A step towards dynamic foot classification: Functional grouping using ankle joint frontal plane motion in running

The premise behind static foot classification suggests structure dictate's function. However, the validity of this has been challenged, as weak association between static foot type and dynamic motion exists. This has led to calls for dynamic assessments and classification of feet based on functional motion, yet methods to do this have been seldom explored.Within a group of runners do homogenous sub-groups of ankle joint complex (AJC) frontal plane motion exist?A k means clustering analysis was conducted on the frontal plane AJC motion patterns of a group of healthy adults running barefoot (n = 42) to identify functional movement groups. Once identified, statistical parametric mapping was employed to determine the differences between clusters across stance. The identified clusters were used to determine dynamic foot type; an agreement analysis was conducted between the newly defined foot types and the Foot Posture Index (FPI-6).Two distinct clusters were identified. Waveform analysis identified that cluster 1 displayed significantly (p 0.001) less AJC eversion between 0% and 97% of the stance phase compared to cluster 2, with the differences between clusters associated with large effect sizes (g1). Based on the displayed kinematic profiles, cluster 1 was defined as a Neutral Dynamic Foot Type (NeutralWe demonstrated a protocol to classify a runner's foot type derived directly from AJC motion during running. Poor agreement between the dynamic and static classification measures further evidence that these assessments are not analogous. Our results question the validity of static classification when looking to characterise the foot during running, suggesting dynamic assessments are more appropriate to reflect the foots functional response.