Comprehensive Mechanics-Based Metrics for Quantification of Head Impacts from Kinematics

Mechanics-based metrics derived from principles of mechanical power and energy offer a comprehensive approach to characterizing head acceleration events (HAEs) recorded by impact sensing devices. However, systematic evaluation of diverse metric formulations remains limited. The objective of this study was to establish and compare a comprehensive set of 40 mechanics-based metrics for characterizing HAEs, applied to low-severity soccer headers as a demonstration dataset. A custom instrumented mouthpiece system collected head kinematic data from 18 subjects across 308 headers. Exploratory unsupervised analyses were intended to characterize the internal structure of the metric space rather than establish predictive validity or generalizability beyond this dataset. Principal components analysis revealed three latent metric families (proportional, rotational, translational/combined), with mechanics-based metrics demonstrating stronger loadings on principal components compared to peak resultant kinematics alone, suggesting they capture additional dimensions of biomechanical variability within this metric space. K-means clustering identified four distinct kinematic impact profiles, demonstrating that meaningful biomechanical structure exists even within a homogeneous sample of low-severity impacts. A minimal reporting set spanning traditional peak metrics, one energy or power metric, and one proportional metric is recommended to facilitate cross-study comparisons. The forty metrics presented should not be interpreted as immediate improvements in injury prediction; but rather they may provide comprehensive and complementary biomechanical characterization that is useful for future analyses of exposure assessment, feature selection, and metric validation studies.