Development and Prospective Validation of Wearable Sensor-Based Gait Metric for Individuals with Lower-Limb Amputation

Lower-limb amputation is associated with persistent gait asymmetries and functional limitations that are not fully captured by conventional clinical outcome measures. This study aimed to develop and prospectively validate a wearable sensor-based Gait Goodness Score (GGS) derived from ensemble classifiers to summarize overall gait quality during supervised clinical walking. The algorithm was previously trained using inertial measurement unit data and clinically meaningful temporal–spatial features. In the present prospective, observational validation study, medically stable adults with lower-limb amputation performed supervised 10 m walk tests in outpatient rehabilitation settings, during which step-based GGS values were collected. Associations between GGS and established clinical measures, including walking velocity, Amputee Mobility Predictor (AMP) score, and Timed Up and Go (TUG) durations, were examined. GGS demonstrated significant differences across functional levels and amputation levels and showed strong associations with walking velocity and AMP score, with a significant moderate-to-fair association also observed for TUG and PLUS-M. These findings support the validity of GGS as a quantitative, sensor-derived metric of gait quality during supervised clinical walking in individuals with lower-limb amputation.