DCD kinematic signature

Six primary outcomes were retained: peak based smoothness (S1), Spectral Arc Length (SAL), Log Dimensionless Jerk (LDLJ), normalized agility score, PeakSD, and normalized Shannon entropy. They were organized into smoothness, agility/regulation, and complexity domains.All six outcomes were calculated separately for each trial. Trial-level values were then averaged within participant and Criticality condition. The final analytical unit was Participant × Criticality, preventing repeated trials from being treated as statistically independent observations. The dominant-hand trajectory was digitized frame-by-frame from video recordings using Kinovea and processed in MATLAB R2023a. The camera was positioned perpendicular to the plane of movement, and the analysis was two-dimensional. Position data were inspected for digitization errors before filtering and numerical differentiation. A fourth-order zero-phase Butterworth low-pass filter with a 5-Hz cutoff frequency was applied before calculation of velocity, acceleration, and jerk. Forward and reverse filtering minimized phase distortion. The 5-Hz cutoff was retained as the prespecified processing condition. Filtering is particularly important for jerk-based outcomes because differentiation can amplify high-frequency noise (Balasubramanian et al., 2015). A 5-Hz cutoff was selected as it effectively preserves the fundamental frequency components of voluntary, goal-directed human upper-limb movements while attenuating high-frequency differentiation noise (Winter, 2009).