用复希尔伯特主成分分析，从无标记3D姿态数据中提取全身运动相位模式。
Phase-Separated Complex Hilbert PCA on Markerless 3D Pose Estimation Data: A Global Phase Network and Its Extension to a Continuous Field on the Body Surface
- 分阶段对运动数据做复希尔伯特主成分分析，提取全局相位模式。
- 发现躯干锚定的相位结构，执行阶段比准备阶段更一致（0.58 vs 0.38）。
- 将相位扩展到1079个体表顶点，实现身体表面连续相位场建模。
体育动作的运动链定量分析对表现评估与损伤预防至关重要。传统方法如运动序列（KS）和连续相对相位（CRP）仅限相邻关节对，缺乏整体协调统一框架；而分段功率流分析需力台与惯性参数，局限于实验室环境。本文在无标记3D姿态数据上，对每个运动阶段（后摆与下摆）分别应用复希尔伯特主成分分析（CHPCA），提取单一复特征向量表示主导的全身相位模式。流程包含全自动基于信号的相位分割（无需击打次数或静止位置先验），并扩展至1,079个体表网格顶点，使运动链表现为身体表面的连续相位场。在单人14次铁锤投掷试验中，框架揭示：(i) 躯干锚定的全局相位架构；(ii) 准备与执行阶段的功能不对称，由第一模态贡献率（45.5% vs 70.5%）与跨试次斯皮尔曼一致性（0.38 vs 0.58）量化；(iii) 骨骼关节与网格顶点间存在高度一致的重构（1,079个顶点，p < 10⁻¹⁰）。作为方法一致性检验，第一模态的成对相位差与所有190个关节对的CRP进行置换检验，相关系数ρ = 0.473，p = 0.0005。进一步对比第一模态振幅与动能动员方差，发现下摆阶段呈强正相关（ρ ≈ 0.71，骨骼与网格均成立），后摆阶段无相关性，表明该框架通过相位结构连接了运动学与动力学描述。
原文摘要 · Abstract (English)
Quantitative analysis of the kinematic chain in sports motion is essential for performance evaluation and injury prevention. Conventional methods such as the kinematic-sequence (KS) and continuous relative phase (CRP) are confined to adjacent joint pairs and lack a unified framework for whole-body coordination, while segmental power-flow analysis requires force plates and inertial parameters that restrict it to laboratory environments. We apply Complex Hilbert Principal Component Analysis (CHPCA) separately to each motion phase (backswing and downswing) on markerless 3D pose estimation data, extracting the dominant whole-body phase pattern as a single complex eigenvector. The pipeline further includes a fully automatic signal-based phase segmentation (no priors on strike count or rest location) and an extension to 1,079 body-surface mesh vertices, so that the kinematic chain is represented as a continuous phase field across the body. On 14 hammer-striking trials of a single subject, the framework reveals (i) a trunk-anchored global phase architecture, (ii) a functional asymmetry between preparation and execution phases quantified by Mode-1 contribution (45.5% vs. 70.5%) and inter-trial Spearman consistency (0.38 vs. 0.58), and (iii) a consistent reorganisation across both skeletal joints and mesh vertices ($p < 10^{-10}$ on 1,079 vertices). As a methodological consistency check, pairwise phase differences from the Mode-1 eigenvector are compared against CRP on all 190 joint pairs by a permutation test ($ρ= 0.473$, $p = 0.0005$). A correspondence analysis between Mode-1 amplitude and kinetic-energy mobilisation variance further shows a strong positive correlation in the downswing ($ρ\approx 0.71$ on both skeleton and mesh) and no correlation in the backswing, indicating that the proposed framework bridges kinematic and kinetic descriptions of coordination through phase structure.
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