Qualitative Assessment of Ballet Kinematics Algorithm: Case Study in the Glissade Saut de Chat.

Abstract

Background: Objective assessment of ballet execution remains limited by the subjective nature of expert evaluations, which often integrate stylistic interpretation and artistic expression. Objective: This study introduces the Qualitative Assessment of Ballet Kinematics (QABAK), a computational framework that models ballet jumps within a low-dimensional biomechanical space. QABAK evaluates execution quality using four targeted parameters: Recovery Effectiveness (RE), Slap Coordination (SC), Grand Battement (GB), and Ballon Efficiency (BE). Methods: Motion capture data from professional dancers performing the Glissade Saut de Chat (GSDC) were analyzed using QABAK. Computed scores were compared to expert assessments based on the Performance Competence Evaluation Measure (PCEM). Results: QABAK rankings demonstrated strong alignment with expert evaluations while exhibiting reduced score variability. Each parameter captured distinct biomechanical features contributing to jump quality. Conclusion: QABAK offers a structured, repeatable method for evaluating ballet movement that may complement expert judgment while reducing subjective variance. Its use of biomechanical decomposition within a simplified execution space highlights a promising approach to performance analysis in dance.