The multifeature gait score: An accurate way to assess gait quality

Abstract

Purpose: This study introduces a novel way to accurately assess gait quality. This new method called Multifeature Gait Score (MGS) is based on the computation of multiple parameters characterizing six aspects of gait (temporal, amplitude, variability, regularity, symmetry and complexity) quantified with one inertial sensor. According to the aspects described, parameters were aggregated into partial scores to indicate the altered aspect in the case of abnormal patterns. In order to evaluate the overall gait quality, partial scores were averaged to a global score. Methods: The MGS was computed for 3 groups namely: healthy adult (10 subjects), sedentary elderly (11 subjects) and active elderly (20 subjects). Data were gathered from an inertial sensor located at the lumbar region during two sessions of 12m walking. Results: The results based on ANOVA and Tukey tests showed that the partial scores with the exception of those which describe the symmetry aspect were able to discriminate between groups (p<0.05). This significant difference was also confirmed by the global score which shows a significantly lower value for the sedentary elderly group (3.58 ±1.15) compared to the healthy adults (5.19 ±0.84) and active elderly (4.82 ±1.26). In addition, the intersession repeatability of the elaborated global score was excellent (ICC = 0.93, % SEM = 10.81). Conclusion: The results obtained support the reliability and the relevance of the MGS as a novel method to characterize gait quality.