This study introduces a new measurement called the \(u_{shape}\) synchronization index (uSI). This metric uses voice recordings as a ’proxy’ for brain activity (phEG) to measure how well different brain regions, specifically those related to emotions and movement—work together during phonation. Building on a neuromechanical inversion pipeline, recorded phonation is transformed into probability-density phEG distributions. A \(u_{shape}\) synchronization index (uSI) is defined to capture the curvature of the \(\mu \) -band relative to its immediate neighbors ( \(\vartheta \) and high- \(\alpha \) ), a signature of impaired motor–affective coupling in Autism Spectrum Disorder (ASD). This index was applied to longitudinal phEG samples collected from two ASD participants (one male, one female), each contributing 12 sustained-vowel recordings over six years, and compared these case series against a reference database of 12 male and 12 female healthy controls. Methodological validation combined one-sided bootstrap inference on uSI, for univariate contrasts, and multivariate deviation. Results show that the uSI reliably identifies pronounced \(\mu \) -band troughs in multiple case recordings that exhibit subject-level heterogeneity and occasional discordance. It may be concluded that uSI is a promising, interpretable biomarker candidate that compresses complex spectral relationships into a single, testable index.