Abstract
Deforming 3D scanned data is an important and necessary procedure for the development of dynamic three-dimensional (3D) scanned anthropometry. The inaccuracies in joint center will cause error in deformation. Bell et al. developed the equations to predict hip joint center (HJC) based on anthropometric measurement of inter-anterior superior iliac spine distance (IAD). However, no previous study has reported on the reliability of IAD measurements in 3D scanned data, and therefore the effect on HJC estimates needs to be determined. Four measurers (2 trained/ 2 untrained) were recruited into this study to collect measurements of IAD in 3D scanned data under two situations (with/ without landmarks). The intra-class correlation (ICC) and technical error of measurement (TEM) were used to assess the reliability of the measurements. Results showed the untrained group had the lowest reliability and validity of IAD measurement in the without landmarks situation, and the error of HJC prediction in this situation was significantly higher than in the other situations (p<0.001). Both of training and use of landmarks improved the validity of measurement and HJC prediction; compared with training alone, attaching landmarks can significantly improve the reliability of measurement.
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Chiou, WK., Chen, BH., Chou, WY. (2011). The Effects of Landmarks and Training on 3D Surface Anthropometric Reliability and Hip Joint Center Prediction. In: Duffy, V.G. (eds) Digital Human Modeling. ICDHM 2011. Lecture Notes in Computer Science, vol 6777. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21799-9_1
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DOI: https://doi.org/10.1007/978-3-642-21799-9_1
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