对比两种骑行运动捕捉系统，发现无标记系统精度极高。
Comparison of Kinematics and Kinetics Between OpenCap and a Marker-Based Motion Capture System in Cycling
- 用无标记系统OpenCap与传统标记系统同步采集骑行数据。
- 髋膝踝关节角度误差极小，相关系数超0.9。
- 适合运动康复与真实场景下的人体运动分析研究者。
本研究评估了无标记（OpenCap）与基于标记的运动捕捉系统在骑行过程中关节运动学与动力学参数的吻合度。10名受试者在不同速度和阻力下骑行，两套系统同时记录运动数据。通过OpenSim计算关节角度、力矩及关节反作用力，并采用均方根误差（RMSE）、皮尔逊相关系数（r）及重复测量Bland-Altman分析控制个体内试验依赖性。结果表明，髋关节（屈伸）、膝关节（屈伸）和踝关节（背屈/跖屈）的角度具有极强一致性（r > 0.9），验证了OpenCap在骑行运动分析中的高可靠性。
原文摘要 · Abstract (English)
This study evaluates the agreement of marker-based and markerless (OpenCap) motion capture systems in assessing joint kinematics and kinetics during cycling. Markerless systems, such as OpenCap, offer the advantage of capturing natural movements without physical markers, making them more practical for real-world applications. However, the agreement of OpenCap with a marker-based system, particularly in cycling, remains underexplored. Ten participants cycled at varying speeds and resistances while motion data were recorded using both systems. Key metrics, including joint angles, moments, and joint reaction loads, were computed using OpenSim and compared using root mean squared error (RMSE) per trial across participants, Pearson correlation coefficients (r) per trial across participants and repeated measures Bland-Altman to control trials dependency within subject. Results revealed very strong agreement (r GT 0.9) for hip (flexion/extension), knee (flexion/extension), and ankle (dorsiflexion/plantarflexion) joint angles.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。