Abstract
Clinical gait analysis incorporating three-dimensional motion analysis plays a key role in planning surgical treatments in people with gait disability. The position of the Hip Joint Centre (HJC) within the pelvis is thus critical to ensure accurate data interpretation. The position of the HJC is determined from regression equations based on anthropometric measurements derived from relatively small datasets. Current equations do not take sex or age into account, even though pelvis shape is known to differ between sex, and gait analysis is performed in populations with wide range of age. Three dimensional images of 157 deceased individuals (37 children, 120 skeletally matured) were collected with computed tomography. The location of the HJC within the pelvis was determined and regression equations to locate the HJC were developed using various anthropometrics predictors. We determined if accuracy improved when age and sex were introduced as variables. Statistical analysis did not support differentiating the equations according to sex. We found that age only modestly improved accuracy. We propose a range of new regression equations, derived from the largest dataset collected for this purpose to date.
Highlights
Clinical gait analysis incorporating three-dimensional motion analysis plays a key role in planning surgical treatments in people with gait disability
A common application of motion analysis in the clinical setting is gait analysis, which plays a key role in planning orthopaedics surgical treatments in persons with walking disabilities[1,2]
The sample characteristics, the coordinates of the hip joint centres (HJC) and anthropometric measurements are summarized in Table 1 of the supplementary material
Summary
Clinical gait analysis incorporating three-dimensional motion analysis plays a key role in planning surgical treatments in people with gait disability. The position of the HJC is determined from regression equations based on anthropometric measurements derived from relatively small datasets. A common application of motion analysis in the clinical setting is gait analysis, which plays a key role in planning orthopaedics surgical treatments in persons with walking disabilities[1,2]. The location of the hip joint centres (HJC) is an important part of biomechanics modelling and has repercussion in accuracy and subsequent interpretation of gait data. Existing regression equations estimate the location of the HJC with variable accuracy, from 1.5 cm to more than 3 cm[7,8,9,10,11,12]. The aim of this study was to investigate whether sex and/or age specific regression equations improve the accuracy in locating the HJC
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