanical analysis, the level of agreement was sensitive to whether the same marker set was used. For example, joint angle differences averaging 2.3$\pm$2.8{\deg} when using the same marker set, compared to 4.5$\pm$2.9{\deg} otherwise. Biofeedback from the RGBD camera was provided at 63 Hz. Our study introduces a novel method for using an RGBD camera as a low-cost motion capture solution, emphasizing its potential for accurate kinematic reconstruction and comprehensive upper-limb biomechanical studies.

翻译：生物力学生物反馈可增强康复效果，并为临床医生提供更客观的任务评估。此类反馈通常依赖昂贵的动作捕捉系统，限制了其广泛应用，从而催生了基于计算机视觉的方法。针对上肢，现有方法存在较大的关节角度误差，且在分析中排除了肩胛骨与锁骨的运动。我们的开源方法利用单台低成本RGBD相机，提供了一种用户友好的高保真上肢运动学解决方案，并包含半自动皮肤标记点标注。为验证该方法在上肢应用的可行性，我们对八名参与者执行手部骑行运动进行了从运动学到肌力估计的实时生物力学分析。标记点同时由RGBD相机和作为参考的光电相机系统记录。肌肉活动与外部负荷分别通过八个肌电传感器和仪器化手踏板进行记录。Bland-Altman分析显示两种动作捕捉方法在三维标记点位置上具有显著一致性，平均误差为3.3$\pm$3.9毫米。在生物力学分析中，一致性水平对是否使用相同标记点集较为敏感：使用相同标记点集时关节角度平均差异为2.3$\pm$2.8{\deg}，否则为4.5$\pm$2.9{\deg}。RGBD相机提供的生物反馈频率为63赫兹。本研究提出了一种将RGBD相机作为低成本动作捕捉解决方案的新方法，凸显了其在精确运动学重建和全面上肢生物力学研究中的潜力。