The Advantage of Gait Pattern Assessment in Patients With Osteoarthritis Using Pearson Correlation Coefficient and SMAPE: A Case Series

Abstract

Objective: To assess patient gait ability by capturing both trend and scale aspects, this study proposes a method using the Pearson correlation coefficient and symmetric mean absolute percentage error (SMAPE).Methods: Gait patterns from three patients with hip osteoarthritis (OA) were analyzed using kinematic and kinetic data. In each case, using MAPE or Pearson correlation alone failed to provide a reliable assessment, revealing limitations in capturing the full characteristics of gait patterns.Results: The combined use of Pearson and SMAPE effectively identified gait abnormalities across all cases. This integrated approach offered a more accurate and comprehensive evaluation than single-metric methods.Conclusion: The findings highlight the importance of considering both trend and scale in gait analysis. The proposed dual-metric methodology overcomes the limitations of conventional and single-metric approaches, enabling a clearer understanding of gait characteristics in patients with hip OA.