Test- retest reliability of manual digitising.

This study evaluated a purpose-trained markerless motion capture system for biomechanical analysis in elite pole vault competition. The aim was to determine whether a markerless approach could produce results comparable to manual digitising—the current standard in live competition settings—when operating under the practical constraint of a fixed four-camera setup. Data were collected from eight world-class pole vaulters during the 2024 World Athletics Indoor Championships. The final steps of the run-up through take-off were recorded at 100 Hz and analysed using both manual digitisation and the SIMI Nemo Markerless system to extract key biomechanical variables. Results showed strong overall agreement between methods for most spatial and centre of mass (CM) variables, with mean relative bias and random error of 0.3% and 3.8%, respectively. Step length differed by approximately 1 cm, and running step velocities showed root mean square error (RMSE) values between 0.02 and 0.05 m/s. CM height and horizontal velocity at pole plant showed RMSEs below 0.02 m and 0.1 m/s, respectively. At take-off, horizontal, vertical and absolute CM velocities all showed RMSE values of approximately 0.1 m/s. For these variables, intraclass correlation coefficients ranged from 0.898–1.000. Continuous waveform agreement was also strong, with Coefficient of Multiple Determination values exceeding 0.98 for vertical CM displacement, and above 0.90 for both CM velocity and most joint angle trajectories. In contrast, joint angles at take-off showed less agreement (RMSE 5°–10°), reflecting challenges in joint landmark identification in field conditions, and indicating that further refinement may be needed for complex movements. These findings suggest that, when supported by anatomically-informed pose estimation algorithms, a four-camera markerless setup is capable of capturing essential performance indicators in elite pole vault. The approach shows strong potential for scientific and applied use in real-world sport environments.

本研究针对精英撑竿跳高赛事中的生物力学分析，评估了一款经专项训练的无标记点运动捕捉系统（markerless motion capture system）。本研究旨在明确：在固定四机位拍摄的实际约束条件下，无标记点采集方法能否生成与手动数字化（当前赛事现场的标准流程）可比的分析结果。研究数据采集自2024年世界田径室内锦标赛的8名世界级撑竿跳高运动员。研究对运动员助跑最后阶段至起跳动作的过程以100赫兹帧率进行录制，并分别采用手动数字化方法与SIMI Nemo无标记点系统进行分析，以提取核心生物力学变量。结果显示，两种方法在多数空间变量与质心（CM, centre of mass）变量上整体一致性极佳，平均相对偏差与随机误差分别为0.3%与3.8%。步长差异约为1cm，助跑步速的均方根误差（RMSE, root mean square error）介于0.02~0.05 m/s之间。撑竿插点时刻的质心高度与水平速度的RMSE分别低于0.02 m与0.1 m/s。起跳时刻的质心水平、垂直与合速度的RMSE均约为0.1 m/s。上述变量的组内相关系数（intraclass correlation coefficients）介于0.898~1.000之间。连续波形一致性同样优异：质心垂直位移的多重决定系数（Coefficient of Multiple Determination）超过0.98，质心速度与多数关节角轨迹的该系数均高于0.90。与之相对，起跳时刻的关节角一致性稍差（RMSE为5°~10°），这反映了赛事实地环境下关节地标识别的难点，也说明针对复杂动作仍需进一步优化算法。上述结果表明，在基于解剖学先验的姿态估计算法加持下，四机位无标记点采集方案能够有效捕捉精英撑竿跳高项目的核心运动表现指标。该方法在真实赛事场景下的科研与应用场景中展现出巨大潜力。