The effect of normal gait on acromion trajectory quantification

Shoulder motion is key to gait, and its quantitative trajectory offers insights for biomechanical evaluation and gait-based identification. This study explored how 3D acromion (SAE) trajectories affect intra-individual gait stability, inter-individual variability, and person identification. Using motion capture, 65 subjects’ SAE trajectories (normal walking) were projected onto sagittal and horizontal planes and analyzed via sway mode (α, vertical symmetry) and torsional mode ( β , horizontal symmetry). A gait-specific dynamic time warping algorithm quantified trajectory similarity. Sagittal analysis identified 3 sway types ( α < 1.00, = 1.00, > 1.00), and horizontal analysis distinguished 3 morphological patterns. Sagittal-plane SAE trajectories exhibited significant inter-subject variability, with Rank-1 recognition rates of 84.62% (L_SAE) and 81.54% (R_SAE), AUC values near 0.993 and EER below 5.00%. In contrast, horizontal-plane SAE trajectories had weaker discriminative capacity, with Rank-1 rates of 39.85% (L_SAE) and 39.54% (R_SAE), and EER of 20.61% and 22.11%, respectively. SAE analysis captured unique upper-body gait features, aiding identification or biomechanical interpretation and supporting multimodal gait analysis, clinical assessment, and surveillance.