The aim of this study was twofold. Firstly, to develop a multiple regression normalization (MR) strategy to decorrelate physical properties and walking speed from spatiotemporal gait data in healthy children; and secondly, to use this MR approach to identify the effect of a solid ankle foot orthosis (AFO) on gait in children with cerebral palsy (CP). Spatiotemporal gait data during self-selected walking were obtained from 51 children with diplegic CP and 34 aged-matched healthy controls. Data were normalized using standard dimensionless equations (DS) and a MR approach. Stride length, stance time, swing time, and double support time were significantly different between children with CP and healthy controls using DS (p<;0.05); however, only stride length and swing time were significantly different when children with CP walked with and without an AFO. Normalizing gait data using DS demonstrated significant differences in cadence and step time in children with CP when wearing an AFO compared to the controls (p<;0.05). In contrast, MR normalization revealed significant differences in all spatiotemporal parameters between children with CP with and without an AFO, except double support time. After MR normalization, spatiotemporal parameters in children wearing an AFO became closer to those of the controls, except for double support time. The MR approach presented will assist in evaluating the effectiveness of conservative interventions such as AFOs in children with CP, as well as in surgery, and may be useful in gait classification using machine learning.
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