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The effects of an ankle foot orthosis on cerebral palsy gait: A multiple regression analysis
Insights
A new multiple regression normalization (MR) method improves analysis of gait data in children with cerebral palsy (CP). This approach better evaluates the effectiveness of ankle-foot orthoses (AFOs) and aids in gait classification.
Area of Science:
- Biomedical Engineering
- Gait Analysis
- Pediatric Orthopedics
Background:
- Cerebral palsy (CP) significantly affects gait in children.
- Standard normalization methods may obscure the effects of interventions like ankle-foot orthoses (AFOs).
- Accurate gait analysis is crucial for assessing treatment efficacy in children with CP.
Purpose of the Study:
- To develop a multiple regression (MR) normalization strategy for gait data.
- To decorrelate physical properties and walking speed from spatiotemporal gait parameters.
- To assess the effect of AFOs on gait in children with CP using the MR approach.
Main Methods:
- Collected spatiotemporal gait data from 51 children with CP and 34 healthy controls.
- Normalized data using standard dimensionless equations (DS) and a novel MR approach.
- Compared gait parameters with and without AFOs in children with CP.
Main Results:
- DS normalization showed differences in stride length and swing time with AFOs.
- MR normalization revealed significant differences in most spatiotemporal parameters (except double support time) between children with CP with and without AFOs.
- MR normalization demonstrated that AFOs brought spatiotemporal parameters closer to those of controls.
Conclusions:
- The MR approach offers a more sensitive method for evaluating AFO effectiveness in children with CP.
- This normalization strategy can aid in assessing conservative interventions and surgical outcomes.
- The MR approach shows potential for use in machine learning-based gait classification.
Abstract:
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.
