Kinematic cluster analysis of the crouch gait pattern in children with spastic diplegic cerebral palsy using sparse K-means method

• Published in: Clinical biomechanics (Bristol) 2021-01, Vol.81, p.105248-105248, Article 105248
• Main Authors: Abbasi, Leila, Rojhani-Shirazi, Zahra, Razeghi, Mohsen, Raeisi-Shahraki, Hadi
• Format: Article
• Language: English
• Subjects: Cerebral palsy; Crouch gait pattern; High dimensional cluster analysis; Sparse K-means
• ISSN: 0268-0033; 1879-1271
• DOI: 10.1016/j.clinbiomech.2020.105248

Crouch gait pattern is a common gait pattern in children with diplegic cerebral palsy with excessive knee flexion throughout stance phase. Few studies have grouped this pattern of gait and usually have examined only the features of gait in the sagittal plane and mostly lower extremities without considering pelvis and trunk behavior. Studies usually categorize the gait pattern according to important variables from the researcher's point of view. Sparse K-means is high dimensional clustering methods that perform clustering and variable selection simultaneously even with low sample size and large number of variables. Our aim was to define existing clusters of crouch gait pattern in children with spastic diplegic cerebral palsy. Cluster analysis was applied on the lower extremity, pelvis and trunk gait kinematics data of 64 limbs of children with crouch gait pattern and 64 limbs of typically developing children. Eighty-nine kinematic variables were used as input variables for clustering. Four clusters of crouch gait pattern were defined. Sparse K-means identified influential variables and identified the knee and hip flexion as a major factor in clustering. Kinematic of the trunk, pelvis and ankle was determined in each cluster. Trunk and pelvis kinematic features were strongly correlated with the knee and hip joint flexion severity. Obtained clusters were confirmed observationally. With increasing knee flexion, the kinematic of the trunk and pelvis were further away from the patterns of typically developing individuals. The clusters ranking appear to be reasonable based on the crouch severity. •Sparse K-means is used to cluster the gait pattern in children with cerebral palsy.•Variables are weighted and most important variables in clustering are identified.•Four clusters of crouch gait pattern are selected as the optimal clusters number.•The knee flexion was confirmed as the most important variable in clustering.•As the amount of knee flexion increases, other joints involvement increases too.