Center of pressure metrics derived from spatially registered typically developing data

Pedobarography is a commonly used testing procedure in clinical gait analysis, yet has limited roles in quantification for treatment planning, outcome assessment, and classification. Spatial registration between plantar pressure and motion capture data allows for accurate quantitative assessment and metric development based on a typically developing cohort.

This study assesses the validity of new center of pressure based metrics of anatomically registered pedobarography data by evaluating kinematic relationships over a broad spectrum of feet and by evaluating the sensitivity of these metrics to pathologies, interventions, and outcomes in two common clinical foot pathologies.

3D trajectories from retroreflective markers were recorded to establish a single foot axis simultaneous with plantar pressure mat data spatially calibrated to a global coordinate system. Indices for clinical populations were determined as mediolateral (MLI, |MLI|, MFI) and anteroposterior (API, |API|) deviations of center of pressure excursions from typically developing feet. 198 feet were retrospectively identified to evaluate relationships between mediolateral (ML) indices and foot kinematics over a spectrum of foot pathologies. Additional feet from two broad pathologic foot types, planovalgus (PV) and cavovarus (CV), were assessed pre and post-surgery to determine sensitivity to pathology, surgical intervention, and outcomes.

ML indices and supination were highly correlated (r² > 0.5). Two mediolateral indices (MLI, MFI) and one anteroposterior index (|API|) demonstrated significant differences between typical and PV feet, with the MFI index also exhibiting significant improvement with surgery. All three mediolateral indices and |API| demonstrated differences between typical and cavovarus feet, with |API| significantly improving with surgery. Changes in API also correlated with patient goals.

Spatial registration between plantar pressure center of pressure and motion capture data allows calculation of indices that reflect foot function and are sensitive to foot pathologies and treatment outcomes.