Abstract：
UNASSIGNED: This study presents a comprehensive comparison between a marker-based motion capture system (MMC) and a video-based motion capture system (VMC) in the context of kinematic analysis using musculoskeletal models.
UNASSIGNED: Focusing on joint angles, the study aimed to evaluate the accuracy of VMC as a viable alternative for biomechanical research.
UNASSIGNED: Eighteen healthy subjects performed isolated movements with 17 joint degrees of freedom, and their kinematic data were collected using both an MMC and a VMC setup. The kinematic data were entered into the AnyBody Modelling System, which enables the calculation of joint angles. The mean absolute error (MAE) was calculated to quantify the deviations between the two systems.
UNASSIGNED: The results showed good agreement between VMC and MMC at several joint angles. In particular, the shoulder, hip and knee joints showed small deviations in kinematics with MAE values of 4.8∘, 6.8∘ and 3.5∘, respectively. However, the study revealed problems in tracking hand and elbow movements, resulting in higher MAE values of 13.7∘ and 27.7∘. Deviations were also higher for head and thoracic movements.
UNASSIGNED: Overall, VMC showed promising results for lower body and shoulder kinematics. However, the tracking of the wrist and pelvis still needs to be refined. The research results provide a basis for further investigations that promote the fusion of VMC and musculoskeletal models.
UNASSIGNED: Focusing on joint angles, the study aimed to evaluate the accuracy of VMC as a viable alternative for biomechanical research.
UNASSIGNED: Eighteen healthy subjects performed isolated movements with 17 joint degrees of freedom, and their kinematic data were collected using both an MMC and a VMC setup. The kinematic data were entered into the AnyBody Modelling System, which enables the calculation of joint angles. The mean absolute error (MAE) was calculated to quantify the deviations between the two systems.
UNASSIGNED: The results showed good agreement between VMC and MMC at several joint angles. In particular, the shoulder, hip and knee joints showed small deviations in kinematics with MAE values of 4.8∘, 6.8∘ and 3.5∘, respectively. However, the study revealed problems in tracking hand and elbow movements, resulting in higher MAE values of 13.7∘ and 27.7∘. Deviations were also higher for head and thoracic movements.
UNASSIGNED: Overall, VMC showed promising results for lower body and shoulder kinematics. However, the tracking of the wrist and pelvis still needs to be refined. The research results provide a basis for further investigations that promote the fusion of VMC and musculoskeletal models.
摘要：
■本研究在使用肌肉骨骼模型进行运动学分析的背景下，提出了基于标记的运动捕获系统（MMC）和基于视频的运动捕获系统（VMC）之间的全面比较。
■关注关节角度，该研究旨在评估VMC作为生物力学研究可行替代方案的准确性.
■18名健康受试者进行了17个关节自由度的孤立运动，他们的运动学数据是使用MMC和VMC设置收集的。运动学数据被输入到AnyBody建模系统中，这使得关节角度的计算。计算平均绝对误差(MAE)以量化两个系统之间的偏差。
■结果表明，在几个关节角度下，VMC和MMC之间具有良好的一致性。特别是,肩膀,髋关节和膝关节在运动学方面表现出微小的偏差，MAE值为4.8。6.8个和3.5个，分别。然而,这项研究揭示了追踪手部和肘部运动的问题，导致更高的MAE值，分别为13.7○和27.7○。头部和胸部运动的偏差也较高。
■总的来说，VMC在下半身和肩部运动学方面显示出有希望的结果。然而,手腕和骨盆的跟踪仍然需要完善。研究结果为进一步研究促进VMC和肌肉骨骼模型融合提供了基础。
■关注关节角度，该研究旨在评估VMC作为生物力学研究可行替代方案的准确性.
■18名健康受试者进行了17个关节自由度的孤立运动，他们的运动学数据是使用MMC和VMC设置收集的。运动学数据被输入到AnyBody建模系统中，这使得关节角度的计算。计算平均绝对误差(MAE)以量化两个系统之间的偏差。
■结果表明，在几个关节角度下，VMC和MMC之间具有良好的一致性。特别是,肩膀,髋关节和膝关节在运动学方面表现出微小的偏差，MAE值为4.8。6.8个和3.5个，分别。然而,这项研究揭示了追踪手部和肘部运动的问题，导致更高的MAE值，分别为13.7○和27.7○。头部和胸部运动的偏差也较高。
■总的来说，VMC在下半身和肩部运动学方面显示出有希望的结果。然而,手腕和骨盆的跟踪仍然需要完善。研究结果为进一步研究促进VMC和肌肉骨骼模型融合提供了基础。
