Cluster analysis for the extraction of sagittal gait patterns in children with cerebral palsy

Abstract

Classification of gait disorders would facilitate standardisation of gait management and communication across professional boundaries. In the past, such classification was undertaken using a variety of approaches with often unclear methodology and validation procedures. This study describes the application of hierarchical cluster analysis on sagittal kinematic gait data derived from 56 children with cerebral palsy and 11 neurologically intact children in order to define existing clusters of gait patterns in the children's data. A structured rationale was developed to seek and validate the optimal number of homogenous gait types within the data resulting in 13 different gait clusters that were organised into ‘crouch gait type’, ‘equinus gait type’ and ‘other gait type’. Applying cluster analysis in combination with visual assessment of gait data and a structured protocol, we have been able to define valid gait groupings.