Throughout childhood, braincase and face grow at different rates and therefore exhibit variable proportions and positions
relative to each other. Our understanding of the direction and magnitude of these growth patterns is crucial for many
ergonomic applications and can be improved by advanced 3D morphometrics. The purpose of this study is to investigate
this known growth allometry using 3D imaging techniques. The geometry of the head and face of 840 children, aged 2 to
19, was captured with a laser surface scanner and analyzed statistically. From each scan, 18 landmarks were extracted
and registered using General Procrustes Analysis (GPA). GPA eliminates unwanted variation due to position, orientation
and scale by applying a least-squares superimposition algorithm to individual landmark configurations. This approach
provides the necessary normalization for the study of differences in size, shape, and their interaction (allometry). The
results show that throughout adolescence, boys and girls follow a different growth trajectory, leading to marked
differences not only in size but also in shape, most notably in relative proportions of the braincase. These differences can
be observed during early childhood, but become most noticeable after the age of 13 years, when craniofacial growth in
girls slows down significantly, whereas growth in boys continues for at least 3 more years.
Fall protection harnesses are commonly used to reduce the number and severity of injuries. Increasing the efficiency of harness design requires the size and shape variation of the user population to be assessed as detailed and as accurately as possible. In light of the unsatisfactory performance of traditional anthropometry with respect to such assessments, we propose the use of 3D laser surface scans of whole bodies and the statistical analysis of elliptic Fourier coefficients. Ninety-eight male and female adults were scanned. Key features of each torso were extracted as a 3D curve along front,
back and the thighs. A 3D extension of Elliptic Fourier analysis4 was used to quantify their shape through multivariate statistics. Shape change as a function of size (allometry) was predicted by regressing the coefficients onto stature, weight and hip circumference. Upper and lower limits of torso shape variation were determined and can be used to redefine the design of the harness that will fit most individual body shapes. Observed allometric changes are used for adjustments to the harness shape in each size. Finally, the estimated outline data were used as templates for a free-form deformation of
the complete torso surface using NURBS models (non-uniform rational B-splines).