不同摄像头视角对步态分析精度影响显著，侧视更准，正视更优对称性。
Selecting Optimal Camera Views for Gait Analysis: A Multi-Metric Assessment of 2D Projections
- 对比侧视与正视摄像头，用四个指标评估2D步态分析效果。
- 侧视在步长和膝旋转上误差更小，正视在躯干对称性上表现更好。
- 研究为临床步态分析提供摄像头部署依据，适合疾病导向场景。
目的：系统量化摄像头视角（正面或侧面）对无标记2D步态分析精度的影响，相对于3D运动捕捉真值。方法：18名受试者同时使用正面、侧面及3D运动捕捉系统采集步态数据，采用YOLOv8进行姿态估计。评估四个指标：动态时间规整（DTW）用于时间对齐，最大互相关（MCC）衡量信号相似性，Kullback-Leibler散度（KLD）检测分布差异，信息熵（IE）反映复杂度。使用威尔科克森符号秩检验（p < 0.05）和Cliff's delta（δ）评估统计差异与效应量。结果：侧视在矢状面运动学上显著优于正视：步长（DTW: 53.08±24.50 vs. 69.87±25.36, p=0.005），膝旋转（DTW: 106.46±38.57 vs. 155.41±41.77, p=0.004）。正视在对称性参数上更优：躯干旋转（KLD: 0.09±0.06 vs. 0.30±0.19, p<0.001），腕至髋中距离（MCC: 105.77±29.72 vs. 75.20±20.38, p=0.003）。效应量为中等到大（δ: 0.34–0.76）。结论：摄像头视角显著影响步态参数精度，侧视适合矢状面分析，正视适用于对称性评估。意义：首次系统证据支持2D步态分析中数据驱动的摄像头布局，提升临床实用性。未来应根据疾病特点结合双视角部署。
原文摘要 · Abstract (English)
Objective: To systematically quantify the effect of the camera view (frontal vs. lateral) on the accuracy of 2D markerless gait analysis relative to 3D motion capture ground truth. Methods: Gait data from 18 subjects were recorded simultaneously using frontal, lateral and 3D motion capture systems. Pose estimation used YOLOv8. Four metrics were assessed to evaluate agreement: Dynamic Time Warping (DTW) for temporal alignment, Maximum Cross-Correlation (MCC) for signal similarity, Kullback-Leibler Divergence (KLD) for distribution differences, and Information Entropy (IE) for complexity. Wilcoxon signed-rank tests (significance: $p < 0.05$) and Cliff's delta ($δ$) were used to measure statistical differences and effect sizes. Results: Lateral views significantly outperformed frontal views for sagittal plane kinematics: step length (DTW: $53.08 \pm 24.50$ vs. $69.87 \pm 25.36$, $p = 0.005$) and knee rotation (DTW: $106.46 \pm 38.57$ vs. $155.41 \pm 41.77$, $p = 0.004$). Frontal views were superior for symmetry parameters: trunk rotation (KLD: $0.09 \pm 0.06$ vs. $0.30 \pm 0.19$, $p < 0.001$) and wrist-to-hipmid distance (MCC: $105.77 \pm 29.72$ vs. $75.20 \pm 20.38$, $p = 0.003$). Effect sizes were medium-to-large ($δ: 0.34$--$0.76$). Conclusion: Camera view critically impacts gait parameter accuracy. Lateral views are optimal for sagittal kinematics; frontal views excel for trunk symmetry. Significance: This first systematic evidence enables data-driven camera deployment in 2D gait analysis, enhancing clinical utility. Future implementations should leverage both views via disease-oriented setups.
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