Repeatability of a model for measuring multi-segment foot kinematics in children
Introduction
The measurement of three-dimensional lower body kinematics through the use of stereophotogrammetry has been well tested and validated over many years. Gait analysis now forms a major part of clinical decision making, particularly in the field of surgical treatment for children with cerebral palsy [1]. Conventional lower body models represent the pelvis, femur and lower leg as separate rigid bodies; however, the foot is routinely modelled only as a single vector, with no relative motion between or within its different segments. This provides inadequate information when determining treatment specific to the foot.
Measurement of foot kinematics is becoming increasingly common as motion analysis measuring systems become more accurate. Many research groups around the world are proposing multi-segment foot models, and it is important that the repeatability and clinical significance of these models be thoroughly investigated before they are routinely used to inform clinical decision-making. It is also necessary to standardise the analysis and reporting of results to allow comparisons between centres.
Most work to date has been carried out on healthy adult feet [2], [3], [4], [5], [6], [7], [8], [9], [10], [11] and these studies are mainly limited to the stance phase of gait. A limited amount of work has also been conducted on pathological feet [7], [12], [13], [14], again mainly in adults. No repeatability studies have been reported for measurements on children's feet. This population poses different challenges, the most significant being the small surface area of the foot and greater variability in gait [15]. There are many conditions that produce deformity in children's feet. For example, 90% of children with cerebral palsy develop some form of foot deformity resulting from abnormal forces being applied to the immature skeleton over periods of growth [16]. A valid and repeatable foot model for children is needed for understanding normal and pathological function, planning intervention and evaluating the outcome of treatment.
The purpose of the current study was to take our previously described multi-segment foot model validated for healthy adults [4] and adapt it for use in children over the entire gait cycle. Five variations of the adapted model were then tested to determine the most appropriate method for measuring inter-segment motion within the foot for both healthy and pathological conditions, such as cerebral palsy.
Section snippets
Materials and method
Fifteen healthy children aged 6–14 years (average age 9.5 years, 5 male and 10 female) were tested at the Oxford Gait Laboratory on three separate occasions. Visits were spaced between 2 weeks and 6 months apart. Each child had reflective markers placed on their dominant foot [4] and a conventional marker set on the lower body [17]. A 12 camera VICON 612 system (Vicon Motion Systems Ltd., Oxford, UK) was used to collect 3D kinematics of one foot and both lower limbs for each subject at 100 Hz. A
Results
Measured variables from foot kinematics for each subject were compared between days. For the default model, the patterns of movement were found to be consistent but some offsets between days were observed (Fig. 2). Within subject standard deviations were lowest in the sagittal plane (between 2° and 4°). The highest variability was in the transverse plane at the hindfoot and forefoot; with standard deviations of 8° and 7°, respectively.
All five variations of the model were compared for
Discussion
A comprehensive study has been carried out on the repeatability of foot kinematics in healthy children and this has provided objective data on which to base a final version of the model.
For the default model, good consistency between patterns of foot motion was observed but some offsets in the curves between days were noted. This was quantified by comparing intra-subject standard deviations in peak and range values for the inter-segment angles where the peak values between adjacent segments
Acknowledgements
We acknowledge the generous support of Action Medical Research in funding this project. We would also like to thank Maria Seniorou and the rest of the team at the Oxford Gait Laboratory for their assistance, and the Centre for Statistics in Medicine, Oxford University for statistical support.
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