Measuring gait symmetry in children with cerebral palsy using the SmartShoe

Abstract

Cerebral palsy (CP) is a group of non-progressive neuro-developmental conditions occurring in early childhood that causes movement disorders and physical disability. Many affected children have impaired function in movement and limitations in mobility. Measuring gait symmetry is essential in assessing clinical outcomes of rehabilitation. Modern sensor technology has made it possible to measure gait unobtrusively in the community. However, no wearable systems that allow for gait symmetry measurement in free living have been investigated for children with CP. In this study, data was collected from three children with CP by a wearable shoe sensor system (SmartShoe) in a community environment and the gait symmetry ratio was estimated from the sensor data prior and post rehabilitation therapy. The sensor data were processed by algorithms including data preprocessing, posture and activity classification, and calculation of symmetry ratio of stance. The gait symmetry metrics extracted by the automatic algorithms closely match the metrics manually estimated on the sensor data with an average mean absolute error of 1.235%), suggesting that the proposed method may be an effective way to evaluate rehabilitation progress in the community setting.