1st Joint ESMAC-GCMAS Meeting - Análise de Marcha
1st Joint ESMAC-GCMAS Meeting - Análise de Marcha
1st Joint ESMAC-GCMAS Meeting - Análise de Marcha
Create successful ePaper yourself
Turn your PDF publications into a flip-book with our unique Google optimized e-Paper software.
O-18<br />
3D HIP AND PELVIC GAIT PATTERN RECOGNITION IN CHILDREN WITH CP<br />
Desloovere, Kaat 1,2 , PhD, Molenaers, Guy 2,3 , PhD-MD, Daniels, Kim 1 , PT MSc, Van Campenhout,<br />
Anja 2,3 , MD, Corstjens, Hil<strong>de</strong> 1 , PT MSc<br />
1 Department of rehabilitation sciences, 2 Clinical Motion Analysis Laboratory of the University<br />
Hospital Pellenberg, 3 Department of Paediatric Orthopedics, KuLeuven, Belgium<br />
Summary/conclusions<br />
Cluster analysis was used to recognize typical patterns and to search for un<strong>de</strong>rlying<br />
pathological mechanisms which might explain the large inter-subject variability in hip and<br />
pelvic motion during gait in children with CP. Five typical gait patterns were clinically<br />
<strong>de</strong>scribed. Two groups of ol<strong>de</strong>r children presented with continuous internal hip rotation (one<br />
group with flexed hip and another with full hip extension at terminal stance), and two groups of<br />
young children with gradually increasing hip rotation during stance (also one group with flexed<br />
hip and another with full hip extension at terminal stance). A final group of mainly children<br />
with hemiplegia only showed mild hip problems. The 5 clusters were characterised by<br />
significant between-group differences for pelvic and hip gait parameters and for clinical<br />
measures of muscle contractures and strength, but not for clinical alignment measures.<br />
Introduction<br />
Children with cerebral palsy (CP) present with a variety of gait patterns and in general, there is<br />
a low correlation between clinical parameters (ROM, alignment, spasticity , strength and<br />
selectivity) and gait <strong>de</strong>viations [1]. Therefore, the un<strong>de</strong>rlying mechanisms of the pathological<br />
gait are still poorly un<strong>de</strong>rstood. Gait classification systems have been <strong>de</strong>veloped to structure<br />
and to create more insight into different gait patterns. However, most gait classifications only<br />
<strong>de</strong>scribe sagittal gait patterns, thereby mainly focusing on ankle, knee and sagittal hip motion.<br />
However, 3D hip and pelvic pathology is frequently observed in children with CP, and is<br />
known to be complex, influenced by a combination of bony <strong>de</strong>formities, increased tone, muscle<br />
contractures and weakness [2]. The purpose of the study was to evaluate whether different gait<br />
patterns could be statistically recognized and clinically <strong>de</strong>scribed for 3D hip and pelvic motion<br />
for a large group of ambulant children with CP, by using cluster analysis. It was hypothesised<br />
that the specific gait patterns would be related to diagnosis, age and clinical measurements<br />
(alignment, ROM, tone, strength and selectivity).<br />
Statement of clinical significance<br />
More insight into the typical 3D hip and pelvic gait patterns can help to un<strong>de</strong>rstand the<br />
un<strong>de</strong>rlying mechanisms of pathological gait, and eventually improve communication between<br />
clinicians and facilitate clinical <strong>de</strong>cision-making.<br />
Methods<br />
342 ambulant patients (189 with diplegia and 153 with hemiplegia) were selected for this<br />
retrospective study. The inclusion criteria were: (1) ambulation, without walking aids, (2) full<br />
gait analysis, including 3D kinematics, kinetics and EMG (VICON, AMTI, K-lab) and full<br />
clinical examination (ROM, spasticity, strength and selectivity) at 4 to 20 years of age. 40 gait<br />
parameters (average of 3 trials per subject) and 32 clinical examination parameters were<br />
<strong>de</strong>fined for each subject. To avoid the influence of inter-correlation between limbs, only one<br />
pathological si<strong>de</strong> per subject was inclu<strong>de</strong>d for further analysis. Non-hierarchical k-means<br />
clustering was used on the standardised data of a selection of 18 kinematic and kinetic<br />
parameters of hip and pelvis, resulting in 5 clusters. The <strong>de</strong>finition of the number of cluster<br />
was based on the study of intra and inter cluster variability and the frequency distributions of<br />
the clusters. The 5 clusters were clinically <strong>de</strong>scribed by comparing the gait parameters with the<br />
parameters of an age-related normal control group of 68 children. Mean and SD of all<br />
- 78 -